Current Research Topics for the DEVCOM ARL BAA For

Current Research Topics for DEVCOM ARL BAA For Foundational Research

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Current Research Topics for the

DEVCOM ARL BAA For Foundational Research

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Disclaimer

All current ARL research topics can be found at: https://www.arl.army.mil/opportunties/arl-baa.

Changes to these topics will be made using the website on an as needed basis. This document is

a printed copy of the current ARL research topics as of the noted print date. ARL maintains a

daily static snapshot of the ARL research topic website to ensure submissions are aligned with

listed research topics on the day of submission. The available Army Research Office (ARO)

topics are listed alphabetically followed by an alphabetical listing of the Army Research

Directorate (ARD) topics. Interested parties are encouraged to continually browse the ARL

research topic website and review the ARL BAA for instructions on submissions.

The DEVCOM ARL Broad Agency Announcement for Foundational Research,

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is available on https://www.grants.gov/ and https://sam.gov/

Link to all current ARL research topics

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Available Army Research Office (ARO) Research Topics

The available Army Research Office (ARO) topics are listed in alphabetical order.

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Army Research Office (ARO) Research Topic

Advanced Learning-Enabled Intelligent Cyber Physical SystemsTitle:

ARL-BAA-0032Announcement ID:

TPOC: MaryAnne Fields, PhD - [email protected] - (919) 549-4350

ARL Office: Army Research Office (ARO)

Discipline: Computer Science;Data Sciences and Informatics;Mathematics and Statistics

ARL Foundational Research Competencies: Military Information Sciences;Network, Cyber,

and Computational Sciences

Army Modernization Priorities: Future Vertical Lift;Next Generation Combat Vehicle

Keywords: Intelligent Systems, Interaction, Assured Operations, Online learning, Robust

Intelligence, World Models, Memory Systems, Causality

Description:

Intelligent cyber physical systems play an increasingly important role in civilian and military

settings. With few exceptions, current intelligent systems are restricted to highly constrained

environments for short duration missions. Future systems will need to perform a variety of tasks

in complex, possibly contested, open worlds for extended periods of time. One important

characteristic of open worlds is that the intelligent system will encounter new contexts, activities,

and objects that will require it to adapt previously trained algorithms. Advanced capabilities in

learning, reasoning, interaction, and assured operations are essential to the development of

intelligent systems that can greatly enhance the Army's mobility, agility, lethality, and

survivability in future conflicts.

ON-LINE LEARNING THEORY, METHODOLOGY, AND TECHNIQUES

Over the past 50 years, machine learning has made great strides in classification, natural

language processing, and task learning. However, machine learning still lacks the rigor, agility,

and flexibility necessary to operate in complex, contested open worlds. This thrust focuses on

establishing a theoretical foundation for on-line or continuous machine learning. New learning

approaches will need to address both the dimensionality challenges and temporal characteristics

that may be evolving continuously. In addition, new techniques must address robustness to

enable the learning system to deal with novelty, noise, observation errors and potentially

malicious input that aim to disrupt learning. Innovative approaches to continuous learning will

allow systems to adapt to changing contexts and environments while maintaining previously

learned knowledge. Under this thrust, we investigate approaches that help the intelligent systems

deal with dynamic environments, devise new, transferable skills, and cope with unknown

situations.

While end-to-end learning may be important for certain applications, it may not be an effective

approach for the complex environments typical of most battlefields. Instead, there is a need for

compositional learning systems in which each component may learn primitive actions that are

later combined, and adapted, to solve complex long-horizon manipulation problems. Research is

needed to understand how to express and learn the preconditions and post-conditions for each of

the primitive actions. Linking elements from a library of primitives and adapting the ensemble to

solve an existing problem is also an outstanding issue. Automated curriculum learning in which

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the CPS devises its own learning strategy is an open research area. Important issues in this area

include generating sample task environments from observation, memory and simulation;

sequencing those task into an effective curriculum; and transferring the learning as the tasks

become more complex.

DECISION MAKING FOR THE OPEN WORLD

Long duration operations require CPSs to continually reason, make decisions, or take actions

with very limited knowledge of the pertinent events or objects that could impact those decisions.

In real world missions, systems often address multiple near-simultaneous tasks to accomplish

their objectives - on a battlefield, systems need to travel to a location while searching for

potential adversaries and sharing information with teammates. Architectures that draw from

psychological models for human decision making, such as Dual Process theory, may enable

CPSs to effectively distribute the processing for near-simultaneous reasoning tasks. Advances in

risk-aware online planning will enable autonomous systems to balance potentially conflicting

objectives and operate safely in poorly understood environments. CPSs also need to develop a

sense of "'causality" that discovers relationships between objects and events and allows the

system to incorporate temporal and spatial information into the reasoning processes.

Storing and accessing information is vital to long term mission. Not all pertinent information is

collected at the same time: new research in memory systems will enable cyber physical systems

to determine what information, in what form, it needs to store to support future actions that may

or may not relate to its current action. Memory systems are not simply information stores -

processes like reflection, abstraction, and learning enable CPSs to develop new information.

Retrieval mechanisms are very important - information is not useful unless the system can recall

it when it is needed. Research to understand effective memory structure and processes will

benefit from a collaboration with cognitive scientists to understand memory in biological

systems. New approaches are needed to address potential issues with memory systems such as

catastrophic or forgetting, limited storage capacity, and development of new methods to

efficiently use external knowledge stores.

INTERACTION

Future autonomous systems must interact physically with humans and other intelligent systems

operating in the same space, remotely with spatially distant entities, and virtually in cyberspace

with intelligent software agents. New research in human-robot interaction and robot-robot

teaming will enable humans and robots to share the same space and work together on complex

tasks. Research in Ad-hoc teamwork will enable entities (human and systems) to dynamically

join together to address a specific problem, then pursue separate tasks after the problem is

solved. In this type of teaming, there is no prior coordination between agents and we cannot

assume that the entities share the same types of learning algorithms or reward structures or that

they have prior agreements regarding action coordination and information sharing. Some of the

important research problems within ad-hoc teaming are: ensuring that actions are understandable

to fellow teammates; modeling the capabilities of team members; including humans in the

ad-hoc teams, and dynamically modeling the performance of both the team and the individuals.

Explicit Human-Robot interaction has been extensively explored throughout the last decade.

Implicit Human-Robot interaction, on the other hand, is relatively unexplored. In this case,

humans may not directly interact with an intelligent system but instead take actions that the

system could use as input. The human actions may be intentional, unintentional or even

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unconscious but they are a rich source of signals for learning or cooperative actions. These

implicit actions may also provide context information that could be used to adapt a previously

learned behavior to a new environment. Some important research topics in this area include:

identifying implicit signals, the value of implicit robot-human signals, and context-aware

interaction.

ASSURED OPERATIONS

Assured operations require a deep understanding of how a complex system composed of several

components, including mechanical systems, computational hardware, and software algorithms

operates as a coordinated system. In much the same way as the community is trying to

understand the behavior of neural networks, which are composed of layers of mathematical

functions, this topic seeks to understand how information and actions flow from the lowest levels

of the system to system level decisions and actions. Along those lines, new theory and principles

are needed to understand the impact of both gradual and abrupt changes at the component level

on the evolution of the entire system. Investigating modularity and compositionality will enable

the system to address the multiple near-simultaneous problems it is likely to encounter in long

term operations. New theories in information sharing in dynamic environments will lay the

foundation for accountability and provide clear criteria for component-level and global

input/output specification (in terms of computation, rate, semantics, ..) that can be used to: train a

learning component, optimize outputs of a planning component, and test individual and systems

level components. As these areas mature, they will provide a firm mathematical foundation for

systems-level research in learning-based design, performance guarantees, and robustness to

degraded components.

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Army Research Office (ARO) Research Topic

Atomic and Molecular Physics (AMP)Title:

ARL-BAA-0022Announcement ID:

TPOC: Meg Shea, PhD - [email protected] - 240-941-4880

ARL Office: Army Research Office (ARO)

Discipline: Computer Science;Materials Science;Physics

ARL Foundational Research Competencies: Network, Cyber, and Computational

Sciences;Photonics, Electronics, and Quantum Sciences;Weapons Sciences

Army Modernization Priorities: Assured PNT;Long Range Precision Fires;Network/C3I

Keywords:

Description:

Topics of interest within Atomic and Molecular Physics (AMP) include:

Quantum degenerate atomic gases, both Bose and Fermi, their excitations and properties,

including mixed species, mixed state, and molecular;

Quantum enhanced precision metrology;

Nonlinear processes;

Quantum systems in cavities;

Collective and many-body states of matter; and

Emerging areas.

There is an interest in emerging areas of AMO physics such as collective states of matter,

emergent lattices in quantum gases, non-equilibrium many body dynamics, advanced quantum

simulation, and metrology in non-ideal environments. Research efforts within the AMP fall

within two thrust areas: Advanced Quantum Capabilities and Novel Quantum Methods. It is

anticipated that research efforts within these areas will lead to applications including novel

materials, efficient computational platforms, and exquisite quantum sensors.

Advanced Quantum Many-body Dynamics

The focus of this thrust is the development and study of strongly correlated many-body systems.

The quantum simulator portion of the thrust seeks research on novel techniques and studies that

leverage our control and understanding of simple quantum mechanical systems to explore more

complex quantum effects and materials. The effort seeks the validation of many-body quantum

theories through the development of experimental tools including quantum gas microscopes,

atom-array experiments, synthetic gauge fields, mixed species, and novel interactions.

Complimenting this effort will be the inclusion of foundational investigations into quantum

mechanics, such as entanglement, many-body localization, collective modes, and entropy. To

take advantage of the precision inherent in future quantum devices, these systems will need to

connect to the classical world in such a manner that allows them to sample the signal of interest

while remaining robust to noisy environments. Consequently, studies of how the quantum

system interacts with classical world, and the quantum-to-classical boundary are also of interest.

Investigating how to maximize both the quality and quantity of entanglement within these

systems will be a priority. General issues of quantum coherence, quantum interference,

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entanglement growth, entanglement purity, and non-equilibrium phenomena, as well as

discovering new scientific opportunities are also of interest.

Novel Quantum Metrology

The AMP Program has a general interest in exploring fundamental AMP that may impact future

Army capabilities. This thrust is divided into two main areas: precision metrology beyond the

standard limit and harnessing collective many-body states to improve quantum sensing. The

Novel Quantum Metrology efforts will expand the foundations of quantum measurement into

new areas that seek to exploit entanglement, spin-squeezing, harnessing collective-spin states,

developing back-action avoidance measurements, and other areas that increase fundamental

precision through interactions, including cavities and Rydberg atoms. It is expected that research

in this thrust will complement efforts in the Advanced Quantum Many-body Dynamics thrust

and vice versa. For example, collective many body states could be studied in optical lattices or

quantum gas microscopes and foundational research of entanglement are anticipated to provide

new metrological capabilities in non-ideal environments.

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Army Research Office (ARO) Research Topic

BiochemistryTitle:

ARL-BAA-0017Announcement ID:

TPOC: Stephanie A. McElhinny, PhD - [email protected] - (919) 549-4240

ARL Office: Army Research Office (ARO)

Discipline: Biological Sciences;Chemistry;Materials Science

ARL Foundational Research Competencies: Biological and Biotechnology Sciences;Sciences

of Extreme Materials

Army Modernization Priorities:

Keywords: Biotechnology, Bioengineering, Biomaterials

Description:

This program emphasizes basic research focused on understanding and controlling the activity

and assembly of biomolecules. Scientific advances supported by this program are anticipated to

enable the development of novel systems, materials and processes that enhance Soldier

protection and performance. Overarching goals of the program are to provide the scientific

foundations to expand the chemical diversity accessible by biomolecules and to support

biological activity outside of the cellular environment, including integration of biological

systems with synthetic systems.

The Biomolecular Specificity and Regulation thrust is focused on novel approaches to engineer

the specificity and regulation of biomolecules, either via modulation of natural mechanisms or

via design of non-natural mechanisms. Approaches to expand the chemical diversity of

ligands/substrates that are recognized/accepted by biomolecules and/or the products of

biocatalytic reactions beyond elements and chemical bonds common to natural biological

systems are of particular interest. This includes both individual enzymatic reactions as well as

multi-step biocatalytic pathways. The goal of this thrust is to develop novel engineered

approaches to modulate and control biomolecular activity, with emphasis on expanding the

chemical diversity accessible by biomolecules and achieving biomolecular control in

non-cellular contexts.

The Biomolecular Assembly and Organization thrust is focused on understanding the molecular

interactions and design rules that govern self-assembly of biomolecules into both naturally

occurring biomolecular structures and non-natural human-designed architectures. This thrust

aims to elucidate fundamental understanding of sequence-structure-property relationships in

natural biomolecular assemblies, biomaterials, and biological composites to enable rational

design of biological and hybrid biological/abiological assemblies with tailored properties and

functions. Biomolecular assembly across length scales is of interest, including discrete

multi-protein complexes or nucleic acid structures, as well as hierarchical protein or nucleic acid

assemblies and biological composites. This thrust includes homogeneous assemblies utilizing a

single building block, as well as heterogeneous systems in which a mixture of different

biomolecules and/or non-biological species (e.g., minerals, synthetic polymers) self-assemble.

Of particular interest are approaches to expand the chemical diversity of biomolecular

architectures beyond elements and chemical bonds common to natural biological systems. This

research thrust also includes the design of self-assembled biomolecular or hybrid

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biological/abiological architectures that provide control over the chemical environment and

spatial organization necessary to support complex biomolecular function in non-cellular

contexts, including artificial cells and cell-free systems.

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Army Research Office (ARO) Research Topic

BiomathematicsTitle:

ARL-BAA-0021Announcement ID:

TPOC: Virginia B. Pasour, PhD - [email protected] - (919) 549-4254

ARL Office: Army Research Office (ARO)

Discipline: Biological Sciences;Data Sciences and Informatics;Earth and Environmental

Sciences;Mathematics and Statistics;Network Science;Physics;Social Science

ARL Foundational Research Competencies: Biological and Biotechnology Sciences;Humans

in Complex Systems

Army Modernization Priorities: Soldier Lethality

Keywords: biomathematics, mathematical biology, theoretical ecology, theoretical

epidemiology, modeling

Description:

The introduction of Biomathematics as a separate area of basic research recognizes the

importance and specialized nature of quantitative methods, specifically mechanistic modeling, in

the biological sciences. Biology involves a large number of entities that interact with each other

and their environment in complex ways, and at multiple spatial and temporal scales.

Understanding how dynamics at different spatial scales come together to form a biological

system and understanding the dynamics of a system at intermediate timescales, as opposed to its

long term, asymptotic behavior, are critically important in biology, more so than in many other

fields.

This complexity makes biomathematics a highly interdisciplinary field that requires unique and

highly specialized mathematical competencies to quantify structure in these relationships. In fact,

progress in mathematical models of biological systems has traditionally been achieved by

making convenient simplifications; major advances in Biomathematics research continue to

require removing these assumptions (for example, stationarity, ergodicity and deterministic

nature) and finding ways to effectively model the essential complexity. Modeling techniques

currently utilized in the field range from agent-based approaches for determining the results of

individual behavior, whether those individuals be molecules, zooplankton, or humans, to

multi-compartmental modeling in physiology, epidemiology and neurobiology, to network

models involved in understanding ecosystem and human social dynamics, as well as

encompassing both deterministic and stochastic approaches. Research in control techniques is

also valuable for its potential application in militarily important areas such as bio warfare and

disease spread. Exciting new opportunities to advance the field are found in high risk attempts to

develop modeling techniques in areas of mathematics, such as algebra and topology, not

traditionally brought to bear on biological problems, advances in Bayesian statistics, a growing

recognition that the diffusion approximation is not necessarily adequate for many systems, and

the availability of large amounts of complex biological data.

The ultimate goal of the Biomathematics Program focuses on adapting existing mathematics and

creating new mathematical techniques to uncover fundamental relationships in biology, spanning

different biological systems as well as multiple spatial and temporal scales. One area of special

interest to the program is Neuromathematics, the mechanistic mathematical modeling of neural

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processes. Recent advances in neuroscience provide important foundations to begin

understanding how the brain works. Combined with experimental data, innovative mathematical

modeling provides an unparalleled opportunity to gain a revolutionary new understanding of

brain physiology, cognition (including sensory processing, attention, decision-making, etc.), and

neurological disease. With this new understanding, improved soldier performance, as well as

treatments for Post-Traumatic Stress Disorder, Traumatic Brain Injury, and other brain-related

disorders suffered by the warfighter will be able to be achieved more effectively, efficiently, and

ethically than via experimentation alone.

Thrust areas of the Biomathematics Program are as follows:

Fundamental Laws of Biology

The field of physics has long been "'mathematized" so that fundamental principles such as

Newton's Laws are not considered the application of mathematics to physics but physics itself.

The field of biology is far behind physics in this respect; a similar process of mathematization is

a basic and high-risk goal of the ARO Biomathematics Program. The identification and

mathematical formulation of the fundamental principles of biological structure, function, and

development applying across systems and scales will not only revolutionize the field of biology

but will motivate the creation of new mathematics that will contribute in as-yet-unforeseen ways

to biology and the field of mathematics itself. For example, heterogeneity/stochasticity is

ubiquitous in biological systems; is heterogeneity necessary for tipping points that result in

diseased individuals and epidemics and if so, what is its role? More generally, is heterogeneity in

biological systems necessary for their functioning or a problem to be overcome, or is the answer

system/function dependent?

Multiscale Modeling/Inverse Problems

Biological systems function through diversity, with large scale function emerging from the

collective behavior of smaller scale heterogeneous elements. This "'forward" problem includes

creating mechanistic mathematical models at different biological scales and synchronizing their

connections from one level of organization to another, as well as an important sub problem, how

to represent the heterogeneity of individual elements and how much heterogeneity to include in

the model. For example, the currently increasing ability to generate large volumes of molecular

data provides a significant opportunity for biomathematical modelers to develop advanced

analytical procedures to elucidate the fundamental principles by which genes, proteins, cells,

etc., are integrated and function as systems through the use of innovative mathematical and

statistical techniques. The task is complicated by the fact that data collection methods are noisy,

many biological mechanisms are not well understood, and, somewhat ironically, large volumes

of data tend to obscure meaningful relationships. However, traditionally "'pure" mathematical

fields such as differential geometry, algebra and topology, integration of Bayesian statistical

methods with mathematical methods, and the new field of topological data analysis, among

others, show promise in approaching these problems. Solutions to these types of multiscale

problems will elucidate the connection, for example, of stem cells to tissue and organ

development or of disease processes within the human body to the behavior of epidemics.

The "'inverse" problem is just as important as the forward problem. From an understanding of

the overall behavior of a system, is it possible to determine the nature of the individual elements?

For example, from knowledge of cell signaling, can we go back and retrieve information about

the cell? Although inverse problems have been studied for a long time, significant progress has

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been elusive. This thrust area involves innovations in spatial and/or temporal modeling of

multi-level biological elements with the goal of achieving a deeper understanding of biological

systems and eventually connecting top-down (data-driven) and bottom-up (model-based)

approaches.

Hybrid Modeling

While the Biomathematics Program has primarily been concerned with developing and using

mathematical modeling techniques to understand the mechanisms behind biological system

function, future predictions about a system have typically been achieved through statistical

modeling using available data; these methods are limited by their ability to make trustworthy

predictions only under the same situations under which the data was collected. This thrust seeks

to develop new methods that will take advantage of the strengths of both types of modeling, still

allowing the hypothesis and testing of biological mechanism while also allowing prediction

under an expanded set of conditions. These new methods will facilitate the utilization of the

increasingly available data in many areas of biology to expand our ability to understand and

predict biological systems and may be furthered through the use and development of existing and

new data analysis techniques. For example, can we develop a mechanistic model to understand a

cell's ability to repair damage to its DNA by incorporating Machine Learning?

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Army Research Office (ARO) Research Topic

Bionic ElectronicsTitle:

ARL-BAA-0069Announcement ID:

TPOC: Albena Ivanisevic, PhD - [email protected] - (301) 580-3020

ARL Office: Army Research Office (ARO)

Discipline: Biological Sciences;Chemistry;Electronics;Materials Science;Physics

ARL Foundational Research Competencies: Biological and Biotechnology Sciences;Humans

in Complex Systems

Army Modernization Priorities:

Keywords: bioelectronics, biotronics, bionic

Description:

This research area focuses on the discovery and manipulation of phenomena and the creation of

new processes where electronics and biology overlap at the cellular / sub-cellular level. This

length scale is where the amplitudes of many types of energies (e.g., electrostatic, mechanical,

and chemical terms) converge, and correspondingly, where electronics can have fundamental

biological impacts and where leveraging electronics capabilities at the nanoscale can yield

unique new understanding of the cellular and intracellular processes.

New electronic structures and materials are now able to focus localized static electric and

magnetic fields and electromagnetic fields at the nanoscale, which presents the opportunity to

selectively address and manipulate the organelles and membranes making up the structure of the

cell. Moreover, cell constituents can have a frequency dependent response to mechanical and

electromagnetic excitation, resulting in unique electronically enabled and controlled biological

experiments. Molecular and subcellular events at the biological interfaces or surfaces are key to

downstream biological dynamics. The stimulation or manipulation of these events by electronic

means provides the opportunity for unique control and experimentation that are orthogonal to

existing biochemical or genetic approaches. Ion flow, which is fundamental to inter- and

intra-cellular signaling and process control, is susceptible to electromagnetic influence and

produces electromagnetic signatures of cellular processes. The dynamics of charged and

polarized cellular components also produces minute displacement currents, and can produce very

large field distributions in a confined nanoscale space (e.g., within a protein scaffold or across a

lipid bilayer); both of which are subject to electromagnetic probing and analysis. The different

geometries of organelles within a cell result in different electromagnetic signatures and

sensitivities which can be leveraged for selective control of cellular processes. Proteins play a

role in almost every cellular process. As extremely large and complex molecules, they should

have electromagnetic and mechanical responses that can be exploited for control. The skeletal

protein assemblies of the cell, in particular, may offer a highway for the introduction of electrical

currents or mechanical vibrations. Bio-chemical or genetic alteration of the interface of the cell

and its components can introduce new electromagnetic properties, for example a new capability

for photosynthesis in bacteria or new electromagnetic responses. Cellular engineering of

membranes, cellular organelles, and proteins by the introduction of nano-particles and

bio-molecules can introduce new sensitivities and new functionality. Opto-genetics is a

well-established procedure for interrogating cells. Early attempts at "'magneto-genetics" have

been controversial, however "'electro- or RF-genetics" may offer new opportunities. There may

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also be inherently non-trivial quantum mechanical mechanisms linked to biological behaviors,

such as navigation. Inherently quantum phenomena such as the tunneling of electrons and

protons play a critical role in many intracellular processes and can be modulated or manipulated

with nanoscale electric fields. This research area seeks understanding and control of inter- and

intra-cellular phenomena at the micro- and nano-scale. The program facilitates highly innovative

extensions of techniques based on the unique capabilities of electronics as well as totally new,

complementary methods, addressing the internal function and electrical processes within a living

entity. Biotronics seeks to accomplish this with unprecedented spatial and temporal resolution

and with minimal disruption of "'normal" living cell function. The basic science questions being

addressed by the Biotronics program are geared to achieve a natural evolution into bionic

electronics. Through this evolution the goal is to us

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Army Research Office (ARO) Research Topic

Complex Dynamics and SystemsTitle:

ARL-BAA-0018Announcement ID:

TPOC: Dean R. Culver, PhD - [email protected] - (919) 549-4225

ARL Office: Army Research Office (ARO)

Discipline: Data Sciences and Informatics;Materials Science;Mathematics and

Statistics;Mechanics;Physics

ARL Foundational Research Competencies: Biological and Biotechnology Sciences;Energy

Sciences;Humans in Complex Systems;Mechanical Sciences;Military Information

Sciences;Network, Cyber, and Computational Sciences;Photonics, Electronics, and Quantum

Sciences;Sciences of Extreme Materials;Terminal Effects;Weapons Sciences

Army Modernization Priorities: Air and Missile Defense;Future Vertical

Lift;Network/C3I;Next Generation Combat Vehicle;Synthetic Training Environment

Keywords: nonlinear dynamics; mechanics; high dimensional; morphological computation;

chaos; embodied intelligence; hierarchical mechanics; heterogeneous systems; stochastic control;

stochastic learning

Description:

The Complex Dynamics and Systems program emphasizes fundamental understanding of the

dynamics, both physical and information theoretic, of nonlinear and nonconservative systems as

well as innovative scientific approaches for engineering and exploiting nonlinear and

nonequilibrium physical and information theoretic dynamics for a broad range of future

capabilities (e.g. novel energetic and entropic transduction, agile motion, and force generation).

The program seeks to understand how information, momentum, energy, and entropy flows and

transforms in nonlinear systems due to interactions with the system's surroundings or within the

system itself. Research efforts are not solely limited to descriptive understanding, however.

Central to the mission of the program is the additional emphasis on pushing beyond descriptive

understanding toward engineering and exploiting time-varying interactions, fluctuations, inertial

dynamics, phase space structures, modal interplay, practical control opportunities, and other

consequences of nonlinearity in novel ways to enable the generation of useful work, agile

motion, and engineered energetic and entropic transformations. Further information on the

current scientific thrust areas are detailed in the paragraphs that follow.

High-Dimensional Nonlinear Dynamics

Classical dynamics has produced limited fundamental insight and theoretical methods

concerning strongly nonlinear, high-dimensional, dissipative, and time-varying systems. For over

a century, qualitative geometric approaches in low-dimensions have dominated research in

dynamics. These approaches of reduced-order-modeling of high-dimensional dynamics are often

premised on empirical and statistical model fitting and are incapable of capturing the effects of

slowly growing instabilities and memory. The program seeks to develop novel theoretical and

experimental methods for understanding the physical and information dynamics of driven

dissipative continuous systems. It also seeks novel reduced-order-modeling methodologies

capable of retaining time-dependent and global nonlinearities. Novel research pertaining to the

analysis and fundamental physics of time-varying nonlinear systems and transient dynamics is a

high-priority.

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Embodied and Distributed Control, Sensing, and Actuation

This thrust develops deeper understanding, through supporting theory and experiment, of the role

of embodiment and dynamics on a physical system's capability to process information and

transform energy. Proposals emphasizing the mechanics and control of soft, continuous bodies

are encouraged along with novel experimental paradigms leveraging programmable printed

matter. Generally, this thrust strongly leverages advances in, and approaches from, sensory

biomechanics, neuromechanics, underactuated systems theory, and mechanical locomotion

dynamics to understand the motion of both articulated and continuum dynamical systems

operating in highly-dynamic environments. The scientific principles sought, however, are not

limited to biological movement and manipulation. Proposals are strongly encouraged that view

morphology in an abstract sense. For example, understanding morphology as a system's

symmetry, its confinement (e.g. chemical reactions), or its coupling topology.

Statistical Physics of Control and Learning

The program seeks to lay the foundations for an algorithmic theory of control and learning that

goes significantly beyond the state of-the-art in model predictive control and integrates novel

learning methodologies that are not mere variations of artificial neural networks and deep

learning. Additional goals of this program is to develop an experimentally tested theoretical

framework for controlling and creating new types of critical dynamics, phase transitions, and

universality classes by bringing together theory and physical principles in statistical dynamics

with control and dynamical systems theory (controlling statistical dynamics).

Topics of interest relating to this include: nonlinear control of distributions with non-Gaussian

uncertainty; non-Gaussian uncertainty representations; understanding relationships between

work absorption and dynamics in the presence of fluctuations leading to emergent prediction and

emergent centralization; steering multi-critical interacting dynamical systems toward desired

universal scaling behaviors; externally controlling the strength of stochastic fluctuations and

intrinsic noise in systems that are driven far from thermal equilibrium and display generic scale

invariance; and selectively targeting and stabilizing specific self-generated spatio-temporal

patterns in strongly fluctuating reaction-diffusion systems. Stochastic control at the microscale to

enable novel manipulation of the dynamics of synthetic and natural biomolecular machines is

also of interest.

Mechanics of Hierarchical and Heterogeneous Systems

Recent experimental, theoretical, and computational advancements have made it possible to

challenge macroscopic, continuum representations of inherently hierarchical systems like never

before - acknowledging that desirable macroscopic characteristics arise as a function of

architecture and interaction between scales cascading all the way down to the nanoscopic

environments within. This thrust in part seeks to develop reduced order and component-level

models of nano-scale mechanisms in order to identify principles of physical interaction in these

intricate (and in most cases only stochastically or empirically understood) systems. In addition to

understanding the capabilities of component and mechanism design at the nano-scale, the

program encourages the characterization of energy and information passing from one "'scale" to

the next, as well as sensing and control strategies that tap into hierarchical and complex systems

at different scales and locations.

Topics of interest include, but are certainly not limited to: magnetohydrodynamics; the control of

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plasmas; frontiers of dynamical systems theory exploring turbulence; modeling biochemical

mechanisms in order to identify design principles that exceed their capabilities; locomotion at

micro- and sub-micro-scales. The program highly encourages studies that approach these

problems from the perspective of hierarchical structures as assemblies of known base units rather

than continua whose emergent properties can be modeled by approximating the complexity of

the structure within.

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Army Research Office (ARO) Research Topic

Computational MathematicsTitle:

ARL-BAA-0034Announcement ID:

TPOC: Radhakrishnan Balu, PhD - [email protected] - (301) 394-4302

ARL Office: Army Research Office (ARO)

Discipline: Mathematics and Statistics;Physics

ARL Foundational Research Competencies: Mechanical Sciences;Network, Cyber, and

Computational Sciences;Photonics, Electronics, and Quantum Sciences;Weapons Sciences

Army Modernization Priorities: Assured PNT;Network/C3I

Keywords: Mathematical modeling, Scientific computation, Fractional order methods,

Mathematics of QIS, Atmospheric physics, Embedded simulation

Description:

The research strategy of this program is to focus on the following opportunities for crucial

discoveries: innovative methodologies for solving currently intractable problems that take

advantage of symmetry, conservation, and recurrence, that can adapt to both the evolving

solution and to the evolving run-time resource allocation of modern computer architectures;

novel algorithms that accommodate different mathematical models at different scales, interacting

subsystems, and coupling between models and scales; methods that incorporate nonlocality

through integral operators with advantageous representations. Research in this area will

ultimately lead to the development of new mathematical principles that enable faster and higher

fidelity computational methods, and new methods that will enable modeling of future problems.

Scientific computation is an essential component of scientific inquiry, complementing theory and

experiment, and is also an essential element of engineering in both design and in failure autopsy.

Simulations in support of inquiry, design, or autopsy often require expert knowledge in order to

select methods that are compatible with the assumptions of the scenario at hand, require

considerable skill to properly set up, require considerable time, memory, and storage on large

scale parallel/distributed/heterogeneous systems to compute, and require considerable skill and

effort to distill useful information from the massive data sets which result. Expert knowledge is

also required to quantitatively estimate solution accuracy and to estimate the time and effort

required to achieve a desired accuracy. Data has become ubiquitous and is potentially very

valuable in increasing solution accuracy and/or decreasing the effort required to solve, but

mathematically sound methods for incorporating data into accurate simulations are incomplete.

Simulations are not always timely, with results often not being available until after they are

needed, for example in calculating failure of New Orleans levees during Katrina and in revising

those estimates based on real time surge data.

The emphasis in the Computational Mathematics program is on mathematical research directed

towards developing capabilities in these and related areas. For problems that are not

time-limited, research areas of interest include but are not limited to the following:

Advances in Numerical Analysis. Novel methodologies are sought for solving currently

intractable problems. New ways of taking advantage of symmetry, conservation, and recurrence

are of interest, as are new ways of creating sparsity and new computational structures which can

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adapt to both the evolving solution and to the evolving run-time resource allocation of modern

computer architectures. Rigorous analysis is sought for each in order to enable error bounds,

error distribution, and error control.

Mathematics for Quantum Information Systems (QIS). New mathematical constructs and

understanding are sought in order to provide useful mathematical tools and language to others

working to advance QIS. QIS goes far beyond quantum computing (QC), with focus also on

quantum networking, quantum sensing, topological quantum computing, and topological phases

of matter. Advances are sought in factors of von Neumann algebras, type II and type III, that are

yet to be fully explored even after a century of studies from a QIS point of view. Topological

quantum information processing going beyond anyons and in 3+1 spacetime dimensions are of

interest. Exploration of noncommutative geometry from QIS point of view are important in

pushing the field. Advances are sought in the language for quantum field theory as a basis for

QIS and for the associated mathematical structures that are involved. New bases for QIS-based

chemical and biological systems are just beginning; language and representations for these

more-complex and messier-than-physics-based-systems are sought in order to enable new

mathematical models. The QIS of metamaterials-based systems is very different from other

systems, and new mathematics is sought that is capable of representing the unification of these

disparate QIS themes.

Fractional Order Methods. As an alternative to high order methods and other less-local

operators, fractional operators are another nonlocal operator that have proven to work well in

modeling and have the advantage of not enforcing dubious assumptions of smoothness,

especially at discontinuities and interfaces. However, the nonlocality of fractional operators also

typically introduces a significant increase in computational load. Advances in novel efficient

computational methods for these operators are of interest. Army systems often operate under

rapidly-changing unpredictable and adverse conditions. It is desirable for models to be

computationally simulated and fast enough to drive decision making, exercise control, and to

help avoid disaster. Such simulations need to be created, run, and interpreted in better than real

time. Research directed towards making this goal achievable is of interest, such as: Fast Methods

for Atmospheric Physics. Modeling and prediction of local and mid-range atmospheric physics

are a key part of the domain of operations. New exploratory efforts in fast algorithms for

atmospheric physics have been identified as an area where new computational methods could

make an important impact on problems of current and future Army interest. The emphasis of

these efforts is on mathematical methods which have some promise of wider application rather

than methods limited only to specific application areas.

Reduced Order Models. Full scale simulations are often not realizable in real time. In order to

investigate the behavior of systems under a variety of possible scenarios, many runs are required.

Reduced order models are one way to enable this. Possible methods to create these models

include adaptive simplification methods based on singular value decompositions and reduced

order numerics. To be useful, all such models should be equipped with reliable estimates of

accuracy.

Problem Solving Environments. To enable rapid decision making that is driven by simulation,

it is necessary to set up simulations very quickly and obtain results in an understandable format.

Matlab is one current tool for such a problem solving environment. What are other approaches?

Embedded Simulation. As algorithms become more efficient and computational devices shrink,

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it will become increasingly possible to use real-time simulation to drive control systems. New

methods which address this goal are welcome, especially those which permit user- controlled

and/or adaptively-controlled tradeoffs between speed and accuracy. Decision Making. One valid

criticism of numerical simulation is that it takes so long to set up, run, and post-process the

results that they cannot be used in a timely manner to guide decision making. Mathematical ideas

that help address this problem are of interest.

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Army Research Office (ARO) Research Topic

Condensed Matter PhysicsTitle:

ARL-BAA-0029Announcement ID:

TPOC: Joe X. Qiu, PhD - [email protected] - (919) 549-4297

ARL Office: Army Research Office (ARO)

Discipline: Materials Science;Physics

ARL Foundational Research Competencies: Electromagnetic Spectrum Sciences;Photonics,

Electronics, and Quantum Sciences;Sciences of Extreme Materials

Army Modernization Priorities: Assured PNT;Network/C3I

Keywords: Solid-state physics; Crystal lattices; Correlated oxides

Description:

This program strives to drive research that looks beyond the current understanding of natural and

designed condensed matter, to lay a foundation for revolutionary electronic device concepts for

future generations of warfighters.

Strong Correlations and Novel Quantum Phases of Matter. Understanding, predicting, and

experimentally demonstrating novel phases of matter in strongly correlated solid state materials

will lay a foundation for new technology paradigms for applications ranging from information

processing to sensing to novel functional materials. Interest primarily involves strong

correlations of electrons, but those of other particles or excitations are not excluded. This thrust

is currently emphasizing endeavors to determine if material properties can be significantly

altered by dressing bosonic states within materials with engineered fluctuations of the vacuum.

Topologically Non-Trivial Phases in Condensed Matter. Topologically non-trivial states of

matter in solid state materials beyond the quantum Hall phases have shown a remarkable

opportunity to advance our understanding of physics and provide a foundation for novel device

concepts. This thrust emphasizes the interaction between magnetic order and topological states.

A deeper understanding of these interactions is necessary to determine if meaningful device

concepts can be built upon them. The thrust is also broadly interested in the discovery and

engineering of new non-trivial phases, verification of non-trivial topologies and phase transitions

between trivial and non-trivial topological states.

Unique Instrumentation Development. Advanced studies of SSP phenomena often require unique

experimental techniques with tools that are not readily available. The construction and

demonstration of new methods for probing and controlling unique quantum phenomena in solid

state materials is of particular interest.

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Army Research Office (ARO) Research Topic

Dynamical Influences on Social SystemsTitle:

ARL-BAA-0102Announcement ID:

TPOC: Gregory Ruark, PhD - [email protected] - (240) 890-3591

ARL Office: Army Research Office (ARO)

Discipline: Computer Science;Mathematics and Statistics;Social Science

ARL Foundational Research Competencies: Humans in Complex Systems;Military

Information Sciences

Army Modernization Priorities:

Keywords:

Description:

The overall goal of this program is to enhance fundamental understanding of the interdependent,

reciprocal, and complex relationships across social systems accounting for environmental factors

needed to enhance future warfighters' performance across operational contexts. Performance is

traditionally bounded to a task where the ability to successfully execute actions and achieve

mission objectives is a result of training and leadership. This narrow focus on the task, however,

does not account for the critical factors in everyday interactions that impacts performance: the

social system that shapes the warfighters through shared norms, values, and expectations; lived

experiences that support inter- and intra-dependence; and exogenous variables that directly and

indirectly impact quality of life. A warfighter's social systems exists among other systems -

whether embedded within larger systems, parallel to, in competition to, and/or in opposition of -

that see reciprocal influence forces exchanged between them. These social systems transcend the

task or operational environment to include garrison, schools, deployments, and other institutions

to include those outside the military that co-exist with social systems, and in combination impact

the warfighters' capabilities development. Therefore, it is important to take a holistic approach

that accounts for the human, social, and environmental elements that interact and over time

shape development to understand and predict performance levels and variability within and

across missions.

The Dynamical Influences on Social Systems program supports fundamental research to

understand how to construct, maintain, and, as necessary, reconstruct social systems within and

across environments that promote the desired social behaviors necessary for effective

performance. Successful projects will develop new innovative theoretical, methodological, and

modeling approaches to understand scalable human behaviors within complex systems and

across environments. This program has three focal areas of interest. First, create the scientific

capability to identify and assess the influence of meaningful contextual factors that consciously

and unconsciously impact ongoing affective, cognitive, and behavioral processes within and

across individuals and collectives. Second, to enable the integration of the science of time (i.e.,

the experience and perception of time) to understand cascading effects beyond first and second

order effects on social systems. Third, to understand the impact of advanced technologies that

more closely mimic human characteristics and capabilities on the evolution of various social

systems.

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Army Research Office (ARO) Research Topic

Earth Materials and ProcessesTitle:

ARL-BAA-0007Announcement ID:

TPOC: Jamin M. Rager, PhD - [email protected] - (919) 549-4313

ARL Office: Army Research Office (ARO)

Discipline: Data Sciences and Informatics;Earth and Environmental Sciences;Mechanics

ARL Foundational Research Competencies: Electromagnetic Spectrum Sciences;Humans in

Complex Systems;Mechanical Sciences;Military Information Sciences;Network, Cyber, and

Computational Sciences

Army Modernization Priorities:

Keywords: geoscience, earth science, environmental, civil engineering, urban, built

environment, atmosphere, terrain

Description:

The Earth Materials and Processes program seeks to enable maneuver, communication and

situational awareness in all terrain through understanding and prediction of the physical and

mechanical properties and behaviors of rocks, soil, and man-made earth surfaces and their

interactions with their surrounding environment. The Program is especially interested in

interdisciplinary efforts that could be eligible for cross-discipline support. Topics for

consideration include but are not limited to the following:

Investigations on the transmission of information (e.g., seismic, acoustic, or radio frequency) in

challenging environments: Of special interest are urban, high-latitude, high-altitude, and forested

environments. Access to new field areas and high-resolution data collection and modeling

provide opportunities to differentiate sources and characterize terrain.

Research on fundamental processes within the built environment: How natural and artificial

surfaces (e.g., soil, sand, or concrete) store and conduct energy depending on their spatial

relationships, inherent material properties, and imparted features such as moisture storage and

evapotranspiration. Detailed characterization of these environments will enable prediction of

geophysical and environmental processes in diverse urban settings. Investigations that support

the development, integrity, and resilience of cyber-physical systems as related to environmental

sensing are of special interest.

Science to advance environmental security: These efforts must focus on the fundamental

knowledge that will inform new approaches and tools to predict and mitigate risks posed by

changing environments and extreme weather events and to ensure access to natural resources,

including strategic minerals. Note that (1) the Program focus is on the science required to enable

development of tools and products, not the development of the tools and products themselves,

and (2) proposals must target specific Army-relevant challenges rather than general topics (e.g.,

extreme weather, climate change, natural hazards, as broadly defined). A discussion with the

program manager is encouraged to determine if a topic sufficiently addresses an Army challenge.

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Army Research Office (ARO) Research Topic

ElectrochemistryTitle:

ARL-BAA-0025Announcement ID:

TPOC: Hugh C. De Long, PhD - [email protected] - (919) 549-4271

ARL Office: Army Research Office (ARO)

Discipline: Chemistry;Materials Science

ARL Foundational Research Competencies: Energy Sciences;Sciences of Extreme Materials

Army Modernization Priorities:

Keywords: Electrochmistry, Redox, Chemistry, Transport, Electroactive

Description:

This Program supports fundamental electrochemical studies to understand and control the

physics and chemistry that govern electrochemical redox reactions and transport of species, and

how these are coupled with electrode, catalysis, electrolyte, and interface. Research includes

ionic conduction in electrolytes, electrocatalysis, interfacial electron transfer, transport through

coatings, surface films and polymer electrolytes, activation of carbon-hydrogen and

carbon-carbon bonds, and spectroscopic techniques that selectively probe electrode surfaces and

electrode-electrolyte interfaces. Novel electrochemical synthesis, investigations into the effect of

microenvironment on chemical reactivity, quantitative models of electrochemical systems, and

electrochemistry using excited electrons are also of interest. This Program is divided into two

research thrusts, although other areas of electrochemical research may be considered:

Reduction-oxidation (Redox) Chemistry and Electrocatalysis

The Redox Chemistry and Electrocatalysis thrust supports research to understand how material

and morphology affect electron transfer and electrocatalysis, to tailor electrodes and

electrocatalysts at a molecular level, and to discover new spectroscopic and electrochemical

techniques for probing surfaces and selected species on those surfaces.

Transport of Electroactive Species

The Transport of Electroactive Species thrust supports research to uncover the mechanisms of

transport through heterogeneous, charged environments such as polymers and electrolytes, to

design tailorable electrolytes based on new polymers and ionic liquids, and to explore new

methodologies and computational approaches to study the selective transport of species in

charged environments.

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Army Research Office (ARO) Research Topic

Electronic SensingTitle:

ARL-BAA-0027Announcement ID:

TPOC: Tania M. Paskova, PhD - [email protected] - (919) 549-4334

ARL Office: Army Research Office (ARO)

Discipline: Electronics;Materials Science;Physics

ARL Foundational Research Competencies: Photonics, Electronics, and Quantum Sciences

Army Modernization Priorities: Future Vertical Lift;Long Range Precision Fires;Soldier

Lethality

Keywords:

Description:

This program focuses on basic research investigations leading to new electronic sensing science

that enable 100% situational awareness to include day/night, all weather, non-line-of-sight and

through natural and man-made obstructions for sensing of personnel, weapons, chemical and

biological threats. The Electronic Sensing (ES) program is currently emphasizing research

focused on materials development, including experimental, theoretical and computational studies

that design, create, and understand novel materials functionalities and device operation concepts

through advances in the fields of electronics, photonics, photoacoustics and piezo-phototronics to

enhance or enable new detection capabilities. This program is divided into two thrusts: (i) Novel

materials platforms and (ii) Advanced sensing concepts.

Novel materials platforms

This thrust seeks to push beyond the state of the art in conventional material systems, seeking

novel advanced material platforms with functionality beyond the established limits on

sensitivity. Research of interest is targeting fundamental understanding of nontraditional

materials and nanostructures of high quality enabling new phenomena and unique properties that

could lead to higher detectivity and ultrafast response at or near ambient temperature. This thrust

also supports research aimed at exploring the properties and capabilities of artificially engineered

materials platforms including, but not limited to: metamaterials; 2D vertical or lateral stacking;

azimuthally twisted mono/bilayers or chiral twisted nanowires, which can enable exotic

phenomena such as strong electron correlations, superconductivity or novel optically excited

quasiparticles such as moire excitons or trions, leading to enhanced energy transport toward the

quantum limits in efficiency. Engineered 3D photonic and artificially shaped 2D crystals into

increasingly complex 3D structures, benefitting from expansion into the additional dimension

that could allow enhanced interaction with light or enhanced chemical reactivity are also of

interest. Advances in these areas require deep understanding of mechanisms of interface

formation, new phenomena and properties arising from the unique integration of same or

dissimilar materials, calling for innovative theoretical and experimental methods.

Advanced sensing concepts

This thrust emphasizes research in design and development of tailored device architectures based

on different sensing concepts to achieve performance metrics surpassing current capabilities to

detect, recognize and identify targets and threats. The goal of this thrust is to develop new

engineered approaches to enhance the stimulus-response characteristics and improve the

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signal-to-noise ratio and conversion (transduction) of the signal to another form with higher

efficiency, while reducing all components of the noise (thermal, optical, mechanical, and

electrical) and thus enabling higher sensitivity, reliability and resilience to various environmental

factors. Of particular interest are research efforts exploring innovative hybrid architectures in

pursue of novel or multi-functionality, benefiting from various combinations of optical and

piezoelectric electromechanical resonances, nonlinear plasmonics, selective gating or field

modulation and tailored band structure when targeting different sensing modalities, such as

electro-optic, thermal, acoustic, chemical or biosensing. Other modalities and mixed concepts

that meet the Army needs for highly sensitive, fast, tunable, flexible or multimodal sensors are

also welcome. Advances in these areas require theory-guided experimental research paving the

way towards development of new generation detectors with enhanced multi-band, broad-band or

hyperspectral capabilities.

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Army Research Office (ARO) Research Topic

Environmental ChemistryTitle:

ARL-BAA-0005Announcement ID:

TPOC: Elizabeth (Liz) K. King-Doonan, PhD - [email protected] - (919)

549-4386

ARL Office: Army Research Office (ARO)

Discipline: Biological Sciences;Chemistry;Earth and Environmental Sciences

ARL Foundational Research Competencies: Biological and Biotechnology Sciences;Energy

Sciences;Humans in Complex Systems;Military Information Sciences

Army Modernization Priorities:

Keywords: Environment, Chemistry, Fate, Transport, Climate, Arctic

Description:

The Environmental Chemistry Program seeks to support transformative research to enable

unprecedented detection, prediction, manipulation, and mitigation strategies in complex

environmental matrices. This is an interdisciplinary program that incorporates recent discoveries

in chemical, biological, and physical principles to enhance national security.

Current focus areas for this portfolio include, but are not limited to, the following:

Biogeochemical transport and transformation aims to elucidate and characterize novel

biogeochemical mechanisms that drive (or prevent) the release and/or transformation of

emerging compounds of concern within or across environmental reservoirs. Environmental

reservoirs of interest include the lithosphere (e.g., soils and sediments), biosphere (e.g., plants

and microbiome), hydrosphere, and atmosphere.

Environmental chemistry of the built environment supports research to understand the

biogeochemical interactions that are unique to built and urban environments. The reactions in

these environments are a function of the structure and partitioning of the compounds present, the

chemical and physical properties of the built/artificial materials, and the microenvironments that

form at the natural-built interface. Topics of interest include (but are not limited to)

environmental/biofilm formation on Army-relevant built materials, biological and chemical

transport in subterranean built environments, and contaminant transport and transformation

through diverse urban interfaces.

Environmental forensics strives to develop cutting-edge approaches to enable novel techniques

for detection, tracking, source partitioning, and prediction at military-relevant scales. Research

that leverages recent discoveries in other scientific fields such as biology, physics, network and

data science, and computational modeling are encouraged. Topics that focus on

instrument/sensor development and materials design are not supported.

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Environmental chemistry to inform environmental security characterizes how dynamic and

extreme weather events (e.g., fires, flooding, drought), or extreme environmental conditions

(e.g., temperature, relative humidity) alter the speciation, partitioning, transformation, and

recovery of biological and chemical compounds of interest, including critical resources.

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Army Research Office (ARO) Research Topic

Fluid DynamicsTitle:

ARL-BAA-0030Announcement ID:

TPOC: Jack R. Edwards, PhD - [email protected] - 919-549-4235

ARL Office: Army Research Office (ARO)

Discipline: Mechanics

ARL Foundational Research Competencies: Weapons Sciences

Army Modernization Priorities: Future Vertical Lift;Long Range Precision Fires

Keywords: fluid, turbulence, dynamic stall,

Description:

Fluid dynamics plays a critical role in many Army operational capabilities. Accurate and

efficient prediction of the flow physics required for the design of future advanced capabilities

and improvements to the performance of existing systems is challenged by the nonlinear and

high-dimensional character of the governing equations. In addition, Army relevant platforms are

often dominated by flows with high degrees of unsteadiness, turbulence, and compressibility and

are characterized by multiple and widely separated spatio-temporal scales and geometrical

complexity of solid or flexible boundaries. The program seeks to support basic research

investigations of fundamental and novel flow physics underpinning future concepts and

capabilities for Army platforms.

The program seeks basic research proposals in the following three thrust areas:

Dynamics of Unsteady and Separated Flows

Efforts in this research area require novel and aggressive strategies for examination of the

interplay between disparate spatio-temporal scales, the inclusion of physically significant sources

of three dimensionality, and the characterization of the role of flow instabilities and nonlinear

interactions across a range of Mach and Reynolds numbers appropriate to Army aerial vehicle

and weapons systems. In all cases, the flow is characterized by a high degree of unsteadiness.

Criteria for identifying the signatures of unsteady separation and/or incipient separation are of

particular interest, as are diagnostics capable of real time measurements of such

signatures. Historical management of complexity has often resulted in scientific approaches that

lead to the elimination of potentially critical flow physics. Research efforts capable of gaining

deep understanding of highly complicated flows are likely to allow these critical physics to be

exploited.

Nonlinear Flow Interactions and Turbulence

Many Army relevant flows are governed by strong nonlinearities and are fundamentally

turbulent in nature. Historically, many analysis tools developed for linear dynamics have been

applied to gain understanding of flow behaviors. The practical usefulness of such techniques has

saturated; the ability to gain global understanding of the evolution of flows requires the

development and use of approaches that can deal directly with inherent nonlinearities. Operator

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theoretic methods are making great strides in tackling the perennial difficulties associated with

the Navier-Stokes equations. Our understanding of turbulent flows is also benefitting from new

approaches based in dynamical systems theory to build frameworks beyond the notions based on

Reynolds averaging and stochastic dynamics. By leveraging the existence of underlying

deterministic structures, significant advances in the ability to design systems capable of not just

dealing with turbulence but exploiting its dynamics may become possible. Modeling turbulent

flows near walls at high Reynolds is a continuing challenge for practical applications of

scale-resolving simulation methods. Creative numerical and theoretical constructs may benefit

from novel non-intrusive diagnostics that can accurately measure turbulent flow properties near

walls.

Dispersed-phase Interactions with Aerodynamic Surfaces

Understanding the dynamics of the interaction of dispersed phases (sand, dust, rain, frozen

precipitation) with aerodynamic surfaces is necessary to mitigate potential performance

degradations and to expand the range of applicability of Army aerospace systems. Accurate

prediction and description of dispersed-phase interactions within aerodynamic boundary layers,

with solid surfaces, and with other dispersed-phase components is needed for a better

understanding of the underlying flow physics. Advances in modeling and simulation strategies

capable of predicting near-surface dispersed phase and dense-phase effects are needed, as are

quantitative diagnostics capable of interrogating local flow phenomena that impact overall

aerodynamic performance.

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Army Research Office (ARO) Research Topic

GeneticsTitle:

ARL-BAA-0035Announcement ID:

TPOC: Micheline K. Strand, PhD - [email protected] - (919) 549-4343

ARL Office: Army Research Office (ARO)

Discipline: Biological Sciences

ARL Foundational Research Competencies: Biological and Biotechnology Sciences

Army Modernization Priorities: Soldier Lethality

Keywords: genetics, genetic variation, DNA barcoding, mitochondria, oxidative stress

Description:

The Genetics program supports fundamental basic research in genetics, molecular biology,

genomics, epigenetics, and systems biology in areas that are anticipated to enable improved

cognitive and physical performance capabilities, increase survivability, and enable new Army

capabilities in areas such as biomaterials, sensing and intelligence. This program emphasizes

innovative high-risk fundamental research in areas such as identification and characterization of

genetic variation, gene function, gene regulation, genetic interactions, gene pathways, gene

expression patterns, epigenetics, mitochondrial regulation and biogenesis, and nuclear and

mitochondrial DNA stability and instability. More specifically the Genetics program is currently

focused on the following questions: Can we advance our understanding of the factors that affect

mitochondrial integrity and oxidative stress? Can we further our understanding, characterization

and exploitation of genetic variation within and between species? Can we fully identify,

characterize and understand the relationships with and the effects of prokaryotes and fungi on

larger eukaryotes, including in eukaryotic organs traditionally considered to be sterile? How can

we exploit genetic pathways and genetic variation to protect soldiers and develop new Army

capabilities?

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Army Research Office (ARO) Research Topic

Information AssuranceTitle:

ARL-BAA-0010Announcement ID:

TPOC: Paul L. Yu, PhD - [email protected] - (240) 890-3589

ARL Office: Army Research Office (ARO)

Discipline: Computer Science;Data Sciences and Informatics;Network Science

ARL Foundational Research Competencies: Network, Cyber, and Computational Sciences

Army Modernization Priorities: Network/C3I

Keywords: cyber defense, resiliency and robustness, trusted computing and communication,

wireless security

Description:

Information Assurance

The Information Assurance program establishes the scientific mathematical and information

processing foundations for achieving information and decision dominance under threat

conditions. Information provided to warfighters must be authentic, accurate, secure, reliable, and

timely. The research program seeks the development of foundational science to assure

information flows in autonomous cyber systems, protect their interactions with capable

adversaries, and understand how to apply and account for deception. Central to program efforts

is the resilience of complex systems in highly dynamic and congested environments that are

contested by capable adversaries.

Models and Metrics for Next Generation Systems

The program seeks foundational science to measure a complex system and provide

trustworthiness and robustness guarantees. Assurance principles and metrics are needed to help

define, develop, and evaluate future resilient systems and networks that can, with measurable

confidence, survive and recover from sophisticated attacks and intrusions. An enduring challenge

is the proactive discovery of exploits and vulnerabilities in cyber-physical systems, neural

networks, and other complex systems. Ideally, the subsequent mitigation process improves

resilience against future attacks. Deep understanding and accurate modeling of attacker-defender

interactions will also be important to improve future system development. In addition, some

areas of interest for improving warfighter performance include the development of

human-centric security and usability metrics, computational models for usable security in

stressful situations, and adaptive security protocols according to perceived threats.

Trusted Learning for Cyber Autonomy

Future Army autonomous systems, especially cyber-physical systems working alongside

soldiers, are subject to adversarial attacks during operations such as fault injection. While current

testing and verification techniques help assure system integrity prior to deployment, few of them

can help mitigate runtime risk or achieve automatic recovery after a compromise. Robustness

certification or domain adaptation at both the data processing layer and the information/decision

layer may lead to better mission sustainment and resiliency against adversarial manipulation and

exploits. Also lacking is the ability to adapt to changing operational environments, mission

requirements, and adversarial conditions. New research is sought to establish fundamental

principles for cyber autonomous system adaptation, including trusted cyber-domain learning,

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decision making, introspection, self-healing, and adaptation. Assurance of the autonomous

response for safety and correctness is critical for defense systems to maintain mission assurance.

Cyber Deception

Cyber deception is a proactive technique to degrade the adversary's effectiveness by

manipulating its cognitive state and decision process. Scientific understanding is required to

establish effective models for understanding and tracking the adversary's tactics, techniques, and

procedures (TTP) and quantify the effectiveness of deceptive maneuvers in steering the

adversary's decision processes. Deceptive cyber artifacts have been used to engage adversaries

but the dynamics between attackers and defenders, especially mental interactions, are not well

understood. Advanced methods are sought to understand adversaries through neutralized

engagements to inform effective deception schemes. Capable adversaries will also leverage

deceptive techniques in engaging with Army networks; it is critical to model deceptive

adversaries that attempt to mask their TTP, evade detection, and launch sophisticated attacks.

Trustworthy Tactical Communication

The program seeks direct guidance in the design of theory, protocols, and techniques that assure

delivery of trustworthy information over tactical wireless systems. Novel ideas in fundamental

research areas, such as information-theoretic security and game theory, may yield new

paradigms for physical layer security (ranging from confidentiality to authentication to

trustworthiness), fundamental bounds in trust management and data integrity in distributed

systems, and assured information delivery and dissemination in tactical environments. The

corresponding constructions stemming from such investigations represent a significant avenue

for improving trustworthiness of future tactical wireless communications.

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Army Research Office (ARO) Research Topic

Information Processing and FusionTitle:

ARL-BAA-0008Announcement ID:

TPOC: John S. Hyatt, PhD - [email protected] - (240) 309-8380

ARL Office: Army Research Office (ARO)

Discipline: Computer Science;Data Sciences and Informatics;Mathematics and Statistics

ARL Foundational Research Competencies: Military Information Sciences

Army Modernization Priorities:

Keywords:

Description:

With ubiquitous data acquisition capabilities, effective data and information processing is of

critical importance to defense missions. The Information Processing and Fusion program is

concerned with the creation of innovative theories and algorithms for extracting actionable

intelligence from diverse, distributed multimodal data to support Army operations.

Foundations of Image and Multimodal Data Analysis

Innovative research is sought concerning: (1) novel representations of multimodal data to enable

the understanding of multimodal sensor data and contextual information, including nonstandard

data types beyond image and video; (2) detection, localization, and recognition of objects and

locations from image data with particular emphasis on provable performance guarantees; (3)

detection of events, actions, and activities to extract activity-based intelligence, especially when

no extensive training data is available; and (4) integrated approaches that enable semantic

descriptions of objects and events including relations. Learning and adaptation should enable the

representation at both low and high levels, where inputs from actual users of the systems are

used to improve the performance of the algorithms and the fidelity of models at all levels of the

modeling hierarchy. Of high interest are methods to exploit the structure of the data, capture its

intrinsic dimensionality, and extract information content of data, and which go beyond

correlative modeling to incorporate causality, symbolic reasoning, and physics. The development

of an "'information/complexity theory" and a "'learning theory" specific for remote sensing,

imaging data, and decision tasks is highly desirable.

Data and Information Fusion

Multimodal data acquisition systems are increasingly prevalent with disparate sensors and other

information sources, ranging in design from a finite number of locally grouped sensors to a very

large, geographically dispersed sensor network. This thrust seeks advanced mathematical

theories and approaches for integrating multimodal data and contextual information to provide

actionable intelligence. Of particular interest are systematic and unifying approaches for data and

information fusion from diverse sources with heterogeneous fidelities and timescales, varying

degrees of overlap, and differing levels of uncertainty. Scalable methods are needed for

efficiently handling vast amounts of data, as are methods for preserving data provenance and

identifying the key raw data used to generate fused representations or make predictions. Fusion

in networked environments addressing issues such as adaptive, distributed, and cooperative

fusion is emphasized. Theories and principles for performance analysis and guarantees at all

fusion levels to support robust, uncertainty-aware data and information fusion are important to

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ensure successful military operations.

Active and Collaborative Sensing

Modern sensing systems typically include multiple networked sensors with communication

capabilities where the whole network can be thought of as a meta-sensor that can be controlled,

in addition to each individual node having some controllable degrees of freedom such as

mobility for unmanned aerial/ground systems, pan-tilt-zoom for infrastructure sensors, or

waveform for agile radar. Depending on the task or query, it is desirable for the system to control

the data acquisition process to acquire the "'most informative data" for the specific task or query,

to minimize uncertainty, or to identify the type and deployment scheme of additional sensors

required. Consequently, of particular interest are methods that address the integration of

mobility, sensor-selection, modality selection, and active observation for real-time assessment

and improvements of sensing performance. Another research area of interest is

performance-driven active data collection, where a query is given to the system together with a

desired performance bound. Where the confidence in answering the query is insufficient, the

system should actively interrogate or control sensors to achieve the desired confidence. Such an

active learning and information-driven sensor control should include the user in the feedback

loop.

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Army Research Office (ARO) Research Topic

Knowledge SystemsTitle:

ARL-BAA-0033Announcement ID:

TPOC: Robert St. Amant - [email protected] - (240) 927-2060

ARL Office: Army Research Office (ARO)

Discipline: Computer Science;Data Sciences and Informatics;Economics;Mathematics and

Statistics;Network Science;Social Science

ARL Foundational Research Competencies: Military Information Sciences

Army Modernization Priorities: Network/C3I;Next Generation Combat Vehicle;Synthetic

Training Environment

Keywords: Game Theory; Natural Language Processing; Decision Making; AI as software;

Problem Solving

Description:

The overall objective of the Knowledge Systems program is to augment human decision makers

(both commanders and Soldiers) with enhanced-embedded battlefield intelligence that will

provide them with the necessary situational awareness, reconnaissance, and decision making

tools to decisively defeat any future adversarial threats. While software agents will likely be the

decision aide, it turns out robots also need planning and decision tools and need to be able to

understand their human handlers/ colleagues. Given these objectives, it becomes necessary to

understand (a) fundamentals of what intelligence means in the context of autonomous systems

and how to build intelligent systems especially as it relates to interaction amongst a network of

humans and machines, and (b) foundational algorithmic issues in representation and reasoning

about networks inherent in societies and nature.

Information Networks

In order to model network effects it is necessary to algorithmically represent large networks and

reason about them. Unfortunately, information about networks is seldom complete - data

available might be missing crucial pieces of information, might have contradictory pieces of

information, or could be approximate (with associated notions of uncertainty). Representing and

reasoning about these networks requires advances in knowledge representation, graph and data

mining, natural language processing, algorithmic graph theory, machine learning, and

uncertainty quantification and reasoning. Examples include the emerging area of Graphons

which provide new tools for generating and reasoning about graphs that occur in practice

(satisfying power law distributions), but also provide new tools for Machine Learning. In

particular, a major goal of this thrust are tools and techniques that allow data driven approaches

to capturing latent relationships with powers to both explain and predict. Advances in this thrust

would not only lead to improved autonomous systems and algorithms, but also

enhanced-embedded battlefield intelligence with tools for creating necessary situational

awareness, reconnaissance, and decision making. Finally, it should be noted that algorithmic

notions of approximations, tight performance bounds, probabilistic guarantees, etc., would be

major concerns of the solution space.

Adversarial Reasoning

Development of appropriate mathematical tools to model and reason about societies and cultures,

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that brings together tools from Game Theory, Social Sciences and Knowledge Representation.

Research of interest includes, but is not limited to, Game Theory for security applications while

accounting for bounded rationality, development of Game Theory based on data regarding

cultural and adversarial groups, and Behavioral Game Theory that can explain intelligence in

groups and societies. In particular, the role of human biases in decision making and game theory

is of importance to this thrust of the program.

Natural Language Processing and Affective Computing

Inference algorithms work incredibly well when data is in a structured format. However, most

reports, email, and conversations are written out as text with information embedded in them.

This thrust seeks advances in purposeful Natural Language Processing at scale that can account

for context and mode-switches by bringing together statistical and logical methods. Indeed, when

combined with other signals, such as video signals, the inter-play of non-verbal and verbal/

textual communication provides rich contextual information, which, in turn, leads to accurate

information being gleaned from an interaction.

Engineering AI Systems

AI systems are insular, brittle, dependent on massive amounts of data, and with no avenues for

composition. While notions of type systems, effect systems, assume-guarantee assertions, and

procedural and process abstractions are all now available to describe and compose software

components, similar notions of modularity are critically needed for building AI systems from

small learning-based components. There are examples such as model-cards and data-sheets that

are now available, which along with notions of Probabilistic Programming could provide the

necessary basis. However, there are a number of problems, especially in the context of Deep

Neural Networks, that still need to be addressed. The necessary science required to address AI

safety - rigorous specifications for composition, run-time monitoring, self-healing, reasoning,

etc., are all of interest to this program.

Afore mentioned problems of interest deal with tools for producing robust AI

systems. However, the task of designing and building AI systems from scratch - from vague

definitions of problem to be solved - is still open. An enormous amount of insight and effort

may go into the process of turning an ambiguous description into a formal problem specification

amenable to an AI solution. What data sources are relevant? What structure can be identified in

the problem space? What makes one family of solution techniques better than another? Which

measures should be adopted for evaluating the quality of a solution? Research on problem

formulation and formalization can be found in the literature, with results in some specialized

areas such as concept learning for DNNs, general game playing, and historical work on

formalizing data analysis procedures. General solutions are lacking, however, which has a

bearing on current challenges in AI (e.g. under-specification for ML systems) and may

contribute to the relatively slow adoption of AI in some high-stakes domains (e.g. clinical

practice in medicine). The need is more than simply for automated tools to assist AI

developers. Rather, the scientific question to be answered concerns the extent to which the

informal process of problem formulation can be formalized.

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Army Research Office (ARO) Research Topic

Materials DesignTitle:

ARL-BAA-0012Announcement ID:

TPOC: Evan L. Runnerstrom, PhD - [email protected] - (919) 549-4259

ARL Office: Army Research Office (ARO)

Discipline: Chemistry;Materials Science;Physics

ARL Foundational Research Competencies: Electromagnetic Spectrum Sciences;Photonics,

Electronics, and Quantum Sciences;Sciences of Extreme Materials

Army Modernization Priorities: Soldier Lethality

Keywords: self-assembly, soft materials, colloids, functional materials, metamaterials,

Description:

The overarching goal of the Materials Design program is to establish new smart materials

concepts by pursuing fundamental science that exploits multiple physical and chemical forces at

play during directed self-assembly to create stimuli-responsive, multifunctional materials with

designer geometries, hierarchical complexity, and the ability to dynamically switch among

configurations, thereby enabling the future Warfighter to adapt to any environment or situation.

Bottom-up materials science, functional materials, and soft matter are the unifying themes of the

Materials Design program. The program supports experimental, theoretical, and computational

advances to better design, create, understand, and manipulate novel functional materials from the

bottom up. The foundations established here support the realization of 3D metamaterials,

reconfigurable optics and electronics, bio-mimetic materials, and multi-functional materials that

dynamically respond to their environment.

supports basic research into the multiple physical and chemicalThe Science of Self-Assembly

forces at play during directed, bottom-up 3-D assembly into super-structures incorporating

multiple components. The goal is to design novel self-assembled materials that would be

impossible to create using top-down techniques. Self-assembling materials systems of interest

include: colloids; nanocrystals; liquid crystals; functional biomaterials and bio-hybrid materials;

and/or hybrids (e.g., polymeric composites) of these materials. Specific research interests

include: non-equilibrium and dissipative self-assembly; 3-D photonic crystals and structural

color; interactions between self-assembled materials and water; and non-traditional assembly

directing forces (e.g., turbulence).

supports the design and synthesis of soft matter capable of reversibleReconfigurable Materials

transformations. The goal is to elucidate the design rules for creating novel functional materials

with dynamic property contrast and/or emergent behavior and develop new methods to

"'program" materials with the ability to respond in specific ways to external stimuli.

Reconfigurable materials systems of interest include: bio-mimetic materials; liquid crystal

elastomers; colloidal metamaterials; 3D/4D metamaterials; and active matter. Specific research

interests include: 3D/4D printing of functional materials with molecular-scale precision;

materials that form reconfigurable networks; "'natural" (i.e., non-robotic) active matter capable

of autonomous collective behavior and/or computation, and, in particular, materials capable of

changing their shape, color, or texture.

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seeks to leverage recent advances in machine learning,Computer-aided Materials Design

artificial intelligence, computational materials science, and other numerical approaches to solve

difficult materials design problems, particularly those in soft matter, self-assembly, and

reconfigurable materials. Points of interest include inverse design of self-assembled materials;

data-driven design of heterogeneous hierarchical materials; and novel models or algorithms for

solving materials-specific problems. Specific research interests include: "'self-driving" materials

simulations; unified simulation approaches that bridge all time- and length-scales of interest; and

designing soft materials to perform AI/ML computations (e.g., physical artificial neural

networks).

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Army Research Office (ARO) Research Topic

Mechanical Behavior of MaterialsTitle:

ARL-BAA-0001Announcement ID:

TPOC: Daniel P. Cole, PhD - [email protected] - (919) 549-4371

ARL Office: Army Research Office (ARO)

Discipline: Chemistry;Data Sciences and Informatics;Materials Science;Mathematics and

Statistics;Mechanics;Network Science;Physics

ARL Foundational Research Competencies: Sciences of Extreme Materials;Terminal

Effects;Weapons Sciences

Army Modernization Priorities:

Keywords:

Description:

This program focuses on basic research investigations that enable unprecedented mechanical

properties in advanced structural materials in order to ensure high performance under a variety of

extreme and highly variable operational conditions. Experimental, theoretical, and numerical

efforts are encouraged, particularly those that promote understanding of the underlying physical

mechanisms leading to extraordinary behaviors. Studies may focus on a variety of materials,

including: metals, ceramics, polymers, composites, and hybrid structures. Research efforts that

leverage recent discoveries in other scientific fields, such as Physics, Chemistry, Mathematics,

Network Science and Data Science, are also highly encouraged. These investigations are

expected to enable transformative capabilities for the Soldier in the areas of protection,

maneuver, and sustainability. Current focus areas for this portfolio include, but are not limited to,

the following:

Extreme Thermomechanical Behaviors. This thrust emphasizes foundational concepts that

enable structural materials with extraordinary combinations of ultrahigh temperature stability

and exceptional mechanical properties under non-equilibrium conditions, e.g. transient thermal

loads, high g-loading, and/or variable oxidizing environments. Areas of interest include:

Understanding, control, or confinement of deformation mechanisms; exploiting

interface/interphase interactions in heterogeneous materials; and concepts enabling materials to

undergo refinement under relevant conditions to enhance thermomechanical performance.

Disruptive Mechanical Responsiveness. This thrust focuses on structural materials with

unprecedented mechanical responsiveness when subject to complex loading environments, e.g.

severe and/or high strain rate events. Areas of interest include materials that actively respond to

dynamic loading environments and other external stimuli through rapid adaptation of shape,

topology, mechanical properties, and/or through the ability to intrinsically process information.

In addition, this thrust seeks concepts for manipulation of mechanical forces within materials at

specific spatial locations, particularly for the consideration of inelastic behaviors.

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Army Research Office (ARO) Research Topic

MicrobiologyTitle:

ARL-BAA-0006Announcement ID:

TPOC: Robert J. Kokoska, PhD - [email protected] - (919) 549-4342

ARL Office: Army Research Office (ARO)

Discipline: Biological Sciences;Network Science

ARL Foundational Research Competencies: Biological and Biotechnology Sciences;Humans

in Complex Systems;Network, Cyber, and Computational Sciences

Army Modernization Priorities:

Keywords:

Description:

This program supports basic research in fundamental microbiology that can help advance needs

in Soldier protection and performance. There are two primary research thrusts within this

program: (i) Microbial Survival Mechanisms in Challenging and Extreme Environments and (ii)

Analysis and Engineering of Microbial Communities.

The Microbial Survival Mechanisms in Challenging and Extreme Environments thrust focuses

on the study of the cellular and genetic mechanisms and responses that underlie bacterial,

archaeal and fungal survival in the face of environmental stress, as well as the ability of these

microbes to thrive under those conditions. These stressors include extremes in temperature, pH,

or salinity; the presence of toxins including metals and toxic organic molecules; oxidative stress;

and cellular starvation and the depletion of specific nutrients. Included here is the study of

microbial metabolism under conditions of slow growth and the transitions into and out of slow

growth phases. Research approaches can include fundamental studies of microbial physiology

and metabolism, cell biology, and molecular genetics that examine key cellular networks linked

to survival and environmental adaptation, microbial cell membrane structure, and the dissection

of relevant critical signal transduction pathways and other sense-and-respond mechanisms.

The Analysis and Engineering of Microbial Communities thrust supports basic research that

addresses the fundamental principles that drive the formation, proliferation, sustenance and

robustness of microbial communities through reductionist, systems-level, ecological and

evolutionary approaches. Bottom-up analysis of nutrient consumption, information exchange,

signaling interactions, spatial/temporal effects, structure-function relationships, and biosynthetic

output for single and multi-species communities within the context of planktonic and both native

and engineered biofilm architectures is considered. The use of these approaches for the analysis

of model microbial systems that address the biology of mammalian and environmental

microbiomes are welcome. Of joint interest with the ARO Biomathematics Program, research

efforts that advance the ability to work with biological data sets toward an understanding of

microbiological systems marked by ever-increasing complexity are encouraged.

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Army Research Office (ARO) Research Topic

Modeling of Complex SystemsTitle:

ARL-BAA-0020Announcement ID:

TPOC: Robert S. Martin, PhD - [email protected] - (301) 580-7573

ARL Office: Army Research Office (ARO)

Discipline: Mathematics and Statistics;Physics

ARL Foundational Research Competencies: Military Information Sciences;Network, Cyber,

and Computational Sciences;Weapons Sciences

Army Modernization Priorities:

Keywords: data assimilation, inverse problems, model closure, geometric data analysis,

information theory, sparsity, data compression

Description:

The Modeling of Complex Systems Program is a program of fundamental mathematics

oriented research directed at addressing the critical challenges resulting from the approximate

nature of mathematical models that are particularly exacerbated by complex macroscopic

phenomena. While models have traditionally relied on tuned, empirically inspired closures, this

program seeks to rigorously explore the bounds of model predictive power through the

development of coupled nonlinear uncertainty propagation methodologies and novel data

assimilation techniques for the self-consistent integration of observed data within constrained

modeling frameworks. By leveraging available prior knowledge such as conservation laws,

invariances, symmetries, graph interaction structure, and information geometry, the program

seeks to improve predictive horizons beyond naive interpolative data fitting across a variety of

disciplines. The program particularly seeks modeling frameworks that can be adapted to span a

variety of disciplines where complete first principle descriptions are unavailable,

computationally inaccessible, or that require inference of missing and incomplete information in

problem descriptions to enable rapid predictions for applications ranging from anomaly detection

to design and planning. Although they break down into more specific research directions, the

three thrust areas of interest to the Modeling of Complex Systems Program are 1) development

and analysis of new, general, outer-loop modeling and data assimilation frameworks 2)

validation metrics for models of complex phenomena that avoid overfitting phenomena and 3)

data topology, hierarchical compression, and nonlinear sparsity in quantifying optimal minimal

model state representations across the range of observed emergent system complexities.

Note that the research in modeling of complex phenomena supported by the Modeling of

Complex Systems Program is primarily mathematical analysis and not numerical analysis or

computational mathematics. Rather than demonstrating asymptotic convergence of numerical

methods to an assumed mathematical model form, the goal instead is in the development of

frameworks capable of asymptotic convergence of predicted uncertainty bounds to observed

distributions under the assumptions of finite complexity computation and limited data

availability.

Models of particular complex systems that address and are to be utilized for more specific

purposes and objectives will be assessed within the context of one of the program's other

modeling thrust areas. Research carried out under this section should address the general theory

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and analysis of mathematical modeling from a broader perspective.

Furthermore, any modeling research effort that could be of benefit to military applications but

that might not fall directly under one or more of the program thrust areas will still be considered,

particularly if the innovation in the modeling and analysis are significant and noteworthy.

The three major areas and subsequent sub-areas of research for the Modeling of Complex

Systems Program are described further below.

Outer-Loop Modeling Frameworks and Analysis

Mathematical modeling is fundamental to nearly every other direction of research in the

physical, social, and computational sciences. A common element of modeling - even if the

phenomenon in question is highly complex - is truncation and simplification that sacrifices

realistic application and utility for computational tractability. This is particularly true for

enabling outer-loop models such as those used in design optimization, uncertainty quantification,

model predictive control, and inverse problems. Where necessary, data-driven simplifications

motivated by observed regularity with corresponding uncertainty bounds are preferred to ad hoc

assumptions. Modeling frameworks are desired that are able to eschew the usual computational

simplification assumptions and realistically capture, adequately govern and/or control, and

effectively operate within the particular complexities of real-world environments and

phenomena, while maintaining sufficient computational tractability to provide testable

predictions at relevant timescales. Of specific interest are hybrid model frameworks that capture

both causal and predictive features, data assimilation in compressed spaces, probabilistic

modeling frameworks for the nonlinear evolution of uncertainty, and applications of categorical

models.

Validation Metrics

A critical component of any mathematical modeling framework, reliable validation metrics are

required to attain confidence in model predictions. Traditional metrics, such as a few low

moments of quantities of interest, often leave system characteristics unconstrained for

phenomena in which observers in general and the Army in particular may later become

interested. This is particularly true of rare event and heavy-tailed phenomena. With the

application of increased model complexity to many complex phenomena, as in the case of highly

parameterized purely data-driven models, new metrics need to be developed to balance model

expressivity with the risk of overfitting. Approaches for understanding the bounds of model

validity near mode transition boundaries where model assumptions fail are also particularly

critical. As is the case for the modeling effort, these metrics should preferably be in a complete

mathematical analytical framework, which is to say, in part, that they should derive from the

problem in question and its inherent complexity as opposed to a situation in which one forces the

model to fit an a priori chosen metric. Further, with the proliferation of post-hoc data-mining,

development of rigorous metrics that are resilient to overfitting are particularly critical.

Data Topology, Hierarchical Compression, and Nonlinear Sparsity

Representation of complex, irregular geometric objects and complicated, often high-dimensional,

abstract phenomena, functions, and processes is fundamental for Army, DoD, and civilian needs.

These compressed representations are often a critical initial step in modeling of any complex

system. Such needs arise in the multiscale models of physical phenomena, coarse-graining,

sociological and biological objects, information flow, and many other contexts. While any finite

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representation of real data is necessarily lossy, finding efficient spaces that retain the information

necessary for a given prediction task is a critical component of building computationally

tractable models. Any research that incorporates an innovative information geometric and/or

topological approach to address a problem with military, defense, and intelligence applications is

welcome and will be considered, but there are three specific threads that are of particular interest

to this thrust of the program: 1) geometric data analysis, and 2) multiscale geometric modeling,

including dynamics and physical modeling on domains with fine, complex, geometric and/or

topological structure and 3) the fundamental mathematical structure of closure models.

Geometric data analysis includes - among other subfields - topological data analysis, subspace

analysis, manifold learning, empirical dynamic modeling, and dimension reduction techniques.

Current research directions of importance to Army applications include video, audio, and image

processing (i.e. mathematical signal analysis), fast and accurate object recognition (i.e.

reconstructing and matching geometric data through queries over a database), embedology,

causal inference, geometrically motivated methods and structures for working effectively with

large - and often real-time extracted - data sets that may be corrupted in some way (e.g. missing

or distorted data), and the application of persistent homology in the detection and classification

of signals by shape. New approximation theory that does not require the classical assumptions -

primarily smoothness - and that provides structure for the many new non-smooth approximation

techniques currently under investigation is required. Concurrently, research on the metrics by

which we measure and evaluate the approximation is needed.

Additionally, approximation theory for information flow and other abstract phenomena in large

wireless communication, sensor and social networks is also of interest. The approximation

theory developed under support of this program is expected to provide building blocks for

computational geometry, pattern recognition, automatic target recognition, visualization systems,

information processing and network information flow.

Multiscale geometric modeling, analysis, and dynamics are of particular interest, both in the

context of models of physical phenomena over real-world terrain and in the aforementioned

complex, high-dimensional data structures. Models that make use of self-similar structures and

recursively defined spaces (e.g. fractals, solenoids, etc.) would be of great interest in adapting or

enhancing current techniques in areas such as data mining, fluid and heat flow, and search,

evasion, deployment, and maneuver over complex terrain that exhibits self-similar properties

(e.g. urban or mountainous terrain). Current techniques for dealing with complex dynamical

processes and large, noisy, and possibly corrupted data sets could be greatly improved in both

the time and efficiency realms by employing techniques from scale symmetry, which often

allows one to reduce a large and unwieldy number of variables to a more manageable problem if

the variables are appropriately scaled.

Finally, closure models, and particularly those that exploit self-similarity or other structural

invariances, are of interest. However, reliance on model closures remains contingent on the

development of rigorous mathematical foundations for highly parameterized models such as

those arising from neural network approximations in establishing convergence properties,

uniqueness, and equivalence of the resulting inferred maps.

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Army Research Office (ARO) Research Topic

Modern OpticsTitle:

ARL-BAA-0009Announcement ID:

TPOC: James A. Joseph, PhD - [email protected] - (919) 549-4213

ARL Office: Army Research Office (ARO)

Discipline: Physics

ARL Foundational Research Competencies: Electromagnetic Spectrum Sciences;Network,

Cyber, and Computational Sciences;Photonics, Electronics, and Quantum Sciences

Army Modernization Priorities:

Keywords:

Description:

The objective of this program is to promote a deeper understanding of the properties of light and

the discovery of new optical effects that can improve Army capabilities. Most sensing and

communications systems depend on light in some way. This program seeks transformational

basic science discoveries in optical physics that are needed to enable dynamic control of light for

remote sensing, information routing, and energy transmission. In order to accomplish this goal,

the Modern Optics Program targets new or emerging phenomena related to quantum optics,

light-matter interactions, structured light and ultra-short pulse lasers.

Quantum Photonics. This thrust seeks to push beyond the state of the art in photonics and

integrated optical platforms, seeking novel functionality beyond classical limits on sensitivity,

accuracy, and stability. Research efforts may include studies addressing complexity and loss in

integrated optical systems, scalable realizations of multi-photon quantum states or quantum light

sources, and novel laser platforms to probe or manipulate quantum information in physical

qubits. Basic science understanding is needed to push integrated photonics into the quantum

regime which will be essential for next generation quantum technology.

Meta-Optics. This thrust looks for novel functionality enabled by optical metamaterials. In this

area, the conventional norms of classical optics will be broken. Examples include resolution

beyond the diffraction limit, super-lensing, as well as subwavelength control of optical fields.

Proposals related to non-Hermitian optics and the physics of exceptional points, where these

concepts are utilized to fabricate photonic structures with novel properties and sensors with

precision beyond the state of the art are sought. In general, any phenomena arising from optical

metamaterials that would benefit the Soldier and improve Army capabilities will be considered.

Extreme Light. This thrust focuses on extreme light, meaning the examination of optical fields in

extreme limits, such as shortest pulse and/or high intensity. General areas of study under this

thrust include, THz formation, broadband localized radiation, coherent control of atomic and

molecular energy states, plasma effects in materials, and relativistic plasma physics. Theoretical

and experimental research efforts are needed to push beyond the state of the art in ultrafast

science and to understand how extreme light interacts with matter.

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Army Research Office (ARO) Research Topic

Multi-Agent Network ControlTitle:

ARL-BAA-0031Announcement ID:

TPOC: Derya Cansever, PhD - [email protected] - (919) 549-4282

ARL Office: Army Research Office (ARO)

Discipline: Computer Science;Data Sciences and Informatics;Network Science

ARL Foundational Research Competencies: Military Information Sciences;Network, Cyber,

and Computational Sciences;Weapons Sciences

Army Modernization Priorities: Long Range Precision Fires;Network/C3I;Next Generation

Combat Vehicle

Keywords: Control, Reinforcement Learning, Quantum, Multi-Agent, Distributed, Data Driven,

Networked Systems

Description:

The objective of the Multi-Agent Network Control program is to establish the physical,

mathematical and information processing foundations for the control of complex dynamic

networks with possibly multiple controllers that may operate using different information sets.

The research program seeks the development of novel mathematical and computational methods

for the modeling and control of the collective behavior of large-scale networked systems

controlled by of heterogeneous agents which may or may not follow a common goal. Autonomy

is central to program efforts to support anticipated dynamics of the future battle space.

Requirements of such environments may include mobility, effective sensor coverage, efficient

information flow, responsiveness to support the military goals of information superiority,

dominant maneuver and precision engagement.

Distributed and Time-Varying Control of Networked Systems

Distributed control techniques play a major role in the analysis and synthesis of networked

systems. They have been successfully used in robotics for replicating self-organized behaviors

found in nature (e.g., bird flocking, fish schooling, and synchronization) and in developing

applications such as formation control, rendezvous, robot coordination, and distributed

estimation. Many dynamic systems are, or can be made time-varying, and they may be subject to

possibly abrupt transitions of the states, and hard to predict disturbances and external effects.

Innovative methods that incorporate, and even exploit time varying nature of distributed systems

for establishing their stability, robustness and optimality is of interest. Analysis and control of

networked non-linear systems where standard linearization methods are not satisfactorily

applicable is also sought. Potential use of techniques such as geometry, graph theory, topological

analysis and other innovative methods are encouraged.

Data Driven Control and Learning

Control of systems with unknown dynamics and methods to reduce their uncertainties has been

part of mainstream control systems research, examples of which include Reinforcement Learning

(RL), Adaptive Control, and in general data driven control. Reinforcement Learning is shown to

be closely related to Stochastic Dynamic Programming, which enabled successful leveraging of

significant body of research of the latter. However, data driven controls such as RL face

significant challenges, including computational complexity, very long convergence times, and

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lack of sufficiently rich training data. Hybrid approaches that properly incorporate prior or

learned models of the systems to be controlled into the problem formulation are emerging and

their furthering is encouraged in this program. Broadly, research to address fundamental issues in

data driven control is sought. Those include, but not limited to, efficient computation methods

that allow real-time operations without sacrificing precision, scalability, optimization algorithms

that address the occurrence of multiple local minima encountered in learning and developing

systematic methods for reliable transfer of learning from other experiments. Use and advancing

of control theoretical tools such as stability analysis, non-convex optimization, and other

innovative approaches to address these open problems is encouraged. New insights to RL

algorithms which may extend, modify, or replace standard Markovian formulations are desired.

Extensions of RL techniques to networked systems featuring multiple controllers with

applications to autonomy and coordination among interacting agents are sought. Innovative

research focused on adaptive control, and system identification techniques to reduce

uncertainties and facilitate optimal or near-optimal control is also in scope.

Control of Quantum Systems and novel applications of control theory

Innovative tools and methodology from control theory could provide new insights and

approaches to pave the path for solving some of the outstanding problems in quantum, such as

maintaining coherence and stability of Quantum Qubits and their entangled states. Capabilities

enabled by quantum computers are expected to surpass their classical counterparts in the future.

However, maintaining the desired state of qubits remains a fundamental problem encountered in

the realization of quantum computers and quantum networks. Adaptation of control theoretical

tools and approaches in enhancing the stability of coherence of qubits and reducing the impact of

noise in quantum gates and their operations could provide new research opportunities in the

control of networked quantum systems.

Researching and devising other applications of control theory in areas that are relevant to the

Army and that could advance the state of control theory itself is of interest. Among novel

applications of potential interest is the study of control functions acting on neural circuits that are

distributed in the brain. These interactions include synchronization, but their fundamental

principles and underlying mechanisms are not well understood. Modeling and analysis of these

phenomena could provide novel research opportunities in the control of networked systems.

Similarly, study of biological systems has unveiled control architectures that are not encountered

in industrial control systems. Understanding the principles, analyzing the effectiveness of such

naturally occurring control systems and their potential adaptation to the control of man-made

applications could be an area of fertile research.

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Army Research Office (ARO) Research Topic

Neurophysiology of CognitionTitle:

ARL-BAA-0016Announcement ID:

TPOC: Chou P. Hung, PhD - [email protected] - (240) 962-0229

ARL Office: Army Research Office (ARO)

Discipline: Biological Sciences;Computer Science;Data Sciences and Informatics;Mathematics

and Statistics;Network Science

ARL Foundational Research Competencies: Biological and Biotechnology Sciences;Humans

in Complex Systems

Army Modernization Priorities:

Keywords:

Description:

The Neurophysiology of Cognition program supports non medically oriented high-risk

high-reward basic research that will enable discovery of the appropriate molecular, cellular,

systems and behavioral-level codes underlying cognition and performance across multiple time

scales. An overarching goal of the program is to foster advances in a broad range of

experimental, computational and theoretical approaches applied to animal models and humans as

well as data. Inquiries are strongly encouraged for projects that include recent methodological

advances to assess and augment the nervous system (i.e., electrophysiological, imaging or

computational). Basic research opportunities are sought in two primary research thrusts within

this program: (i) Evolutionary and Revolutionary Interactions and (ii) Neural Computation.

Evolutionary and Revolutionary Interactions (with Real and Mixed Worlds)

The Evolutionary and Revolutionary Interactions thrust aims to understand evolutionary

neurophysiological processes that enable complex task performance in both unstructured and

structured real-world environments. Foundational research is encouraged to uncover biological

mechanisms and to concurrently develop efficient and adaptive computational and modeling

frameworks that abstract cognitive phenomena such as anticipatory sensing, automatic learning,

complex decision-making, and rapid adaptive action. How these neural phenomena translate

across teams of human and AI agents and span wider ranges of spatiotemporal scales and task

complexities is of particular importance. Experimental approaches building upon man-made

structured and mixed environments with increasingly complex, information-rich/poor/deceptive

and cooperative/competitive features will be most informative. Also, foundational research to

understand and improve cognitive performance and to avoid cognitive failures by understanding

(across neuromechanistic, glymphatic, and neurocomputational levels) sleep and mitigation of

cognitive fatigue due to physiological and environmental stressors is of high value.

Neural Computation, Information Coding, and Translation

The Neural Computation thrust is focused on broadening understanding of the mechanisms

employed by neural circuits and systems to generate desirable computations and to learn and

adapt from few examples. Research in this thrust can broadly address research in areas such as

studying aspects of multiscale information processing dynamics mediating computations among

neurons, glial cells and blood vessels as well as identifying how these circuits and circuit

architectures generate desirable computations over multiple timescales, discovering mechanisms

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for bidirectional control. Mathematical and computational frameworks are encouraged for

closed-loop prediction and control of neural dynamics and to translate across divergent

information types (e.g. differing in information capacity, throughput, modality, processing

architectures, levels of abstraction). Focus should be paid to uncovering fundamental principles

of neural system adaptations required to solve unstructured problems, infer expectations of

teammates and adversaries and of tasks and the environment, and estimating rewards for

complex decisions. Integrative approaches involving combinations of experimentation, theory

and mechanistic modeling are highly encouraged, for both biological and novel hybrid

living-nonliving frameworks.

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Army Research Office (ARO) Research Topic

OptoelectronicsTitle:

ARL-BAA-0019Announcement ID:

TPOC: Michael D. Gerhold, PhD - [email protected] - (919) 549-4357

ARL Office: Army Research Office (ARO)

Discipline: Electronics

ARL Foundational Research Competencies: Electromagnetic Spectrum Sciences;Energy

Sciences;Military Information Sciences;Network, Cyber, and Computational Sciences;Photonics,

Electronics, and Quantum Sciences;Sciences of Extreme Materials

Army Modernization Priorities: Air and Missile Defense;Network/C3I;Next Generation

Combat Vehicle

Keywords: optoelectronics, photonics, semiconductor

Description:

Research in this subarea includes novel semiconductor structures, processing techniques, and

integrated optical components. The generation, guidance and control of UV through infrared

signals in semiconductor, dielectric, and metallic materials are of interest. The Army has

semiconductor laser research opportunities based on low dimensional semiconductor structures

(quantum dots, wells, wires, etc.) operating in the eye-safer (>1.4), 3-5, and 8-12 microns regions

for various applications, such as LIDAR, infrared countermeasures, and free space/integrated

data links. Components and sources in the UV/visible spectral ranges (particularly < 300 nm)

may be of interest as well. Research is necessary in semiconductor materials growth and device

processing to improve the efficiency and reliability of the output of devices at these wavelengths.

However, near infrared or wavelength agnostic device advances can be explored for potential

impact on various material systems and wavelengths of interest.

Research that leads to an increase in the data rate of optoelectronic structures is sought.

Interfacing of optoelectronic devices with electronic processors will be investigated for full

utilization of available bandwidth. Electro-optic components will be studied for use in guided

wave data links for interconnections and optoelectronic integration, all requirements for

high-speed full situational awareness. Optical interconnect components are needed in

guided-wave data links for computer interconnection and in free-space links for optical

switching and processing. For high-speed optical signal processing as well as potential for power

scaling, research on individual and 1 or 2-D arrays of surface or edge-emitting lasers is

necessary. Spectral and coherent beam combining approaches for integrated photonics need

more exploration. Research addressing efficient, novel optical components for high-speed

switching based on electro-optic materials, nanostructures, metamaterials or other regimes may

be of interest. Emitters and architectures for novel display and processing of battlefield imagery

are important.

Research on components and sub-elements of photonic circuits used in neuromorphic photonic

information processing and computation are of interest. Photonic processing within a photonic

integrated circuit (PIC) requires smaller and more energy efficient modulator devices on the

order of 5 microns and 1 femtojoule/bit. Modulation bandwidth of 10 Gb/s or more, and

insertion loss of 0.1 dB or less are needed to cascade modulators with less than 1 dB/cm total

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loss. Modulation and bit resolutions of 12 bits or more and floating-point calculations will be

required for PIC processor implementations. Other advances leading to enhanced analog

computing performance regimes including energy efficient and high-speed photodetectors and

light sources (most likely coherent) are sought. Exploration of ideas leading to enhanced use of

photonic interactions in both 2D and 3D architectures that take advantage of photonic degrees of

freedom (wavelength, polarization, spatial modes, etc.) will be considered. While quantum

communications and quantum integrated photonics are not focused upon per se, low bit energy

signals (photon count < 500) may be considered. Such research could impact single photon,

quantum optics regimes due to similar signal to noise considerations.

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Army Research Office (ARO) Research Topic

Physical Properties of MaterialsTitle:

ARL-BAA-0003Announcement ID:

TPOC: Kate J. Duncan, PhD - [email protected] - (410) 278-5456

ARL Office: Army Research Office (ARO)

Discipline: Chemistry;Electronics;Materials Science;Physics

ARL Foundational Research Competencies: Electromagnetic Spectrum Sciences;Energy

Sciences;Photonics, Electronics, and Quantum Sciences

Army Modernization Priorities:

Keywords: Novel functional materials discovery, materials characterization techniques,

materials defects

Description:

The Physical Properties of Materials program seeks to discover novel functional materials and

elucidate fundamental mechanisms responsible for achieving extraordinary electronic,

photonic/optical, magnetic and thermal properties in materials to enable future innovative Army

applications. There are mainly three focus areas in this program:

Novel Functional Materials Discovery area supports the discovery of novel functional materials

with unique compositions and/or structures to realize unique physical properties. Examples of

materials include oxides, nitrides, carbides, chalcogenides, super-lattices, free-standing low

dimensional (0D, 1D, 2D organic / inorganic) materials, hetero-structures, polymers,

organic-inorganic hybrids, co-crystals, etc. Basic research ideas in the areas such as synthesis

(thin films as well as bulk materials), modeling, and influence of external stimuli such as light,

magnetic field etc. to determine unprecedented functional properties (semiconducting,

superconducting, ferroelectric/multiferroic, photonic, magnetic, thermal etc.) are encouraged.

Science & Engineering of Crystal Imperfections area explores the influence (either positive or

negative) of various crystalline imperfections (e.g., point, line, area, volume defects etc.) on the

physical properties (electronic, optical, magnetic, and thermal) in functional materials. Basic

research ideas in the areas such as elucidation of different mechanisms of

incorporation/elimination of the defects during thin film growth/bulk materials processing of

materials, characterization of novel defects, and influence of them on the extraordinary

functional properties of the materials etc. are encouraged.

Novel materials characterization techniques: Development of novel characterization techniques

to determine composition- structure- defects- stimuli- property relationships in functional

materials.

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Army Research Office (ARO) Research Topic

Polymer ChemistryTitle:

ARL-BAA-0002Announcement ID:

TPOC: Robert H. Lambeth - [email protected] - (410) 306-0281

ARL Office: Army Research Office (ARO)

Discipline: Chemistry;Materials Science

ARL Foundational Research Competencies: Mechanical Sciences;Sciences of Extreme

Materials;Terminal Effects;Weapons Sciences

Army Modernization Priorities:

Keywords: polymers, stimuli-responsive materials, polymer-based composites, hybrid materials

Description:

The Polymer Chemistry program supports basic, foundational research in polymer design,

synthesis, and characterization with the goal of linking polymer structure through the

atomic/molecular- nano- and microstructural continuum to bulk macroscopic

properties. Innovative methodologies are sought for synthesizing polymers with well-defined

functionality and architecture with the objective of gaining a more acute understanding of how

chemical structure influences microstructure, morphology, phase behavior, self-assembly,

processing and ultimately, functional/structural properties. The continued development of these

relationships is critical to creating new generations of materials with superior mechanical,

thermal, optical, chemical, electrical, and other transport properties to perform well under

extreme operating conditions. Research areas of interest include but are not limited to the

following:

New synthetic approaches are sought for preparing polymersPolymer Synthesis and Assembly

with well-defined molecular weight, functionality, architecture, tacticity, and sequence. This

could include new methodologies for controlled polymerization, catalyst and initiator design for

tacticity or sequence control, novel strategies for post-polymerization functionalization or

transformation and accessing ultra-high molecular weights. Proposals which link molecular level

control to polymer assembly to access increasingly complex structures with improved selectivity

driven by non-covalent chemistry, solvent effects, and/or immiscibility are also

desired. Assembly of dissimilar materials or polymer alloying concepts where mixing entropy

suppresses phase separation are of particular interest. Biological routes to create or degrade

polymers with stable, non-hydrolytic bonds will also be considered. Methodologies that leverage

autonomy, high-throughput experimentation, and machine learning to accelerate the pace of

discovery are also highly sought.

Polymer networks find broad utility in defense applications yetAdvanced Polymer Networks

suffer numerous limitations due to the nature of their polymerization and the resulting defects

that are formed which tend to dominate their mechanical response. New architectures, topologies

and synthetic approaches are desired to access polymer networks with limited or controlled

defects and/or hierarchical structures leading to extraordinary properties. Incorporation of novel

molecular mechanisms or cascades for energy dissipation, sensing, self-healing, actuation, and

recyclability that are triggered by external forces such as light, stress, and electric or magnetic

fields which enable reversible changes in physical properties. Mechanisms that induce

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responsiveness and local molecular motion in thermosets below T /T and/or require low energy

g m

doses and offer spatiotemporal control are highly desired.

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Army Research Office (ARO) Research Topic

Quantum Information ScienceTitle:

ARL-BAA-0023Announcement ID:

TPOC: Sara Gamble, PhD - [email protected] - (919) 549-4241

ARL Office: Army Research Office (ARO)

Discipline: Computer Science;Materials Science;Physics

ARL Foundational Research Competencies: Military Information Sciences;Network, Cyber,

and Computational Sciences;Photonics, Electronics, and Quantum Sciences

Army Modernization Priorities: Assured PNT;Network/C3I;Next Generation Combat Vehicle

Keywords: quantum information science, quantum sensing, quantum computing, quantum

entanglement, quantum networking

Description:

Quantum mechanics provides the opportunity to perform highly non-classical operations that

have the potential to result in beyond-classical capabilities in sensing, precision measurement,

computation, and networking. The quantum information science program seeks to understand,

control, and exploit such non-classical phenomena for revolutionary advances beyond those

possible with classical systems. An overarching interest is the exploration of small systems

involving small numbers of entangled particles. There are three primary areas of interest within

the program.

Foundational Quantum Physics

Experimental investigations of a fundamental nature of quantum phenomena that are potentially

useful for quantum information science are of interest. Examples include coherence properties,

decoherence mechanisms, decoherence mitigation, entanglement creation and measurement,

nondestructive measurement, complex quantum state manipulation, and quantum feedback. An

important objective is to ascertain the limits of our ability to create, control, and utilize quantum

information in multiple quantum entities in the presence of noise. Systematic materials science

based and/or focused research which identifies and/or mitigates decoherence mechanisms is also

of interest. Models of machine learning that are based on the foundations of quantum physics are

of interest. Theoretical analyses of non-classical phenomena may also be of interest if the work

is strongly coupled to a specific experimental investigation, such as proof-of-concept

demonstrations in atomic, molecular, and optical (AMO) or other systems.

Quantum Sensing and Metrology

This research area seeks to explore, develop, and demonstrate multi-particle coherent systems to

enable beyond classical capabilities in sensing and metrology. Central to this research area is the

exploration of small systems involving a few entangled particles. Topics of interest include the

discovery and exploration of (a) multi-particle quantum states advantageous for sensing and

metrology, (b) quantum circuits that operate on multi-particle quantum states to enable

beyond-classical capabilities, and (c) methods for the readout of quantum states. Other research

topics of interest include theory to explore multi-particle quantum states useful for beyond

classical capabilities, quantitative assessment of capabilities and comparison to classical systems,

efficient state preparation, quantum circuits for processing these states as quantum bits, readout

techniques, decoherence mitigation and error-correction for improved performance, supporting

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algorithms as a basis for processing circuits, connections between the solution of hard

computational problems and overcoming classical limitations in sensing and metrology,

entanglement as a resource, and suitable physical systems and key demonstration experiments.

Quantum Computation and Quantum Networking

Quantum computing and networking will entail the control and manipulation of quantum bits

with high fidelity. The objective is the experimental demonstration of quantum logic performed

on several quantum bits operating simultaneously, which would represent a significant advance

toward that ultimate goal of beyond classical capabilities in information processing.

Demonstrations of quantum feedback and error correction for multiple quantum bit systems are

also of interest. There is particular interest in developing quantum computation algorithms that

efficiently solve classically hard problems, and are useful for applications involving resource

optimization, imaging, and the simulation of complex physical systems. Examples include

machine learning, parameter estimation, constrained optimization, and quantum chemistry,

among others. The ability to transmit information through quantum entanglement distributed

between spatially-separated quantum entities has opened the possibility for new approaches to

information processing. Exploration of quantum networking of information and distributed

quantum information processing based on entanglement is of interest. These include the

exploration of long-range quantum entanglement, entanglement transfer among different

quantum systems, and long-term quantum memory.

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Army Research Office (ARO) Research Topic

Social and Cognitive NetworksTitle:

ARL-BAA-0026Announcement ID:

TPOC: Edward T. Palazzolo, PhD - [email protected] - (919) 549-4234

ARL Office: Army Research Office (ARO)

Discipline: Data Sciences and Informatics;Economics;Education;Network Science;Social

Science

ARL Foundational Research Competencies: Humans in Complex Systems;Military

Information Sciences

Army Modernization Priorities:

Keywords: Social, Cognitive, Network, Behavior, Knowledge, Teams, Learning

Description:

The goal of the Social and Cognitive Networks program is to understand human behaviors and

cognitive processes leading to collective level phenomena particularly relevant in military

settings with an emphasis on high performance teams, computational social science, and

collective resilience. Social networks are the underlying structure of interaction and exchanges

between humans within both strategically designed and emergent or self-organized systems.

Social networks allow for collective actions in which groups of people can communicate,

collaborate, organize, mobilize, attack, and defend. The changing nature of DoD's missions

greatly increase the need for models that capture the cognitive, organizational, and cultural

factors that drive activities of co-present, virtual, or distributed groups, teams, and populations.

Better understanding the human dimension of complexity will provide critical insights about

emerging phenomena, social diffusion and propagation, thresholds, and tipping points.

The Social and Cognitive Networks program supports projects that contribute substantive

knowledge to theories about human behavior and interaction and make methodological

advancements in modeling and analyzing social network structures. This program funds projects

successful in blending theories and methods from the social sciences with rigorous

computational methods from computer science, engineering, and mathematical modeling.

Advances in this program are expected to lead to development of measures, theories, and models

that capture behavioral and cognitive processes leading to emergent phenomena in teams,

organizations, and populations.

Community Cognitive Resilience

Cognitive resilience for sustained operations is a critical need within an evolving environment of

work and family. There is a need to create verifiable models bridging cognitive and social

networks to discover the developmental processes and science of cognitive and social well-being

to establish cognitive resilience in individuals and communities. Research in this program

focuses on rapid integration modalities of mindfulness and hypnotherapy for cognitive

management and improvement as well as emotional regulation. Basic research in this thrust will

explore the impact of these modalities on social science theories from psychology,

communication, anthropology, and sociology. Research will use social networks methods to

explore an individual's impact on and from the communities in which they are embedded.

Research supported in this thrust will explore small- and large-scale network patterns that

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support both individual cognitive resilience and collectively support the community. Priority will

be given to fundamental science (nonclinical) efforts focused on illness to wellness related to

PTSD, depression, anxiety, pain management, suicidal ideation and prevention, healthcare

behaviors, and disease propagation.

Human Behavior and Interaction

This program supports research from disciplines such as communication, health and behavioral

science, industrial and organizational and social psychology, library and information science,

management science, and sociology that use a social networks lens to focus on the ways people

think and interact whereby creating higher-order systems. Topics of interest include social

influence, leadership, trust, team science, cooperation and competition, crisis management, and

mis/disinformation. Such social influence and opinion dynamics research could focus on the

formation and dissolution of civic-minded and violent ideological networks, mobilization of

benign to hostile political movements, propagation of and enduring changes in attitudes leading

to populations reaching consensus or contested states, and network-based interventions. Of

particular interest in research focused on the inflection point between cyberspace and physical

domains to understand the interaction space between the two and work towards predictive

models for when human behaviors are likely to move from one to the other.

Information and Knowledge Management

This program supports social network centric research to study the ways people learn

individually and collectively and how they utilize that information for decision making and goal

attainment. Examples of relevant topics include transactive memories, public goods, collective

action, information sharing, information fidelity, diffusion and propagation dynamics, and

collective decision-making. Diffusion dynamics research will develop mechanistic understanding

of opinion and behavior change associated with influence, contagion, and other social

propagation processes. Collective decision-making research will contribute fundamental theories

and models to predict, evaluate and simulate how teams organize, exchange information, build

knowledge, influence, adapt, learn, and build consensus using cooperative strategies and

emergent capabilities. Furthermore, topics of particular interest include social effects of

human-agent teaming, especially related to information processing, cognitive biases, and support

of multi-team systems and multilevel (nested) systems.

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Army Research Office (ARO) Research Topic

Solid MechanicsTitle:

ARL-BAA-0011Announcement ID:

TPOC: Denise C. Ford, PhD - [email protected] - (919) 549-4244

ARL Office: Army Research Office (ARO)

Discipline: Biological Sciences;Computer Science;Data Sciences and Informatics;Earth and

Environmental Sciences;Materials Science;Mathematics and Statistics;Mechanics;Physics

ARL Foundational Research Competencies: Mechanical Sciences;Network, Cyber, and

Computational Sciences;Sciences of Extreme Materials;Terminal Effects

Army Modernization Priorities:

Keywords:

Description:

The Solid Mechanics Program supports investigations of the behavior of material systems under

extreme high loading and loading rate events, such as impact and blast, repetitive loading, and

temperature and pressure extremes. Development of new computational techniques and

enhanced understanding of the physical processes taking place during deformation, damage

initiation and propagation, and failure are sought.

Advances in computational techniques should aim to connect phenomena occurring at different

spatial and/or temporal scales, substantially improve efficiency and/or accuracy of predictions,

integrate new physical relationships, apply a novel approach to studying a physical process, or

expand the range of conditions at which processes can be studied.

Studies of physical processes should seek to uncover relationships or mechanisms rather than

design or optimize a material system for a specific purpose. Studies of all material types,

including brittle, ductile, soft, and composite will be considered. Novel or nature-inspired

compositions, geometries, and structures are particularly encouraged. Studies of biological

tissues or tissue surrogates will also be considered, and studies of interfaces between tissues are

particularly encouraged.

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Army Research Office (ARO) Research Topic

Support to ARL Foundation Research CompetenciesTitle:

ARL-BAA-0070Announcement ID:

TPOC: Unspecified TPOC - [email protected]

ARL Office: Army Research Office (ARO)

Discipline: Biological Sciences;Chemistry;Computer Science;Data Sciences and

Informatics;Earth and Environmental Sciences;Economics;Education;Electronics;Materials

Science;Mathematics and Statistics;Mechanics;Network Science;Physics;Social Science

ARL Foundational Research Competencies: Biological and Biotechnology

Sciences;Electromagnetic Spectrum Sciences;Energy Sciences;Humans in Complex

Systems;Mechanical Sciences;Military Information Sciences;Network, Cyber, and

Computational Sciences;Photonics, Electronics, and Quantum Sciences;Sciences of Extreme

Materials;Terminal Effects;Weapons Sciences

Army Modernization Priorities:

Keywords:

Description:

Under this topic, ARL will consider whitepapers and proposals that may not directly align to the

current research topics published by an ARL TPOC, but can demonstrate a strong alignment to

ARL's mission. ARL's research mission is executed within identified foundational research

competencies that provide the Army foundational expertise and specialized capabilities grounded

in scientific excellence and driven by unique Army challenges. ARL is always interested in

innovative research whitepapers and proposals that demonstrate a strong alignment to ARL's

foundational research competencies and potential to create discovery, innovation, and transition

of technologies for Army transformational overmatch. To learn more about ARL's foundational

research competencies visit the ARL website at

https://www.arl.army.mil/what-we-do/competencies/.

White papers and proposals submitted under the "'Support to ARL Foundation Research

Competencies" topic must clearly describe the research and objectives and will be considered by

ARL if it is aligned to one or more of these foundational research competencies that support the

ARL mission. Applicants interested in submitting a white paper or proposal under this topic are

strongly encouraged to first make preliminary inquiries as to the potential alignment to an ARL

foundational research competency, funding availability for the type of research effort

contemplated, and identification of an ARL TPOC to receive and review potential white papers

or proposals.

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Army Research Office (ARO) Research Topic

Synthesis and Processing of MaterialsTitle:

ARL-BAA-0013Announcement ID:

TPOC: Andrew D Brown, PhD - [email protected] - (301)641-7014

ARL Office: Army Research Office (ARO)

Discipline: Materials Science;Mechanics;Physics

ARL Foundational Research Competencies: Mechanical Sciences;Sciences of Extreme

Materials;Terminal Effects;Weapons Sciences

Army Modernization Priorities: Next Generation Combat Vehicle;Soldier Lethality

Keywords: synthesis, processing, structural, materials, additive manufacturing, ceramics,

metals, composites

Description:

The Synthesis and Processing of Materials program seeks to discover and illuminate the

governing processing-microstructure-property relationships to enable optimal design and

fabrication of nano or micro structural bulk structural materials. Structural materials refer to

materials such as metals, ceramics, and composites that in bulk are used in applications that

support or transmit mechanical stresses.

supports research focused on understanding theElucidation of Phase Transformations

mechanisms by which materials transition from one state of matter to another in order to enable

the creation of new structural materials. Potential research directions include but are not limited

to: discovering the kinetic mechanisms governing phase transformations and new means of

manipulating them to encourage or impair phase transformations, defining the relationships

between properties of the prior phase and the structural properties of the transformed phase, the

creation of specific short-range orders in amorphous materials with unique mechanical

characteristics, and new routes or methods for synthesizing structural material phases previously

accessible only via extreme pressures or temperatures.

supports research focused onAdvanced Methods for Structural Materials Processing

developing alternatives to conventional methods for the synthesis and processing of structural

materials. Potential research should involve exploring new means and forces in order to establish

the technical foundation for new processing methods for structural materials, or further exploring

the underlying mechanisms of existing advanced manufacturing methods to enhance their

capabilities. Examples of directions to potentially be explored include but are not limited to:

ultrasonic arrangement, plasma manipulation and interactions, biological and novel molecular

precursors, and electromagnetic field interactions.

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Army Research Office (ARO) Research Topic

Wireless Communications NetworksTitle:

ARL-BAA-0015Announcement ID:

TPOC: Robert Ulman, PhD - [email protected] - (919) 549-4330

ARL Office: Army Research Office (ARO)

Discipline: Computer Science;Electronics;Network Science

ARL Foundational Research Competencies: Electromagnetic Spectrum Sciences;Military

Information Sciences;Network, Cyber, and Computational Sciences

Army Modernization Priorities: Network/C3I

Keywords: wireless networks, ad hoc networks, Internet of things

Description:

This program is concerned with the investigation and advancing of network science applied to

communication networks in wireless and tactical environments, focusing on DoD and Army

unique problems. Of primary interest is research applicable to infrastructure-less multi-hop

wireless networks operating in congested and contested spectrum. Also of interest is the analysis

of mutual interaction among the communications, social, and information networks.

Wireless Network Theory

Research is required in the broad area of wireless network science including fundamental limits,

performance characterization, novel architectures, and high-fidelity simulation of multi-hop

wireless networks with mobility, node loss, natural and man-made impairments and

unpredictable, bursty traffic. Novel analytical tools and simulation techniques may be necessary

to allow for the modeling of very large networking scenarios without losing the fidelity at the

physical layer, which is critical in millimeter wave networks.

Emerging communications network paradigms of Software Defined Networking (SDN) and

Network Function Virtualization (NFV) are also of interest as applied to wireless and hybrid

networks. Concepts from SDN/NVF could be adapted for wireless ad hoc networks,

centralization is not desirable, but policy control and hierarchical control of semi-autonomous

systems could adapt to disconnected and limited connectivity networks. NFV, facilitated by

SDN, should adapt resources according to the needs and objectives of the users is desired.

Extending concepts of NVF and adapting the network to the mission can be extended to

distributed data caching and processing.

Ad Hoc and Sensor Networks

Networks serving Army need to operate in highly dynamic environments with limited or no

infrastructure support. Available spectrum may be highly congested and contested, and mobile

nodes may only have access to noisy local information with limited awareness of remote nodes

in the network. Novel networking approaches may be needed to account for the lack of full

network state information and reduce the penalty incurred due to coordination while sustaining

acceptable performance. Networking algorithms may need to choose between various radio

interfaces, such as traditional military bands, mm wave, and commercial (e.g., cellular) to based

on throughput, reliability, and security trade-offs.

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Adaptive and specialized machine learning techniques are needed for dynamic allocation of

network resources based on operation needs, traffic characteristics, mobility, natural and

man-made spectrum interference conditions, and security considerations. Networking and

sensing architectures for cognitive mobile ad hoc networks needs to be developed with

qualitative and quantitative performance measures, and the impacts of mobility, fading, and

multi-user interference needs to be investigated.

Networking in combat operations may need to cope with the presence adversarial actions of

various types, including strategically inserted spectral impediments. New signal processing,

information theory, game theory and network science methodologies are needed to provide

reliable and efficient communications in the presence of various adversarial actions. The analysis

and characterization of fundamental tradeoffs among conflicting objectives such as Low

Probability of Detection (LPD) vs. rate of communications vs. operating in a limited frequency

spectrum are needed, along with novel techniques to achieve optimally located areas in the

trade-off boundaries.

Novel and Revolutionary Methods in Communications and Networking

The synergy among social networking and communication networking, particularly in a tactical

mobile ad-hoc scenario, is a research area that could advance the design of new communication

approaches. There are many social networking aspects that are common to mobile ad-hoc

networking needs such as distributed decision making, robustness, cooperation,

self-organization, and cluster formation.

Novel physical and MAC layer techniques are required to improve LPI / LPD / AJ capabilities as

well as throughput. Examples include mm wave and (sub) THz. bands, which have unique

characteristics to overcome or exploit, such as directivity, large bandwidth, and limited range.

With limited bandwidth, the co-existence and dual use of communication and sensing signals

should be explored. In addition, exploration of quantum information processing, teleportation

and networked quantum information theory is of interest.

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Available Army Research Directorate (ARD) Research Topics

The available Army Research Directorate (ARD) topics are listed in alphabetical order.

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Army Research Directorate (ARD) Research Topic

Active and Passive RF SensingTitle:

ARL-BAA-0061Announcement ID:

TPOC: Timothy J. Garner, PhD - [email protected] - (301) 394-2705

ARL Office: Army Research Directorate (ARD)

Discipline: Electronics

ARL Foundational Research Competencies: Electromagnetic Spectrum Sciences

Army Modernization Priorities: Air and Missile Defense;Future Vertical Lift

Keywords: radar, spectrum awareness, synthetic aperature radar

Description:

ARL seeks to create and experimentally demonstrate concepts, algorithms and enabling

technologies that will provide the Army with new capabilities in sensing across the entire RF

spectrum up through millimeter-wave and THz frequencies. Both active and passive RF sensing

are used for targeting, detection & tracking of airborne and ground-based threats, surveillance,

imaging and maneuver. Key attributes of Army RF sensors are the ability to operate in harsh

environments and constraints on size, weight and power consumption.

Topics of interest include:

Air defense radar

Airborne radar

Ground surveillance radar

Multi-static radar v. Signal processing

Spectrum awareness

Waveform design

Multi-function radar

Synthetic aperture radar

Passive imaging

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Army Research Directorate (ARD) Research Topic

Advanced Manufacturing Research in support of the Sciences of Extreme MaterialsTitle:

Competency

ARL-BAA-0075Announcement ID:

TPOC: Brandon A. McWilliams - [email protected] - (410) 306-2237

ARL Office: Army Research Directorate (ARD)

Discipline: Materials Science;Mechanics

ARL Foundational Research Competencies: Sciences of Extreme Materials

Army Modernization Priorities:

Keywords:

Description:

Army modernization requires a set of robust manufacturing strategies and integrated capabilities

that enable a highly connected and collaborative enterprise. Agile manufacturing involves

digitally enabled advanced manufacturing (AdvM) technologies with ubiquitous access to rapid

prototyping, small-scale production, materials by design, etc. that are capable of scalable, and

on-demand distributed production of components and systems. Agile manufacturing integrates

the procedures, resources, and preparation that are needed to respond to changes in the demand

utilizing systems, resources, and practice to react to these demands and adapt quickly without

jeopardizing the Army's ability to meet the performance requirements.

This area seeks transformational materials that can operate in extreme conditions, and methods

to manufacture them readily in the organic US industrial base as well as in austere environments

at the point of need. Next generation Army components and systems will need to integrate novel

structures of unmatched geometric complexity, and novel materials produced using novel data

driven digital manufacturing methods. Topics of interest include:

Additive manufacturing

Artificial intelligence (AI) and machine learning (ML) techniques for AdvM

Printed hybrid electronics including multi-functional devices and structures

Novel and robust design methodologies for convergent manufacturing

Integrated computational materials engineering (ICME) for development of novel

feedstocks for metallic, ceramic, electronic, and polymer additive manufacturing

Tools for path planning for multi-axis multi-material manufacturing

Digital twin and data management for AdvM

Sensor development and in-situ process monitoring

Interface science for heterogeneous structures

Manufacturing across multiple length scales

Integrated manufacturing of dissimilar and gradient materials

Materials, processing techniques, and algorithms for multiple integrated simultaneous

manufacturing operations

Tools for rapid qualification and certification of new materials and components

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Army Research Directorate (ARD) Research Topic

Advanced Unmanned Aerial Systems (UAS) TechnologiesTitle:

ARL-BAA-0100Announcement ID:

TPOC: John W Gerdes - [email protected] - (410) 278-8735

ARL Office: Army Research Directorate (ARD)

Discipline: Computer Science;Mechanics;Physics

ARL Foundational Research Competencies: Weapons Sciences

Army Modernization Priorities:

Keywords:

Description:

Unmanned aerial systems (UAS) are uniquely suited to project capability forward due to small

size, low cost, and the potential to overwhelm adversaries through swarming. Innovative

capabilities are needed to advance the capability provided by UAS, split into two main focus

areas: platforms and payloads.

Platform capabilities sought include adaptive structures and airframes that enhance range,

endurance, agility, resilience, and covertness. Associated technologies related to propulsion

systems and actuators that advance these objectives are sought, including bio-inspired

technology as well as hybrid platform designs that blend vertical takeoff, efficient cruising flight,

and aggressive maneuvers. Single and multi-agent autonomy, teaming, coordination,

maneuvering, and control are required, including route planning, GPS-denied robust navigation,

obstacle avoidance, swarm planning, and associated modeling and simulation strategies. Control

systems are sought that handle hybrid UAS designs, provide damage tolerance, and translate

high-level mission objectives into low-level control commands for single agents and swarm

coordination.

Payload capabilities sought include sensing hardware advances that provide advantageous size,

weight, and power tradeoffs in Army-relevant fields. These include external sensing modalities,

including intelligence, surveillance, and reconnaissance (ISR); electro-optical and infrared

(EO/IR); and acoustic. Intrinsic sensing capabilities are sought related to self and swarm-state

awareness, including angle of attack and airspeed, relative and absolute positioning and timing,

and data processing and fusion techniques.

Technologies relevant to both platform and payload capabilities are sought that reduce reliance

on heavy computing resources, facilitate cross-coordination among agents of a swarm, and allow

for graceful degradation of performance with variable or absent inter-agent communications.

In-flight and post-flight data analysis, reduction, and processing techniques are sought including

neural networks, artificial intelligence, and other relevant methods that improve sensor readings,

state awareness, and swarm awareness.

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Army Research Directorate (ARD) Research Topic

Advanced Vertical Takeoff and Landing (VTOL) Aircraft TechnologiesTitle:

ARL-BAA-0099Announcement ID:

TPOC: Hao Kang - [email protected] - (410) 278-6811

ARL Office: Army Research Directorate (ARD)

Discipline: Computer Science;Mechanics;Physics

ARL Foundational Research Competencies: Weapons Sciences

Army Modernization Priorities: Future Vertical Lift

Keywords:

Description:

Innovative technologies are needed to achieve higher vehicle speeds and hover efficiency,

greater vehicle ranges, increased payload, and reduced maintenance to achieve performance

attributes for future VTOL platforms. Analytical and experimental capabilities to support

development of advanced numerical methods and computational codes for assessing design,

aeroelastic, aeromechanical, and structural dynamics performance are of interest. ARL conducts

foundational aeromechanics, control, and acoustics research to enable future Army rotorcraft

with performance capabilities that are currently infeasible.

ARL seeks proposals to

develop algorithms, methods, and analysis tools for aeromechanics predictions,

performance assessment, acoustics, flight mechanics, and design space exploration of

VTOL vehicles for sizes ranging from small unmanned aerial systems (UAS) to large

vehicles. These algorithms and methods include, but are not limited to, physics-based

modeling and simulation, high-fidelity modeling and analysis, reduced-order modeling and

approaches, AI/ML-based algorithms, and optimization algorithms.

develop new technologies to achieve revolutionary improvements in vehicle performance

across different flight regimes. These technologies include, but are not limited to, active

flow control, passive and active structural shape control, adaptive morphologies, and

AI/ML for flight control and improved aeromechanical behaviors.

explore innovative vehicle and reconfigurable concepts for large VTOL platforms and

micro/small autonomous air vehicles. Develop design tools for innovative vehicle

platforms and reconfigurable concepts.

Novel proposal concepts from structural dynamics, aerodynamic performance, coupled

fluids/structures, nonlinear dynamics, theoretic perspectives, and flight control are relevant.

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Army Research Directorate (ARD) Research Topic

AI Model Optimization for Real-Time, Scalable Data AnalyticsTitle:

ARL-BAA-0043Announcement ID:

TPOC: Venkateswara Rao Dasari - [email protected] - (410) 278-2846

ARL Office: Army Research Directorate (ARD)

Discipline: Computer Science;Data Sciences and Informatics;Mathematics and Statistics

ARL Foundational Research Competencies: Network, Cyber, and Computational Sciences

Army Modernization Priorities: Network/C3I

Keywords:

Description:

Rapid increases in the number of radically distinct Artificial Intelligence (AI) model

architectures deployed in complex areas with variable resource constraints makes it substantially

challenging to apply unified and automated optimization of these heterogeneous models. Topics

of interest include development of novel computing methods and neural architecture search,

development of comprehensive objective functions, optimization algorithms, abstractions to

encapsulate heterogeneity needed to achieve optimization objectives across various model

architectures and inference engines, as well as theoretical and experimental approaches in

support of generalized AI model optimization. The sheer magnitude of the data generated by

experiments and simulations performed necessitates highly efficient and optimized AI assisted

intelligent methods of processing to make it actionable. Proposed AI optimization architectures

should be tailored to enable real-time large scale data analytics that balance performance,

efficiency, and scalability, accommodating different types of AI models, targeting computing

platforms that may be subject to computational and network resource constraints. We are seeking

proposals that explore new frontiers in computational optimization research addressing problems

of Army interest. We also encourage submissions that investigate related fields that can lead to

discoveries at the intersections of these domains.

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Army Research Directorate (ARD) Research Topic

Artificial Intelligence and Machine Learning with Extremely Sparse DataTitle:

ARL-BAA-0038Announcement ID:

TPOC: Rajgopal Kannan - [email protected] - (225) 802-0880

ARL Office: Army Research Directorate (ARD)

Discipline: Data Sciences and Informatics

ARL Foundational Research Competencies: Military Information Sciences

Army Modernization Priorities:

Keywords:

Description:

The Army has limited data to train or adapt AI&ML systems to dynamic and diverse operating

environments. ARL seeks research to enable Army platforms, intelligence systems and command

systems to learn, infer and provide meaningful predictions in circumstances characterized by

extreme epistemic uncertainty. We expect that combinations of data-driven learning and

domain-expert-elicited rules will ease the need for data, and that uncertainty-aware processing

that considers both aleatoric and epistemic uncertainty over neuro-symbolic architectures will

enlighten the limits of inference due to data-driven learning.

Potential research goals include: 1) theories for optimal learning and inference when supervised

training data is limited, 2) computationally efficient approximations to optimal processing, 3)

determination of state transitions when and when not more traditional AI&ML models are

sufficient in light of task difficulty and availability of data, 4) techniques for efficient processing

on edge computing devices, and 5) methods for distributed learning and inference that leverage

graphical neural networks.

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Army Research Directorate (ARD) Research Topic

Artificial Intelligence and Machine Learning-Enabling Technologies for ExpeditionaryTitle:

Maneuver and Air/Ground Reconnaissance

ARL-BAA-0037Announcement ID:

TPOC: Daniel N. Cassenti, PhD - [email protected] - (301) 394-3726

ARL Office: Army Research Directorate (ARD)

Discipline: Data Sciences and Informatics

ARL Foundational Research Competencies: Military Information Sciences

Army Modernization Priorities: Next Generation Combat Vehicle

Keywords:

Description:

The Army must compete with near-peer adversaries in a dynamic battlefield that will increase in

complexity with the rise of artificial intelligence and machine learning (AI/ML). Mixed-entity

battlefields will require understanding of the strengths and weaknesses of human and

autonomous actors, information processors and decision makers. Two mission types have great

significance for Army research in AI/ML: Expeditionary maneuver and air/ground

reconnaissance. Expeditionary maneuver refers to missions that require strategic placement and

movement of Warfighters and their assets in a battlefield to gain overmatch versus adversaries.

Air/ground reconnaissance refers to missions to obtain information about environmental threats

and adversary activity from manned and autonomous sensor platforms on the ground and in the

air. Optimal performance of these missions will require improvements in autonomous agents,

sensors, and edge computing.

ARL seeks research proposals that advance the state-of-the-art in enabling technologies for

expeditionary maneuver and ground reconnaissance, including: (1) scene understanding for

adversarial threats, degraded visual environments, and tracking of moving objects; (2) robotic

movement over rugged terrain with limited human engagement and correction; (3) secure and

informative data sharing among multiple autonomous systems and human collaborators; (4) data

processing algorithms to provide information to human decision-makers in ways that support the

human's cognitive processing needs; and (5) expansion of a repository of proven AI/ML

algorithms, data, and software. Examples of research products of interest to the Army include

new robotic movement capabilities, cognitive modeling integration with AI processes, advances

in cyber-security for autonomous agents, AI simulation processes, advanced sensing in degraded

visual environments, improved object recognition, and advanced machine learning techniques.

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Army Research Directorate (ARD) Research Topic

Artificial Intelligence and Machine Learning_Managing Massive Data SetsTitle:

ARL-BAA-0039Announcement ID:

TPOC: AI/ML Managing Massive Data Sets Topic -

[email protected]

ARL Office: Army Research Directorate (ARD)

Discipline: Data Sciences and Informatics

ARL Foundational Research Competencies: Military Information Sciences

Army Modernization Priorities: Network/C3I

Keywords:

Description:

The Government collects more data than it can meaningfully process, including image data,

video data, structured data sets for a variety of combat and non-combat missions (e.g. health,

maintenance, logistics, and operations), and various stove-piped, unstructured, massive data sets

that exist primarily in the form of text documents. The scale of data collection challenges human

driven solutions to management and processing. ARL is seeking research proposals that may

increase the government's capacity to process data by assisting and augmenting analysts with

artificial intelligence (AI) and machine learning (ML). Potential research areas include:

Experimental investigation and development of data analytic prototypes.

Technologies that help analysts perceive and understand dynamic and unknown

environments.

Comprehensive models of real-world environments in which AI/ML entities facilitate

course of action development, using intuition and improvisation characteristics in

real-time, dynamic scenarios.

Frameworks and tools for the creation of algorithms.

Tailored algorithms to perform discrete tasks, particularly in the fields of computer vision

and language.

Innovative AI/ML computational environments.

Labeling techniques to generate massive scale annotated data for supervised deep learning.

Methods for edge computation that enable use of deep learning algorithms in constrained

computational environments.

Methods to evaluate and determine effectiveness of algorithmic approaches.

Interfaces for display of, search of, and interaction with algorithmically derived metadata

and tabular structured algorithmic output.

Techniques, hardware, software, and tools for training, testing, and validating algorithms.

Storage and indexing capabilities for local algorithmically produced data.

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Army Research Directorate (ARD) Research Topic

Autonomous Sensing and Information Fusion for Advanced Indications and WarningsTitle:

ARL-BAA-0064Announcement ID:

TPOC: Thomas W. Walker - [email protected] - (301) 394-0756

ARL Office: Army Research Directorate (ARD)

Discipline: Computer Science;Data Sciences and Informatics;Network Science

ARL Foundational Research Competencies: Photonics, Electronics, and Quantum Sciences

Army Modernization Priorities: Future Vertical Lift

Keywords: Autonomous Sensing, Information fusion, geophysical sensors, sensors on small

UAS, networked sensors

Description:

This research effort will focus on developing and enhancing traditional and non-traditional

sensing technologies for robust detection and exploitation of unique objects of predominately

military interest, including targeting sensors. Fusion of multiple information sources; including

unattended ground sensors, and relocatable unattended sensors, typified by small autonomous

ground and air platforms, is essential - and much of the program will be focused on foundational

work aimed at facilitating the correlation and reporting of relevant information between all

sensing sources. The research also investigates end-to-end autonomy solutions enabling remote

delivery of loosely integrated ground and relocatable sensors that operate cooperatively to detect,

track, and identify targets. Fundamental research in the physical phenomenology of both

traditional geo-physical modalities and imaging modalities as well as non-traditional modalities

that will lead to improvements in persistent sensing applications involving unique detection,

processing, exploitation, and novel reporting capabilities across diverse environments and

meteorological conditions for low power, long mission life applications.

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Army Research Directorate (ARD) Research Topic

Ballistic Science ResearchTitle:

ARL-BAA-0097Announcement ID:

TPOC: Muge Fermen-Coker - [email protected] - (410) 278-6018

ARL Office: Army Research Directorate (ARD)

Discipline: Materials Science;Mechanics

ARL Foundational Research Competencies: Terminal Effects

Army Modernization Priorities: Next Generation Combat Vehicle;Soldier Lethality

Keywords:

Description:

ARL seeks proposals to enhance the understanding and characterization of material behavior and

failure during projectile target interactions at ballistic impact speeds.

Specific research areas include:

Directed-energy means and effects.

Laser studies and concepts associated with ballistics.

Fundamental and applied physics research associated with ballistic impact, survivability,

and protection.

Electromagnetisms and concepts associated with ballistics.

Plate- impact and Split-Hopkinson Bar (SHB) experiments for materials relevant to

ballistic weapons and armors.

Materials science research associated with improved ballistic performance.

Molecular, meso-scale, multi-scale, and level modeling capability development, including

material models, failure models, and analytical models associated with ballistic impact and

penetration and effectiveness.

Experimental techniques and diagnostics associated with ballistic research.

Novel manufacturing and processing techniques are of interest, provided that the work will

involve high strain rate relevant research scope.

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Army Research Directorate (ARD) Research Topic

Computational Modeling of Aviation SystemsTitle:

ARL-BAA-0101Announcement ID:

TPOC: Phuriwat Anusonti-Inthra - [email protected] - (410) 278-3556

ARL Office: Army Research Directorate (ARD)

Discipline: Computer Science;Mechanics;Physics

ARL Foundational Research Competencies: Weapons Sciences

Army Modernization Priorities:

Keywords:

Description:

Next-generation Army aviation platforms will need to integrate novel technologies in multiple

areas including aerodynamics, acoustics, structural dynamics, and flight controls. These

technologies will be evaluated in computational and experimental environments for real-world

applications. Fundamental modeling and analysis capabilities also need to be developed at

different degrees of fidelity from low fidelity for conceptual design and trade-space exploration

to high fidelity for detailed design or scientific exploration.

Novel technologies for next-generation Army aviation platforms are sought, including both

manned platforms and unmanned aerial systems (UAS). Associated modeling and simulation

approaches for these technologies will be required at varying degrees of fidelity to accommodate

assessments at different stages of design and analysis processes including conceptual,

preliminary, and detailed design stages. Topics of interest include:

Aerodynamics, acoustics, structural dynamics, and flight controls, including component

designs or concepts and software or algorithms for computational modeling of those

technology areas.

Both physics-based and data-driven techniques for modeling and simulation

Design methodologies for these new technologies

Methods to incorporate complex physics such as interactional aerodynamics or electric

powertrain models at a low computational cost suitable for conceptual or preliminary

design.

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Army Research Directorate (ARD) Research Topic

Computational Modeling of Complex Physical SystemsTitle:

ARL-BAA-0041Announcement ID:

TPOC: Jaroslaw Knap, PhD - [email protected] - (410) 278-0420

ARL Office: Army Research Directorate (ARD)

Discipline: Chemistry;Computer Science;Electronics;Materials Science;Mathematics and

Statistics;Physics

ARL Foundational Research Competencies: Network, Cyber, and Computational Sciences

Army Modernization Priorities: Network/C3I;Next Generation Combat Vehicle

Keywords:

Description:

Concentrates on the fundamental aspects of computational science (CS) to enable

multi-disciplinary and multi-scale modeling and simulation (M&S) to predict, quantify, assess,

and optimize the performance and response of complex system and system of systems, enabling

rapid design, development, and transition particularly in cases where laboratory experimental

approaches are costly and difficult to conduct, and/or are not feasible. Proposals are requested

for the following areas:

Computational Mathematics and Algorithms

Research encompasses a range of disciplines seeking new computational methodologies to solve

fundamental equations. Solutions may be sought for existing equations or new equations may be

developed expressly for the purpose of treating problems of Army relevance. Problems in which

the equations can be expressed in the form of partial differential equations may stem from the

basic science and engineering disciplines spanning characteristic length scales from sub-atomic

to continuum, neural signals, stochastic variables, and design theory. Broad classes of problems

may also require considerable specialization of solutions based on the platform used to obtain

them.

Uncertainty Quantification (UQ)

Research is focused on assessing predictive capabilities of models, considering the range of

conditions where models reproduce observed behavior within acceptable tolerances and

establishing confidence levels. UQ research is concerned with novel and efficient concepts and

methodologies for high-fidelity assessment of the level of agreement in sets of models relative to

input and output data, as well as the variations in interdependent models due to various physics,

mathematical, and numerical assumptions. UQ methodologies, integrated with data sciences and

machine learning will enable tools for (i) identifying deficiencies in simulations; (ii) setting

guidelines for adequacy of computational results; (iii) exploring the impact of known variability

and uncertainty of input; and (iv) control of adaptive algorithms to achieve specified levels of

accuracy to aid decisions from design to operational planning.

Multi-scale Modeling

Research focuses on the development of models of complex physical systems in order to

significantly reduce development time and evaluation costs of these systems. This goal can be

through development of 1) high-fidelity at-scale models and 2) computational methodologies

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(numerical methods and associated algorithms) to enable rapid creation of new high-fidelity

multi-scale models of complex systems from at-scale models capable of utilizing modern

extreme-scale computing. The success of multi-scale modeling hinges on the ability to combine

at-scale models into a multi-scale model. However, few numerical methodologies and associated

algorithms have been developed so far to enable such scale-bridging. Moreover, many at-scale

models are extremely demanding computationally and render any multi-scale model utilizing

them unsuitable for practical applications. While surrogate modeling allows reduction of this

computational cost, most methodologies for surrogate modeling are global and thus

characterized by a relatively high cost. New adaptive non-local surrogate modeling

methodologies are needed, which can bring the computational cost to tractable levels. Finally,

at-scale models are frequently endowed with uncertainty due to various sources such as natural

fluctuations, model parameters or model form. This uncertainty and natural variability must be

consistently incorporated into multi-scale computer models to enable computational design.

Machine Learning for Complex Physical Systems

Many Army activities rely on the use of computer models to facilitate making purposeful

decisions. These models often aim to capture behavior of physical systems with many degrees of

freedom, complex dynamics and short time scales. Because of that, existing models often

struggle to adequately span the problem space and cannot be effectively employed to optimize

these Army systems for desired performance. The advent of data science and machine learning

has opened for avenues for improved computer models of physical systems. Yet, direct

applications of existing machine learning techniques to model physical systems are fraught with

challenges. First and foremost, success of machine learning hinges on availability of vast

amounts of data. In contrast, for many physical systems data are rarely obtainable in vast

amounts due to high cost of acquisition and/or experimentation. In addition, the behavior of

physical systems is customarily governed by well-established laws, for example conservation of

mass and energy. Consequently, machine-learning models of physical systems must strictly obey

these laws. Finally, for many physical systems under certain regimes, experimentation is not

technically possible or prohibitively costly. In these circumstances, models of physical systems

serve to extrapolate the description of system response outside of regimes where the

experimentation is feasible. Current machine-learning approaches are known to perform poorly

under extrapolation. Hence, novel approaches in machine learning are urgently needed to allow

for construction of high-fidelity and predictive models of physical systems.

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Army Research Directorate (ARD) Research Topic

Cyber SecurityTitle:

ARL-BAA-0044Announcement ID:

TPOC: Jerry A. Clarke - [email protected] - (410) 278-9279

ARL Office: Army Research Directorate (ARD)

Discipline: Computer Science;Network Science

ARL Foundational Research Competencies: Network, Cyber, and Computational Sciences

Army Modernization Priorities: Network/C3I;Next Generation Combat Vehicle

Keywords:

Description:

The ARL Network Cyber and Computational Sciences foundational research competency of

cyber-defense/cyber-security addresses the prevention, detection, mitigation, monitoring, and

prediction of adversarial activities and their impacts within cyber space. The scope includes

traditional enterprise level and tactical information networks as well as non-traditional networks

such as communication buses found on vehicle platforms. This research effort will focus on

developing the theories, understanding, models and methods to overcome existing barriers to the

realization of effective cyber security defenses and maneuvers against adaptive and sophisticated

adversaries in complex, uncertain and dynamic settings.

The goals of this work are:

Pursue near-autonomous, rapid, resource-efficient monitoring, detection and identification

of malicious cyber activity directed at friendly networks, data, machine learning

algorithms and/or vehicle platform systems.

Advance the predictive characterization of information networks and/or vehicle platform

systems states, resilience and vulnerabilities to cyber-attacks and adversarial

manipulation.

Pursue methodologies for the reliable reconfiguration of friendly cyber assets to evade or

recover from attack, to validate system resilience, and enable continued operations and

mission success.

Advance methods to rapidly and efficiently prepare and respond to adversarial activities in

the cyber domain, including:

Intelligent preparation of the cyber battlespace and cyber situational awareness

Proactive and reactive cyber deception and counter-deception strategies

Covert means for collection of evidence and predictive analysis of enemy actions

and capabilities

Countering the evasion and manipulation of machine learning algorithms

Building cyber resilience

Pursue methodologies to deceive, degrade or destroy adversarial cyber assets with high

certainty.

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Army Research Directorate (ARD) Research Topic

Disruptive Energetic Materials and ConceptsTitle:

ARL-BAA-0066Announcement ID:

TPOC: Edward F. Byrd, PhD - [email protected] - (410) 306-0729

ARL Office: Army Research Directorate (ARD)

Discipline: Chemistry;Materials Science;Physics

ARL Foundational Research Competencies: Weapons Sciences

Army Modernization Priorities: Air and Missile Defense;Long Range Precision Fires;Next

Generation Combat Vehicle;Soldier Lethality

Keywords: energetic materials, explosives, propulsion, propellants, modeling, experimentation,

synthesis, multiscale, range, lethality, reactive materials

Description:

Improved models, concepts, diagnostics and new energetic materials for propulsion and

explosives are expected to provide enhanced lethality and range, speed of engagement, and

maneuverability while maintaining weapons safety and surety. Additionally, game-changing

energetic concepts with greater than state-of-the-art potential than previous energetics are being

pursued and are expected to enable new approaches to lethality and range, particularly when

partnered with emerging accuracy and precision advances.

These efforts will focus on the exploration and maturation of novel energetic materials and

concepts for explosive and propulsive applications which are expected to provide revolutionary

performance capabilities that are unachievable today. Research in this area seeks to synthesize

high energy density materials with desired physical properties, scale-up techniques, novel

manufacturing and processing techniques, understand and control energy release on desired

timescales, novel diagnostic techniques capturing relevant chemistry and physics, advanced

modeling and simulation of multiscale behavior, novel concepts maximizing work performed

and minimizing losses, and predictive tools guiding performance, synthesis, and processing

directions.

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Army Research Directorate (ARD) Research Topic

Electric- and Magnetic-Field Sensor TechnologyTitle:

ARL-BAA-0076Announcement ID:

TPOC: Stephen J Vinci - [email protected] - (301) 394-0418

ARL Office: Army Research Directorate (ARD)

Discipline: Electronics;Physics

ARL Foundational Research Competencies: Electromagnetic Spectrum Sciences

Army Modernization Priorities:

Keywords:

Description:

Research proposals are desired that are related to small, rugged, low-power electric- and

magnetic-field sensors that can be deployed on a battlefield using artillery-based delivery

systems, or scattered from air or ground vehicles, or emplaced by individual soldiers. These

sensors should be passive or semi-active (i.e., with no local field-generating element), and may

operate at low frequencies in the quasi-static zone (or "near field"), where the electric and

magnetic fields are not coupled. These sensors should be characterized by exceptionally low

power, size, weight, and cost, and/or by exceptionally high sensitivity and low noise (i.e., with

performance limited by the background environment). Sensor bandwidth generally falls between

DC and ~1 MHz, but may be further limited for specific applications: e.g., 0.001-10 Hz for

anomaly detection; 30-3000 Hz for electric-power sensing; 3-30 kHz for very low frequency

(VLF) sensing.

Sensors should operate in an unattended mode, and should be able to detect, classify, identify,

localize, and/or track tactically-significant targets, including ground vehicles (tanks and other

tracked vehicles, and wheeled vehicles), air vehicles (fixed-wing, rotary-wing, unmanned aerial

vehicles (UAV) / manned aerial vehicles (MAV), etc.), and/or other targets and events at

tactically-useful distances. These other targets include, but are not limited to, armed individual

soldiers, underground facilities, power and telephone lines, RF transmitters; other events

including gunshots, mortar and artillery launches, and explosions.

These sensors may be used individually or as part of a wide-area sensor array for surveillance,

target acquisition, and/or engagement. While individual sensors may or may not have

exceptional individual performance, their low size, power, weight, and cost should permit them

to be used on the battlefield in ways not previously contemplated. Moreover, arrays and/or

networks of such sensors are expected to provide new sensing capabilities and levels of

performance simply not available today.

Unattended surveillance sensors may be stationary or mounted on robotic platforms; these

sensors will be integrated with local and networked signal processing and communications

capabilities. They should operate unattended for weeks or months after deployment, and

indefinitely with energy harvesting. The sensor output should be quantitative: e.g., analog

voltage level(s) or digital word(s); it should contain target information, and possibly a

confidence level, suitable for low-bandwidth transmission and/or inter-sensor fusion.

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Proposals will be accepted in six areas:

i. Research on novel electric- and magnetic-field sensor concepts leading to quantification of

detection distance(s), classification, identification, localization, and/or tracking of various classes

of targets. High-performance, low-SWaP-C sensors should have exceptional sensitivity (limited

by environmental noise), frequency and phase response, dynamic range (60 to 120+ dB),

linearity, total harmonic distortion, hysteresis, cross-axis sensitivity, cross-modality sensitivity,

etc. Arrays of sensors should be characterized by exceptional performance matching.

ii. Research directed at environmental and/or platform noise reduction, and/or reduction of

sensor front-end noise (particularly 1/f noise).

iii. Research related to filtering and/or signal processing techniques, which are expected to

improve the detectability of targets in a battlefield environment. Array processing, in-situ

"imaging", and multi-modal processing are of particular interest. Processing should be

resilient with performance that gracefully degrades in the presence of intermittent power,

intermittent and/or unreliable networking, information assurance attacks, memory failures, and

cosmic rays, etc.

iv. Computer-based modeling of targets and sensors that can provide a capability to perform

trade-off analyses of sensor performance during prototype design.

v. Algorithms that can provide improved detection, classification, and/or identification of targets

of interest in real-world environments. Proposed algorithms should be low-SWaP-C, portable to

the Internet of Battlefield Things (IoBT), and usable in tactical networks.

vi. Research related to the novel application of electric- and magnetic-field sensors to analyze

electric power system operation, including islanded microgrids and large fixed grids.

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Army Research Directorate (ARD) Research Topic

Electromechanical and magnetomechanical power conversion (INACTIVE) (INACTIVE)Title:

(INACTIVE) (INACTIVE) (INACTIVE) (INACTIVE) (INACTIVE) (INACTIVE)

(INACTIVE) (INACTIVE) (INACTIVE)

ARL-BAA-0058Announcement ID:

TPOC: Bruce R. Geil - [email protected] - (301) 394-3190

ARL Office: Army Research Directorate (ARD)

Discipline: Electronics

ARL Foundational Research Competencies: Energy Sciences

Army Modernization Priorities: Future Vertical Lift;Next Generation Combat Vehicle

Keywords:

Description:

This research topic has 4 thrust areas:

1. High-torque-density and/or high-power-density electric machines with high efficiency.

2. Novel designs for higher-reliability electromechanical power conversion components,

including magnetic bearings and magnetic gearboxes.

3. High-torque-density, high-efficiency noncontact magnetic gear boxes or magnetically geared

machines, including designs for propulsion and actuation applications.

4. Novel magnetic, electrical, thermal, and/or structural materials for use in electric machines,

magnetic gears, and transformers, including multifunctional materials and alternatives to

rare-earth materials.

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Army Research Directorate (ARD) Research Topic

Energy AwarenessTitle:

ARL-BAA-0056Announcement ID:

TPOC: Robert S Jane - [email protected] - (845) 938-7401

ARL Office: Army Research Directorate (ARD)

Discipline: Data Sciences and Informatics;Electronics

ARL Foundational Research Competencies: Energy Sciences

Army Modernization Priorities: Future Vertical Lift;Next Generation Combat Vehicle

Keywords: energy sensing, energy optimization, energy forecasting

Description:

Technologies providing energy sensors and virtual sensing techniques, at the component,

system and platform level. Primary interest areas are sensors to collect energy flow and use

information; and virtual techniques to generate data on energy when direct sensing is not

available or practical.

Advanced cognitive techniques for real time adaptive prediction and optimization for real

time energy awareness. Primary interest areas are technologies to enable machine-based

decision making for energy management that utilize heuristics and cognitive techniques. A key

goal is to provide learned behavior with input from external sources such as operational data,

weather, maintenance, and other factors.

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Army Research Directorate (ARD) Research Topic

Environmental Security for Multi-Echelon Decision Making -Assessing and MitigatingTitle:

Climate Risk

ARL-BAA-0040Announcement ID:

TPOC: Robb M. Randall, PhD - [email protected] - (575) 678-3123

ARL Office: Army Research Directorate (ARD)

Discipline: Earth and Environmental Sciences

ARL Foundational Research Competencies: Military Information Sciences

Army Modernization Priorities:

Keywords:

Description:

ARL seeks proposals for basic and applied research that advances our understanding of

environmental effects on DoD assets and operations within climatological time frames, to

include dynamics and changes in the dynamics of the atmospheric boundary layer in complex

environments (including high-relief and dense urban terrain) with emphasis on the atmospheric

surface layer and the land-surface processes that effect the environmental state. Research work

products should enable technologies for mission command decision support, interoperability of

distributed networked systems, and mission planning.

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Army Research Directorate (ARD) Research Topic

Estimating and Predicting Human BehaviorTitle:

ARL-BAA-0050Announcement ID:

TPOC: Amar R. Marathe, PhD - [email protected] - (301) 873-2886

ARL Office: Army Research Directorate (ARD)

Discipline: Biological Sciences;Computer Science;Data Sciences and Informatics;Social

Science

ARL Foundational Research Competencies: Humans in Complex Systems

Army Modernization Priorities: Future Vertical Lift;Network/C3I;Next Generation Combat

Vehicle;Soldier Lethality;Synthetic Training Environment

Keywords: Human Variability, Human State Estimation, Human Performance,

Human-Machine Teaming, Opportunistic Sensing

Description:

Summary

Within complex systems, human behavior and skills tends to be highly variable. This variability

in behavior presents challenges for developing techniques for intelligently selecting the right

person for the right job and providing intelligent agents the capability to understand their human

teammates. In addition to these challenges, variability in human behavior also provides potential

information regarding the local context. To address these challenges and capitalize on this

potential information source, this research area focuses on developing novel approaches to

estimate and predict human states (e.g stress, fatigue, task difficulty, intent) to enable technology

adaptation and inference of the environmental context and to estimate and predict human

knowledge, skills, and behaviors in order to forecast an individual's capability to effectively

interact with intelligent systems.

Background

The research goals for estimating and predicting human behavior are to integrate empirical and

theoretical efforts to generate novel concepts and approaches to generate high-resolution

predictions of individual Soldier's performance variability in mixed human-agent teams across

multiple time scales. In turn, these concepts and approaches will provide the foundation for

future Army systems and processes to adapt to the individual Soldier's states, traits, behaviors,

and intentions. Likewise, this will enable identification of the best Soldiers for specific roles and

provide those Soldier the most favorable conditions to train, engage in operations, and team with

intelligent systems and personnel from the U.S. and partner nations.

This research will provide the techniques to generate high resolution, multi-time scale,

predictions of individual Soldier's internal and external behavioral and performance dynamics in

mixed-agent team and across training and operational socio-technical environments. Critical

breakthroughs are needed in two specific areas: (i) creating multi-faceted models to generate

high resolution, moment-to-moment prediction of individual human state based on multi-modal,

multi-time scale data with sufficient resolution to enable technology adaptation; (ii) developing

models to predict an individual's technology fluency, defined as the ability to effectively interact

with dynamic, adaptable, intelligent systems in future operating environments; and (iii) creating

models to leverage information from human behavior and actions to make inferences about the

environment or situation that they are operating within.

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Specific Questions of Interest

How do multi-timescale human processes influence individual's moment-to-moment

capabilities, behaviors, and performance?

What are the multi-disciplinary foundational theories and models required to understand

individual dynamics and emergent team behavior in heterogeneous human-agent teams?

Can models of individual and/or team technological fluency be developed that effectively

predict performance?

What are the knowledge, skills, and behaviors that enable specific individuals to be more

technologically fluent (the ability to use and rapidly adapt novel and intelligent

technologies without formal training on specific technologies) than others?

What are the critical team factors (e.g., composition, interactions, shared situational

awareness) that enable sufficient technological fluency to effectively adapt significant

shifts in technological intelligence and behavior?

Can human cognition be predicted in complex socio-technical setting and on a

moment-to-moment basis with sufficient resolution to provide disruptive military relevant

information?

How can we use current and next-gen human sensing technologies to provide context and

insight (i.e. via access to human cognition) into how individuals and teams understand

complex real-world environments?

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Army Research Directorate (ARD) Research Topic

Heat Transfer and Thermal ManagementTitle:

ARL-BAA-0059Announcement ID:

TPOC: Adam Andrew Wilson - [email protected] - (301) 394-1984

ARL Office: Army Research Directorate (ARD)

Discipline: Electronics

ARL Foundational Research Competencies: Energy Sciences

Army Modernization Priorities: Air and Missile Defense;Future Vertical Lift;Next Generation

Combat Vehicle

Keywords:

Description:

This research topic has two thrust areas:

Materials, packaging, passive/active cooling techniques for thermal transfer and storage.

Fundamental thermal transport, switching, tunability, and phenomenon in

nano/micro/macro-scales for enabling steady-state and fast-transient pulse power,

switching, personnel, and environmental cooling modalities

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Army Research Directorate (ARD) Research Topic

High Voltage/High Frequency Power Switching DevicesTitle:

ARL-BAA-0060Announcement ID:

TPOC: Miguel Hinojosa, PhD - [email protected] - (301) 394-1860

ARL Office: Army Research Directorate (ARD)

Discipline: Electronics

ARL Foundational Research Competencies: Electromagnetic Spectrum Sciences;Energy

Sciences

Army Modernization Priorities: Air and Missile Defense;Future Vertical Lift;Next Generation

Combat Vehicle

Keywords: HV semiconductors, power switches

Description:

Research into semiconductor power devices in the following three thrust areas:

Device design and fabrication of monolithic and hybrid voltage-controlled SiC or GaN

high-temperature high-field power devices.

High-temperature high-field insulator materials for use as gate dielectric and field

passivation layers for application to SiC and/or GaN power devices.

Advanced Technology Computer-Aided Design (TCAD) modeling methods, techniques

and/or material models that advance computational efficiency or accuracy.

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Army Research Directorate (ARD) Research Topic

Human-Guided System AdaptationTitle:

ARL-BAA-0047Announcement ID:

TPOC: Kaleb G. McDowell, PhD - [email protected] - (410) 278-1453

ARL Office: Army Research Directorate (ARD)

Discipline: Biological Sciences;Computer Science;Data Sciences and Informatics;Network

Science;Social Science

ARL Foundational Research Competencies: Humans in Complex Systems

Army Modernization Priorities: Future Vertical Lift;Network/C3I;Next Generation Combat

Vehicle;Soldier Lethality;Synthetic Training Environment

Keywords: Interactive Machine Learning; Human-in-the-Loop Learning; Adaptation;

Human-guided Machine Learning; Reinforcement Learning; Intelligent Technology; Imitation

Learning; Training; Human Feedback

Description:

Summary

The rising capability to rapidly field blue and red force technologies, as well as the proliferation

of Artificial Intelligence (AI) into the civilian environment, will force future Soldier-systems to

have the capability to rapidly adapt. This research topic seeks novel methodologies to enable

humans to efficiently guide the adaptation of blue force technologies through multiple forms of

human interaction to develop new or upgraded human-system team capabilities.

Background

Human-guided system adaptation aims to integrate empirical and theoretical efforts to generate

novel concepts and approaches for humans to influence and guide the evolving behavior of

intelligent technologies for the purposes of effectively solving complex problems under variable

resource and time constraints. We generally characterize the complex problems as more

ambiguously structured with uncertain boundaries (if any) across time and space. Such complex

problems are computationally intractable for common analytic solutions due to massive and

perhaps unattainable data requirements to obtain complete certainty. These problems may not

have singularly optimal solutions, because problems will often have multiple, competing criteria

and all solutions will ultimately reflect trade-offs and reduction of optimality in meeting other

criteria in the set.

Contextualized within the concept of enhancing adaptive human-autonomy teamwork, this topic

specifically seeks to (i) discover a novel suite of mechanisms to extract human intelligence that

ensures Soldiers in the field can efficiently train and adapt intelligent technologies; and (ii)

elucidate principles of effective, stable mutual adaptation between humans and intelligent

systems that improve performance in complex, dynamic environments. If successful, the science

is envisioned to enable in-field human-machine adaptation capable of responding to novel

mission demands, enemy actions, and technological surprise across a wide range of operational

environments for all US Army Modernization areas.

Specific Questions of Interest

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How can human knowledge be leveraged to enable system adaptation in highly uncertain

and poorly understood environments? How do you transfer knowledge of how to do a task

from the Soldier to an intelligent technology in a way that requires little to no expert

knowledge (i.e., without programming skills)? Can you create a suite of knowledge

transfer mechanisms that in combination allow machine learning (ML) to infer intent

under different environments and mission constraints?

Can hierarchical reinforcement learning be extended to dynamic, partially-observed

environments for both improved multi-task generalization and enhanced human

interpretability and compatibility with human-in-the-loop feedback?

Can behavior cloning, intervention learning, learning from human preferences, and

learning from evaluative feedback be combined into a single learning framework with

reinforcement learning to enable continuous adaptation and training of intelligent agents?

How do you ensure long-term stability when allowing groups of people to train ML? How

do you allow ML systems to be adaptable by multiple humans and when should that

adaption occur?

Can crowd-sourcing techniques be used to provide reward shaping and evaluative human

feedback to rapidly train autonomous agents? What are the best methods and approaches

to elicit the notion of "'functional equivalence" from crowd workers?

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Army Research Directorate (ARD) Research Topic

Human-System Team InteractionsTitle:

ARL-BAA-0046Announcement ID:

TPOC: Brandon Scott Perelman, PhD - [email protected] - (410) 278-5968

ARL Office: Army Research Directorate (ARD)

Discipline: Biological Sciences;Computer Science;Data Sciences and Informatics;Network

Science;Social Science

ARL Foundational Research Competencies: Humans in Complex Systems

Army Modernization Priorities: Future Vertical Lift;Network/C3I;Next Generation Combat

Vehicle;Soldier Lethality;Synthetic Training Environment

Keywords: Human-Machine Teaming; Human-Autonomy Teaming; HAT; Human Robot

Interaction; Man-machine interface

Description:

Summary

A critical challenge facing the deployment of human-system teams is developing the necessary

principles to enable dynamic interaction of Soldiers and advanced intelligent systems to

effectively collaborate on complex tasks. This research area focuses on developing: a theoretical

understanding of emergent team properties, techniques to link variability in individual agent

performance to changes in overall team performance, approaches to develop and maintain a

shared situation understanding, methods to dynamically allocate tasks across Soldiers and

intelligent systems in complex adversarial environments. These team-level interactions must be

developed to account for degradation or loss of team capabilities, changes in mission goals or

priorities, and responding to adversarial actions.

Background

The research goals in human-system team interaction are to integrate empirical and theoretical

efforts to generate novel concepts and approaches for future Army multi-, mixed-agent teams

across distributed network systems. These technologies must effectively merge human and agent

capabilities for collaborative decision-making and enhanced team performance; ensure that

diverse teams of Soldiers comprehend new and critical information to maintain unprecedented

situation awareness; and interact effectively with Soldiers and noncombatants to foster trust and

gain community acceptance within complex, dynamic, environments. These heterogenous

multi-agent networked teams will enable faster and better-informed decisions; reduce Soldier

workload; provide otherwise unachievable levels of situation understanding and management;

and maintain strategic and tactical advantages in future operating environments.

The objective of this research is to provide the critical technological breakthroughs needed to

shape current and future operational environments consisting of Soldiers and heterogenous

intelligent systems operating in distributed teams to: (i) rapidly comprehend new and critical

information from a diverse set of battlefield sensors to achieve unprecedented situational

awareness (ii) effectively enable collaborative decision-making and enhanced team performance

in dynamic, and complex socio-technical environments; (iii) effectively coordinate distributed

human-system behaviors to enable actions on an objective; and (iv) rapidly adapt team behaviors

to dynamic battlefield events or unexpected threats across a wide range of operational

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environments for all U.S. Army Modernization areas.

Specific Questions of Interest

What are the general principles that underlie the capability for human-technology teams to

perform any mission, adapt to any situation, and overcome any adversary? How do these

principles change as machine intelligence evolves?

Can we discover novel theories, algorithms, methods modulating individual

human-technology interaction that dramatically improve human-technology robustness in

the presence of complex, real-world environment-task-technology novelty?

Can we predict and optimize mixed teams of humans and agents across a wide spectrum of

real world and future battlefield conditions?

What novel and advanced methods are critical to enable rapid team reconfiguration, in

mixed teams of humans and agents, in rapidly changing socio-technical environments?

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Army Research Directorate (ARD) Research Topic

Hybrid Human-Technology IntelligenceTitle:

ARL-BAA-0049Announcement ID:

TPOC: Javier Omar Garcia, PhD - [email protected] - (949) 981-7697

ARL Office: Army Research Directorate (ARD)

Discipline: Biological Sciences;Computer Science;Data Sciences and Informatics;Network

Science;Social Science

ARL Foundational Research Competencies: Humans in Complex Systems

Army Modernization Priorities: Future Vertical Lift;Network/C3I;Next Generation Combat

Vehicle;Soldier Lethality;Synthetic Training Environment

Keywords: Cognition; Intelligence; Command and Control; Decision Making; Adaptation;

Ideation

Description:

Summary

Future operational environments will require faster than human decision-making within

increasingly complex, dynamic and rapidly evolving sociotechnical environments to ensure a

technological advantage over adversarial forces; current human-technology systems do not take

full advantage of the unique capabilities of both human and machine intelligence. This research

topic seeks anti-disciplinary research aimed at reconceiving human brain processes to optimize

how humans and machines could jointly think (ideation, decision making, adaptation) to

influence decisions and actions previously believed to be outside of human capabilities alone.

Background

Futurists envision seamless integration of humans with technology not only in the future

battlefield of the US Army but also in our everyday lives. This concept extends to teams as it is

well-documented that (i) intricate tasks are routinely implemented in multi-team and (ii) modern

technology has infiltrated nearly every facet of the human experience. This future vision of the

world, coupled with the prioritization of complex multi-domain (e.g., ground, air, cyber)

operations creates substantial challenges to the US Army to maintain overmatch at the

intersection of humans and technology. Briefly, these challenges span temporal and spatial scales

and operate at several levels of complexity. Human-technology teams are expected to operate

independently but coordinated with geographically distributed operations, accommodate

incredibly rapid incoming complex information from distributed sources, and adapt to needs of

different command echelons. With these challenges and needs we must consider

human-technology hybrid systems that operate symbiotically to accomplish mission goals,

account for the emergent hybridized cognitive capabilities of the system and reconceive human

brain processes to optimize human-technology hybrid thinking, perhaps creating new forms of

intelligence that transcends humans' current level of complexity.

This topic seeks to merge scientific advancements from human-guided machine learning (e.g.,

instantaneous crowdsourcing; interactive machine learning) with advancements from

neuroscience (e.g., neuroprosthetics; neurostimulation) and/or team science and training (e.g.,

technology-enhanced human teaming; training for rapid human adaptation) to reimagine the how

thoughts are processed in hybrid human-technology systems. If successful, the science is

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envisioned to allow for 10-1000x faster decision making, exponentially increase decision

complexity, and open new opportunities for idea generation, which fundamentally can change

how the US Army operates in including but not limited to command and control.

Specific Questions of Interest

What brain processes may be hybridized for optimal, faster than human decision making?

What is the limit to the scale of hybridization, in systems, agents, and groups? What new

cognitive elements will arise after hybridizing uniquely human characteristics?

Can agents (i.e., intelligent technologies) integrated with human teams generate novel

ideas faster and more effectively than agents or teams alone? Can hybrid teams converge

information into more effective decisions? Can neurostimulation paired with agents

rapidly promote shared understanding and divergent thinking? Can humans' innate ability

to adapt be made faster and extended to radically different forms of thinking (merged

human-agent thinking)?

Can humans be integrated with intelligent command and control (C2) agents to adapt C2

plans to live, incomplete and potentially erroneous data streams in real time to overcome

semi-predictable and unforeseen events? Can intelligent C2 agent policies be effectively

translated for humans to understand and interpret under stressful and time constrained

conditions? Can a flexible, multi-faceted approach to human-AI interaction (AI as a tool,

AI as a human decision enhancer, trainable AI) improve adaptability to semi-predictable

and unforeseen events?

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Army Research Directorate (ARD) Research Topic

Invincible Materials Research in support of the Sciences of Extreme MaterialsTitle:

Competency

ARL-BAA-0077Announcement ID:

TPOC: Kris Behler, PhD - [email protected] - (410) 306-2238

ARL Office: Army Research Directorate (ARD)

Discipline: Chemistry;Data Sciences and Informatics;Materials Science;Mechanics;Physics

ARL Foundational Research Competencies: Sciences of Extreme Materials

Army Modernization Priorities:

Keywords:

Description:

The invincible materials portfolio focuses on the fundamental, basic and applied material science

and engineering to identify novel and emerging materials, systems and technologies for use

across multiple high valued platforms and systems. The portfolio seeks to expand knowledge of

materials and the related science and engineering of all materials classes with respect to

synthesis, processing, development of novel materials or feedstocks, methods, advanced

manufacturing techniques, experimentation, high through put techniques, machine learning,

characterization, and modeling and simulation. The portfolio seeks to enable the discovery,

development, design and integration of emerging structural, chemical and biological protection,

electronic, laser and energy, materials in traditional and extreme environments such as materials

under high rate and dynamic conditions. The portfolio also seeks material science and

manufacturing technologies that supports the soldier, combat vehicles, combat support vehicles

and other high valued assets to enable improved performance and survivability.

Goals and Objectives:

Provide advances in materials through science and technology to enable improved

protection and survivability of soldiers, combat equipment and combat support equipment

and other high valued assets.

Improve materials performance in extreme and non-traditional environments such as high

rate/dynamic or within the electromagnetic spectrum (lasers for example).

Decrease weight and improve power, energy and fuel efficiency for the soldier, combat

vehicles, combat support vehicles and other high valued assets

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Utilize new or improve upon existing capabilities to rapidly discover, design and develop

materials and the supporting science to enable solutions for the Army.

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Army Research Directorate (ARD) Research Topic

Invisible Materials Research in support of the Sciences of Extreme Materials CompetencyTitle:

ARL-BAA-0078Announcement ID:

TPOC: Daniel De Bonis - [email protected] - (410) 306-0690

ARL Office: Army Research Directorate (ARD)

Discipline: Chemistry;Data Sciences and Informatics;Materials Science;Mechanics;Physics

ARL Foundational Research Competencies: Sciences of Extreme Materials

Army Modernization Priorities:

Keywords:

Description:

The Invisible Materials Portfolio seeks to identify novel electromagnetic spectrum materials

(EMS) for use in a wide range of military applications. The portfolio seeks materials with

advanced capabilities to increase, decreases or alter the energy emitted, scattered or absorbed in

a controlled manner.

Mission

Provide expertise and support for identifying emerging materials science technologies that can

potentially transform how the military is detected by sensors across the entire EMS.

Goals and Objectives

Provide a suite of technologies that can be tailored and fused to improve the Army's ability

to meet diverse platform/system/mission requirements.

Improve the ability to manage EMS emissions from Soldiers, Combat, and Combat

support equipment.

Provide advances in EMS materials to allow future combat force to adapt to unknown

threats across the electromagnetic spectrum (EMS) in real time.

Dramatically improve materials performance to allow extreme EMS performance in

realistic military environments (temperature, UV exposure, humidity, low power, etc.).

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Army Research Directorate (ARD) Research Topic

Isomer Power for Enhanced Mission EnduranceTitle:

ARL-BAA-0098Announcement ID:

TPOC: James J. Carroll - [email protected] - (301) 394-0039

ARL Office: Army Research Directorate (ARD)

Discipline: Chemistry;Physics

ARL Foundational Research Competencies: Energy Sciences

Army Modernization Priorities: Future Vertical Lift;Next Generation Combat Vehicle

Keywords:

Description:

The Army faces significant challenges in meeting its future energy and power needs and is

exploring the feasibility of tapping into nuclear-scale energies via radioisotope decays, whether

natural or induced. For this topic, the emphasis is on the potential for induced energy release

from metastable nuclear excited states (nuclear isomers), particularly when their half-lives are on

the order of a year or longer and when their ground states can release additional energy by

radioactive decay. A key to utilizing isomers as essentially nuclear batteries is the ability to

move a population of nuclei from a long-lived isomeric state to the ground state via a nuclear

reaction: this has been termed "'isomer switching" or "'isomer depletion" and has been discussed

in the scientific literature (see the 2024 publication of "'Isomer Depletion" in the European

Physical Journal - Special Topics). For most processes envisioned for isomer

switching/depletion, the two general components are 1) a pathway of electromagnetic transitions

within an isomeric nucleus that leads from the isomer to the ground state and 2) a mechanism by

which to initiate the switching via the transition from the isomer to a higher-lying excited state

that starts the switching/depletion pathway. The recent demonstration of nuclear excitation by

electron capture (NEEC) shows one possible mechanism by which to initiate isomer

switching/depletion, but there are also other known mechanisms that may be useful for some

long-lived isomers. Other related research areas include the study of reactions by which to best

produce isomers and ways to eventually convert the released energy of induced decays

(following isomer switching/depletion) into useful energy and power.

ARL seeks research proposals that advance the state-of-the-art in research into isomer

switching/depletion in the areas described above and which augment and/or expand ARL's

existing internal efforts. Such proposals could be experimental in scope, providing new

approaches to identifying switching/depletion pathways in nuclei having long-lived isomers,

investigating NEEC or other switching/depletion mechanisms, or studying isomer-production

reactions. Much of ARL's internal research into isomer switching/depletion have focused on

beam-based approaches using facilities like that at Argonne National Laboratory

ATLAS/Gammasphere using multi-fold gamma-ray spectroscopy. Proposals could follow

similar methods, but could also suggest other approaches using implantation detectors,

etc. Proposals could also be theoretical in scope, seeking to better understand the nuclear

structure leading to effective switching/depletion pathways in nuclei of interest, or enhancing

models for NEEC or other switching/depletion mechanisms. Proposals to study reactions for

isomer production would also be of interest.

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Army Research Directorate (ARD) Research Topic

Light Manipulating Materials and DevicesTitle:

ARL-BAA-0036Announcement ID:

TPOC: William Shensky - [email protected] - (301) 394-0937

ARL Office: Army Research Directorate (ARD)

Discipline: Chemistry;Materials Science;Physics

ARL Foundational Research Competencies: Energy Sciences

Army Modernization Priorities: Future Vertical Lift;Next Generation Combat Vehicle;Soldier

Lethality

Keywords: Nonlinear optics. metamaterials, novel optical materials, optical switching

Description:

Light manipulating materials and devices: The Energy Sciences Competency requires research in

transparent nonlinear optical (NLO) materials, electro-optical (EO) materials, metamaterials, and

related components and devices that can reduce their optical transmission across the visible,

NIR, SWIR, MWIR, and/or LWIR wavelength range passively or actively, when subjected to an

incident laser beam. Orders-of-magnitude of reduction of transmission, or optical density (OD),

is desired. Materials and devices must be highly transmissive in the initial state.

Technical areas of interest include, but are not limited to, the following:

Development of optical materials with large nonlinearities and a broad wavelength and/or

pulse-width response (fs to continuous wave). This can include molecular modeling,

material synthesis, and characterization of nonlinear parameters as well as nonlinear

transmission studies to determine structure-property relationships to improve their

response. Materials can be organic, inorganic, or hybrid.

Modeling efforts to relate material properties to their ability to affect laser light. Modeling

effort should include details on how the materials affect the propagation of incoming laser

beams.

Development of metamaterial structures and nanoparticles, or other structured or

engineered materials and devices that can reflect, scatter, or otherwise affect laser

propagation, including modeling studies and characterization efforts.

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Army Research Directorate (ARD) Research Topic

Mechanical Metamaterials for Advanced ProtectionTitle:

ARL-BAA-0096Announcement ID:

TPOC: Muge Fermen-Coker - [email protected] - (410) 278-6018

ARL Office: Army Research Directorate (ARD)

Discipline: Chemistry;Materials Science;Mechanics

ARL Foundational Research Competencies: Terminal Effects

Army Modernization Priorities: Next Generation Combat Vehicle

Keywords:

Description:

DEVCOM ARL is seeking proposals on the exploration and maturation of mechanical

metamaterials and associated concepts, testing/diagnostics methods for characterization, scale-up

methods etc., in a manner relevant to ballistic impact conditions. Novel manufacturing and

processing techniques are of interest, provided that the work will involve high strain rate relevant

characterization. Research in this area seeks to understand and control/manipulate material

behavior to ballistic advantage, understand behavior on various scales, advanced modeling and

simulation associated with these materials for enhanced understanding and further

design/development of mechanical metamaterials.

Specific research areas include:

Mechanical metamaterials, nanostructured composites, engineered materials specifically

built for manipulating shock and damage propagation due to ballistic impact and

penetration.

Special consideration for increasing thickness, towards building 3D mechanical

metamaterials.

Fundamental systematic studies to link manufacturing/synthesis process,

nano/microstructure, mechanical properties, high strain rate properties, and ballistic

performance.

Use or development of machine learning based approaches to aid in material discovery and

design of mechanical metamaterials when there is no ‘big data'.

Modeling and simulation of such structures at various scales.

Multi-scale modeling approaches, verification, and validation involving mechanical

metamaterials.

Developing/using experimental techniques and diagnostics to assess/characterize

mechanical metamaterials. Scaling effects associated with small scale experimentation of

such materials, and exploration of how they translate to continuum scale dynamic

properties and performance.

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Army Research Directorate (ARD) Research Topic

Multimodal Synthetic Data for Machine LearningTitle:

ARL-BAA-0079Announcement ID:

TPOC: Raghuveer M. Rao, PhD - [email protected] - (301) 394-0860

ARL Office: Army Research Directorate (ARD)

Discipline: Data Sciences and Informatics

ARL Foundational Research Competencies: Military Information Sciences

Army Modernization Priorities: Next Generation Combat Vehicle

Keywords:

Description:

The use of artificial intelligence solutions for Army field applications will rely heavily on

machine learning (ML) algorithms. Current ML algorithms need large amounts of

mission-relevant training data to enable them to perform well in tasks such as object and activity

recognition, and high-level decision making. Battlefield data sources can be heterogeneous,

encompassing multiple sensing modalities. Present open-source data sets for training ML

approaches provide inadequate representation of scenes and situations of interest to the Army, in

both content and sensing modalities. There is a push to use synthetic data to make up for the

paucity of real-world training data relevant to military multi-domain operations of the future.

However, there are no systematic approaches for synthetic generation of data that provide any

degree of assurance of improved real-world performance of the ML techniques trained on such

data. The problem of effective synthetic data generation for ML raises deeper questions than that

of artificially generating speech or imagery that humans find realistic.

Accordingly, ARL seeks research proposals in the following (1) Synthesis techniques for

multimodal machine learning (2) Machine learning for synthesis of causality and hierarchical

relationships (3) Continuous and/or incremental multimodal learning (3) Algorithms and

architectures that learn physics or are endowed with relevant domain knowledge (4) Domain

adaptation techniques with rich intermediate representations (5) Methods for providing insight

into ML models' internal representations and comparison of synthetic versus real representations.

Additional related areas will also be considered.

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Army Research Directorate (ARD) Research Topic

Networking Structure, Dynamics, and ProtocolsTitle:

ARL-BAA-0045Announcement ID:

TPOC: Robert J. Drost, PhD - [email protected] - (301) 394-0158

ARL Office: Army Research Directorate (ARD)

Discipline: Computer Science;Electronics;Mathematics and Statistics;Network Science;Physics

ARL Foundational Research Competencies: Network, Cyber, and Computational Sciences

Army Modernization Priorities: Network/C3I

Keywords:

Description:

The Network, Cyber, and Computational Sciences (NC&CS) foundational research competency

of Networking Structures, Dynamics, and Protocols addresses the increasingly complex

battlefields (highly dynamic, wireless, mobile networking environment populated by hundreds to

thousands of networked nodes) in which the Army must be able to communicate. Often, these

environments are austere in terms of availability of resources for supporting and servicing the

networking equipment. They are highly congested by multiple conflicting demands on

bandwidth and severely contested by a capable adversary. Research in networking and

communications will address these multiple and complex challenges by pursuing the following

overarching goals:

Diverse, effective channels-traditional and non-traditional-will be available for creating

heterogeneous networks rapidly, predictably, and in a manner optimized for specific

requirements and constraints of mission and environment, adapting intelligently to

challenges of terrain, atmospheric conditions, local bandwidth congestion, and ensuring

high performance along with energy efficiency and minimized probability of detection and

interception by the adversary. Inclusion of quantum channels and networks may provide

breakthrough capabilities beyond what is conventionally (classically) possible.

The networks will be autonomously driven to meet performance goals/priories provided by

the warfighter, through protocols and algorithms for control and processing of signal and

information, as well as for self-organization of the network. These protocols/algorithms

will ensure persistent high performance of the network, consistent with dynamically

changing missions, supportive of rapid reorganization and mobility of friendly forces, and

be highly robust against strong disruptions.

Survivability and defensive properties will be integral to the future network, making it

inherently secure and survivable against disruptions by adversarial attacks such as

jamming and other forms of interference, in part by minimizing probability of the

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communications and networks detection, interception, penetration, and information

exfiltration, as well as by responding to adversary actions by agile maneuver and

recovery.

The NC&CS core competency on Networking Structure, Dynamics, and Protocols will provide

underpinning technology for Army capabilities where it is critical to ensure communications

remain reliable, robust, and resilient in the face of disruptive effects such as task reorganization,

mobility of friendly forces, and adversarial attacks on friendly networks in future tactical

environments.

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Army Research Directorate (ARD) Research Topic

Neuroscience and NeurotechnologyTitle:

ARL-BAA-0048Announcement ID:

TPOC: David Lloyd Boothe, PhD - [email protected] - (410) 278-8562

ARL Office: Army Research Directorate (ARD)

Discipline: Biological Sciences;Computer Science;Data Sciences and Informatics;Mathematics

and Statistics;Network Science

ARL Foundational Research Competencies: Humans in Complex Systems

Army Modernization Priorities: Future Vertical Lift;Network/C3I;Next Generation Combat

Vehicle;Soldier Lethality;Synthetic Training Environment

Keywords: Neuroscience; Intelligence; Decision Making; Adaptation; Ideation, Representation,

Abstraction

Description:

Summary

The human nervous system is the most intelligent complex system in the known universe. This

research area attempts to understand and harness the power of the nervous system for the

advancement of future human-technology systems. This topic seeks to integrate neuroscience

with traditional approaches to understanding Soldier behavior to enable system designs that

maximize human-system performance, and also attempts to leverage an understanding of the

nervous system to drive the development of novel computational approaches necessary for

creating future intelligent systems.

Background

The future battlefield presents substantial challenges to the US Army to maintain overmatch at

the intersection of humans and technology. This topic aims to harness the power of the human

nervous system to enable neuroscientific principles to be used to maximize Soldier-system

performance and to drive the understanding and development of novel computational approaches

necessary for improving future algorithms and human machine teams. Specifically, the topic

focuses on the properties of biological systems that allow them to rapidly adapt to changing

context, robustly operate together to complete complex tasks, and quickly understand

environmental constraints to perform actions.

The topic has two discrete integrative, transdisciplinary thrust areas that aim to transcend a single

biological system and be applicable to human-technology systems that span a wide variety of

spatial and temporal scales. (i) The topic aims to abstract the human brain to uncover

computational approaches that can be used to develop robust, human-compatible intelligent

technologies by understanding how connectivity, unit dynamics, and parallel computation

underlie the ability of biological nervous systems to generate abstract representations and predict

future outcomes. If successful, the science is envisioned to generate intelligent algorithms

demonstrating improved flexibility and ability to work ergonomically with human teammates.

(ii) The topic aims to uncover foundational principles of the inter-brain system interactions

underlying heterogeneous effective human-human and human-machine teams. Research is

envisioned that builds off of recent analytical advances in neuroscience such as linking network

features such as connectivity and unit dynamics to the brains ability to construct abstract

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representations and cognition, by the application of new methods to represent neuronal

information such as manifolds, topological data analysis, network science, and dynamical

systems theory.

Specific Questions of Interest

How can current advances in computational methods that transcend disciplines modify our

understanding of brain function? How will emerging (and converging) methods of neural

recording shape our knowledge of brain function? How will new methods, developed on

neural measurements transcend to other complex systems?

What is the primary system to reach and mimic the human's ability to rapidly adapt to

rapidly changing contexts? What are the functional properties of some of the most basic

human properties?

Can we create new machine architectures by mimicking the ability of humans to overcome

uncertainty and context dependence?

How can a mechanistic understanding of inter-brain system interactions enable team

behavioral modification? What advances in computational approaches to detect and

predict team states enable in neural enhancement? How will inter-brain network neural

enhancement affect group behavior?

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Army Research Directorate (ARD) Research Topic

New Developments in Antenna AperturesTitle:

ARL-BAA-0062Announcement ID:

TPOC: Gregory Mitchell, PhD - [email protected] - (301) 394-2322

ARL Office: Army Research Directorate (ARD)

Discipline: Electronics;Materials Science;Physics

ARL Foundational Research Competencies: Electromagnetic Spectrum Sciences

Army Modernization Priorities: Air and Missile Defense;Future Vertical Lift

Keywords: additive manufacturing, antennas, electromagnetic skins

Description:

ARL seeks to develop antenna apertures (i.e., antennas and antenna arrays) for future Army

systems. To realize these radiating structures, there is interest in utilizing new man-made, or

engineered materials, as well as novel processes such as additive manufacturing. Future

platforms will require apertures that are low in profile and can be integrated into both ground and

airborne platforms and are conformal to such platforms. Such apertures should have little or no

visible signature as well as minimal or no obvious protrusion.

Topics of interest include:

Antennas and arrays using engineered materials (e.g., metamaterials)

Electrically thin antennas, integrated into platforms

Electromagnetic skins for required functions

Balun designs exploiting engineered materials and/or additive manufacturing

Apertures with integrated flexible electronics

Diversity schemes for enhanced performance

Conformal antennas and arrays

Additive manufacturing of antennas and RF devices

Antennas that use bio and synthetic biomaterials

Machine learning for development and enhancement of antennas and RF devices

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Army Research Directorate (ARD) Research Topic

Novel Computing Architecture and Algorithm Co-designTitle:

ARL-BAA-0042Announcement ID:

TPOC: Barry R Secrest - [email protected] - (410) 306-1313

ARL Office: Army Research Directorate (ARD)

Discipline: Computer Science;Electronics

ARL Foundational Research Competencies: Network, Cyber, and Computational Sciences

Army Modernization Priorities: Network/C3I

Keywords:

Description:

Theories, models, analyses and development of advanced and unconventional computing

architectures and algorithms optimized to run on novel and emerging architectures. Spanning

commercial off the shelf (COTS), domain- and application-specific computing architectures,

such as lightweight, non-von-Neumann and other emerging architectures. Algorithms and

methods for constrained resource computing with distributed/decentralized communication-, low

size-weight-and-power (SWAP), and scalable computing.

Represented in this BAA for the NC&CS Competency are computer architecture, algorithmic,

and hardware/software co-design goals that form a robust advanced computing foundation to

understand and overcome complex fundamental challenges simultaneous to improving

approaches of importance to the Army. These areas include weapon systems design;

materials-by-design; information dominated and networked battle command applications;

system-of-systems analyses; human performance modeling; platform maneuverability; and

tactical supercomputers. Discoveries and innovations made in this area will exert a significant

impact on the Army of the future. There are natural synergies among the challenges facing

ARL's NC&CS Competency and ARL's other S&T Competencies. Synergistic advances across

all competencies are expected to enable next generation scientific breakthroughs.

This topic concentrates on understanding and exploiting the fundamental aspects of hardware

and associated software and algorithms for emergent and future computing for mobile, scientific,

and data intensive applications. Primary technical areas within novel HW/SW and algorithmic

co-design include tactical scalable computing, extremely low SWaP (Size, Weight, and Power)

computing, and Next Generation Computing Architectures. Tactical scalable computing focuses

on understanding scalable computing on the tactical network to include Emergent Computing

Architectures cloudlets, vehicle born computing, or ad hoc network connected platforms.

Numerous applications are envisioned for these types of system in the future and include

artificial intelligence aids for decision making, processing large-scale datasets (text, video), and

navigation systems for autonomous vehicles. Emergent Computing Architectures considers new

non-von Neumann and domain specific architectures that may provide leap ahead capabilities for

Army applications. Tactical Computing is at-the-edge computing capabilities to better

understand algorithms that provide applications for use by the soldier and edge devices at the

point of need. Finally, Next Generation Computing Architectures research is focused on

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non-traditional computing systems and envisioned to provide disruptive technologies for the

Army. Cognitive computing, neuro-synaptic computing, and DNA computing are some

emerging concepts.

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Army Research Directorate (ARD) Research Topic

Novel Solid State Lasers and Laser MaterialsTitle:

ARL-BAA-0053Announcement ID:

TPOC: Mark Dubinskiy, PhD - [email protected] - (301) 394-1821

ARL Office: Army Research Directorate (ARD)

Discipline: Materials Science;Physics

ARL Foundational Research Competencies: Energy Sciences

Army Modernization Priorities: Air and Missile Defense;Future Vertical Lift

Keywords: laser, Raman, solid-state, fiber, bulk, crystalline

Description:

The Army is interested in research on innovative gain media, for example laser-quality ceramics

with emphasis on engineerable doping and index profile (e.g., gradient doping, sharp-step

waveguiding structures, planar and circular, with sub-10-micrometer diffusion zone); solid-state

materials for high-gain stimulated Brillouin scattering (SBS); specialty fibers and fiber lasers

suitable for high average powers and power scaling (e.g., fibers with glass compositions having

an ultra-low SBS gain and/or ultra-high Raman gain; low-loss fully crystalline double-clad, i.e.,

crystalline core/crystalline cladding, fibers; glass fiber designs with developed mode selection

mechanisms or self-mode selection; fiber designs with specialty wavelength-selective properties,

e.g., for Raman suppression); advanced laser materials for diode-pumped eyesafe lasers (e.g.,

based on high and ultra-high thermal conductivity hosts, environmentally stable

ultra-low-phonon hosts, or gain materials with exceptionally high emission/absorption

cross-sections).

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Army Research Directorate (ARD) Research Topic

Platform Design and ControlTitle:

ARL-BAA-0065Announcement ID:

TPOC: Asha J. Hall, PhD - [email protected] - (410) 278-2384

ARL Office: Army Research Directorate (ARD)

Discipline: Mechanics

ARL Foundational Research Competencies: Mechanical Sciences

Army Modernization Priorities: Future Vertical Lift

Keywords: Platform Design, Control Algorithms for Platforms, Mobile Platforms

Description:

ARL seeks research proposals in platform design and control that will enable maneuverable,

adaptive tactical mobility platforms for Army ground and air vehicles. Technical challenges

include developing a computational framework for automated design of mechanical systems

(soft/compliant robots and platforms) capable of performing morphological computation.

Furthermore, control paradigms are required for non-linear adaptive structures for which

maneuverability is being maximized. The goal is to address (1) structural adaptations (2)

describing structural and aerodynamic performance in dynamic environments as well as (3)

controlling these highly coupled vehicles.

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Army Research Directorate (ARD) Research Topic

Power ConversionTitle:

ARL-BAA-0055Announcement ID:

TPOC: Wes Wesley Tipton, PhD - [email protected] - (301) 394-5209

ARL Office: Army Research Directorate (ARD)

Discipline: Electronics

ARL Foundational Research Competencies: Energy Sciences

Army Modernization Priorities: Air and Missile Defense;Future Vertical Lift;Next Generation

Combat Vehicle

Keywords: Power conversion, inverter, converter, transformers, platform electrification

Description:

Electrical Power Conversion

The Army is searching for innovative technologies and techniques for reducing the size, weight,

cost, and logistics footprint of power conversion systems across the full range of mobile and

stationary Army applications. High efficiency and high temperature operation (for reduced

cooling) are also critical requirements.

Some specific areas of interest include:

Novel power converter toopologies

Novel materials and designs for high-temperature power conditioning components

including capacitors

inductors, transformers and other passive components

High performance components such as switches, transformers, and capacitors

Novel power conditioning components and control research in technologies for conversion

of power between frequencies and voltages with the ability to scale system power levels

based on needs

Pulse-Forming Network (PFNs) and power conversion technology for lethality,

survivability and directed energy capabilities and future high power and high voltage loads

Thermal management materials and techniques for power switching and conversion

components

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Army Research Directorate (ARD) Research Topic

Power Electronics PackagingTitle:

ARL-BAA-0057Announcement ID:

TPOC: Michael Fish, PhD - [email protected] - (301) 394-3173

ARL Office: Army Research Directorate (ARD)

Discipline: Electronics

ARL Foundational Research Competencies: Energy Sciences

Army Modernization Priorities: Air and Missile Defense;Future Vertical Lift;Next Generation

Combat Vehicle

Keywords:

Description:

This topic has four thrust areas:

High performance packaging materials, methods and systems o enable the full

performance level of wide bandgap power electronics. This includes high temperature (Tj>

200 degrees C), high voltage ( > 10 kV), and high frequency (Mhz range) operation.

Integrated design techniques and modeling that utilize co-engineering and/or co-design to

improve power packaging design by understanding the power density, reliability, thermal

performance, and electrical performance trade-offs.

Novel applications of standard additive manufacturing techniques as well as novel additive

manufacturing techniques are desired to enable advanced and high-performance power

packaging. In addition, techniques and methods to functionalize structural, aerodynamic

and/or other structures by integrating power electronics features are of interest.

Intelligent control methods and techniques for in package control and monitoring of device

performance.

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Army Research Directorate (ARD) Research Topic

Quantum Entanglement Science and Efficient Light-Matter InteractionTitle:

ARL-BAA-0052Announcement ID:

TPOC: Brenda L VanMil - [email protected] - (301) 394-0979

ARL Office: Army Research Directorate (ARD)

Discipline: Materials Science;Physics

ARL Foundational Research Competencies: Photonics, Electronics, and Quantum Sciences

Army Modernization Priorities: Assured PNT;Network/C3I

Keywords: quantum; positioning, navigation, timing (PNT); quantum information science;

atomic clocks; entanglement; quantum sensing;

Description:

Over the past century, the quantum principles of superposition, electronic structure, and

uncertainty relations gave us tremendous advances in a number of applications relevant to the

military, including atomic clocks, magnetometry, positioning/navigation/timing (PNT), and

gravimetry. While these areas can still be improved through technological advances,

next-generation gains in sensing and in secure communications will occur through the concept of

quantum identicality and quantum entanglement.

Our efforts conduct cross-cutting foundational research to exploit quantum effects for (1) novel

sensors and capabilities, (2) beyond-classical sensor performance limits using entanglement, and

(3) entanglement-enhanced information processing, decision-making, and security. Research

emphasizes strong light-matter interfaces, including cavity quantum electrodynamics (QED) and

nanophotonic integration. Examples of relevant research include electromagnetic field sensing

using Rydberg atoms, solid-state "atomic" clocks, solid-state defects for sensing and quantum

information, nanophotonics, and building blocks of entanglement distribution (quantum

memories, repeaters, hybrid interfaces, etc).

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Army Research Directorate (ARD) Research Topic

Quantum Information Science and Positioning, Navigation, and Timing (QIS-PNT)Title:

ARL-BAA-0051Announcement ID:

TPOC: Adam Schofield, PhD - [email protected] - (443) 395-0621

ARL Office: Army Research Directorate (ARD)

Discipline: Materials Science;Mechanics;Physics

ARL Foundational Research Competencies: Electromagnetic Spectrum Sciences;Photonics,

Electronics, and Quantum Sciences

Army Modernization Priorities: Assured PNT

Keywords: positioning, navigation, and timing (PNT); quantum information science; quantum

sensing

Description:

The Quantum Information Science and Positioning, Navigation, and Timing (QIS-PNT)

Essential Research Program (ERP) is the Army's leader in continuously transforming quantum

information science and PNT to outpace our adversaries through discovery and innovation of

novel sensing capabilities and quantum approaches to ensure seamless navigation and

communication across all combat environments.

Mission

provide the expertise and component technologies to foster transformational improvements to the

accuracy and resiliency of Army PNT and quantum sensing capabilities that improve the

maneuver, FIRES, and communication capabilities of the future force.

Goals and Objectives

Provide a suite of PNT technologies that can be tailored and fused to improve the Army's

ability to meet diverse platform/system/mission requirements

Improve availability and precision synchronization of time beyond current GPS time

transfer capabilities

Provide improved resilience of position information at GPS-level accuracy and

precision greater than GPS

Improve access to and integrity of navigation and communications information

Identify, develop, and evaluate quantum mechanical principles and quantum phenomena to

support revolutionary advances in sensing capabilities, including clocks, sensing, and

communications

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Army Research Directorate (ARD) Research Topic

Quantum networking for communications, distributed entanglement and informationTitle:

processing

ARL-BAA-0082Announcement ID:

TPOC: Quantum Networking Team - [email protected]

ARL Office: Army Research Directorate (ARD)

Discipline: Computer Science;Network Science

ARL Foundational Research Competencies: Network, Cyber, and Computational Sciences

Army Modernization Priorities: Network/C3I

Keywords: Quantum optics, quantum information distribution, trapped ion quantum

information, quantum entanglement distribution, quantum networking experiment/theory

Description:

The Army seeks proposals in the development of quantum networks to advance performance

metrics across a range of applications, including information distribution/security/processing,

logistics, conventional networking and computing.

Technical areas of interest include experimental and theoretical work in the following topics:

Quantum network connectivity, including methods for preservation and characterization of

quantum signals, including polarization preservation, frequency-control and timing

distribution for network control.

Development of quantum-based networking models involving quantum information

distribution, processing, error-correction and protocols for state characterization and

tomography.

Strong light-matter interfaces including nanophotonic light manipulation and quantum

frequency conversion.

Trapped ion quantum networking, including photon-mediated entanglement-based

networking.

Quantum networking technologies for quantum nodes, quantum information generation,

routing, detection, measurement and control.

Entanglement-enhanced information processing, decision-making, and data security.

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Army Research Directorate (ARD) Research Topic

Reactive Chemical SystemsTitle:

ARL-BAA-0067Announcement ID:

TPOC: James F. Berry (acting) - [email protected] - (410) 278-1519

ARL Office: Army Research Directorate (ARD)

Discipline: Chemistry;Materials Science

ARL Foundational Research Competencies: Energy Sciences;Sciences of Extreme

Materials;Terminal Effects;Weapons Sciences

Army Modernization Priorities: Soldier Lethality

Keywords: responsive assemblies; surface science; catalysis; nanostructured materials

Description:

The goal of the Reactive Chemical Systems Program is to achieve a molecular level

understanding of surface/interfacial activity and dynamic nanostructured chemical systems to

provide leap-ahead advancements in Army relevant materials for the benefit of the Soldier. This

program supports basic research in the areas of surfaces, catalysis, interfaces, coatings, and novel

and stimuli-responsive chemical systems.

This program is divided into three areas: (i) Nanostructure Surface Interactions and Reactivity,

(ii) Development of Per- and Polyfluoroalkyl Substances (PFAS) Alternatives, and (iii) Synthetic

Molecular Systems.

Nanostructure Surface Interactions and Reactivity

This thrust seeks to understand the kinetics and mechanisms of reactions occurring at surfaces

and interfaces, as well as the development of new methods to achieve precise control over the

structure and function of chemical and biological molecules on surfaces. Areas of interest

include adsorption, desorption, the catalytic and reactive processes occurring on surfaces and at

interfaces, and the interfacial activity/reactivity between dissimilar materials to enhance systemic

response to external stimuli. A topic of particular interest is the use of confinement of chemical

species within a system to influence parameters of reactivity. Breakdown of both reactive

(hazardous) and long-lived (stable) chemical species is relevant to this area. Also,

characterization and novel methods to control how surfaces and interfaces of disparate materials

respond to and/or degrade under extreme conditions are of interest. To achieve greater

understanding of the phenomena that govern these interactions, rapid, in-situ characterization of

material changes in extreme conditions is also covered.

Development of Per- and Polyfluoroalkyl Substances (PFAS) Alternatives

Development of robust alternatives to per- and polyfluoroalkyl substances (PFAS), including

coatings/materials that provide performance equal or greater than these fluorine-containing

systems, without the associated hazards, are covered in this area. Investigation of chemical

surfaces and novel materials that enable superior thermal stability, hydrophobicity,

oleophobicity, low surface tension, and low coefficients of friction are of interest. Basic research

efforts for the development of the chemistry that enables these coatings to adhere to various form

factors are of interest, in particular for their use in environmental extremes. Another area of

interest is the exploration of the chemical space that imparts flammability mitigation, especially

for high temperature applications.

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Synthetic Molecular Systems

This topic supports research that imparts multifunctionality, stimuli-responsive and dynamic

behavior to synthetic molecular and chemical systems. Research of interest includes design and

development of nanostructured scaffolds and sequential catalytic systems. Research aimed at

exploring the properties and capabilities of porous supramolecular structures, including their

functionality, and the downstream capabilities that can be integrated into the system, is also a

priority. A specific technical area of interest is "targeting and triggering" in which a specific

chemical (or event) is targeted (recognized) and that recognition triggers a response. Important

technical challenges include selective and reversible recognition, amplification, and

multi-responsive systems in which specific stimuli trigger distinct responses including shape

and/or color change, subsequent generation of chemical species, and unmasking of catalytic

functionalities are also relevant.

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Army Research Directorate (ARD) Research Topic

RF Sensing Through Obscured MediaTitle:

ARL-BAA-0080Announcement ID:

TPOC: Brian Phelan, PhD - [email protected] - (301) 518-0713

ARL Office: Army Research Directorate (ARD)

Discipline: Electronics

ARL Foundational Research Competencies: Electromagnetic Spectrum Sciences

Army Modernization Priorities:

Keywords:

Description:

ARL seeks to discover, innovate, and experimentally demonstrate adaptable, low-SWAP (SWAP

= Size, Weight, and Power) transceivers, adaptable RF front-end concepts, algorithms, and

enabling technologies that will provide new capabilities in standoff explosive threat sensing

across the electromagnetic spectrum. Explosive threats are often obscured; sensor technologies

need to be able to detect explosive threats in such situations. The sensor technologies should be

configurable to operate on mobile platforms (ground-vehicle, and airborne platforms) for field

evaluations and subsequent data collections. Novel techniques, such as distributed-radar

concepts are of interest due to their potential to enable Low-Probability of Detection (LPD)

operation. Furthermore, the sensor technologies should be able to perform standoff detection in

congested, contested, and complex Electromagnetic Environments (EME) by implementing

cognitive radar concepts. Due to continued congestion of the RF spectrum, decision-theory

approaches and other adaptive, flexible, and reconfigurable algorithms and associated hardware

as needed. Spatial, spectral, and temporal domains need to be leveraged to sense, react, and

avoid. Active and passive RF sensing should be employed for targeting, detecting, and tracking

airborne and ground-based threats.

Topics of interest include:

Explosive Hazards

Explosive Hazards Triggering Devices

Transceivers for Passive & Active Capabilities

Digital Backends

Adaptative/Reconfigurable Frontends

Integration of Transceivers on Ground- and Airborne Platforms

Ground-to-Air Tracking Radar

Ground-Surveillance Radar

Multistatic Radar vs. Signal Processing

Multifunction Radar

Synthetic-Aperture Radar

Distributed Radar

Waveform Design & Agility

Passive Imaging

Decision Theory

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Spectrum Situational Awareness (SSA)

Dynamic Spectrum Access (DSA)

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Army Research Directorate (ARD) Research Topic

RF-to-THz Devices and Integrated Circuit TechnologyTitle:

ARL-BAA-0063Announcement ID:

TPOC: Dmitry A. Ruzmetov, PhD - [email protected] - (301) 394-0242

ARL Office: Army Research Directorate (ARD)

Discipline: Electronics;Materials Science;Physics

ARL Foundational Research Competencies: Electromagnetic Spectrum Sciences

Army Modernization Priorities: Air and Missile Defense;Long Range Precision Fires

Keywords: RF, UWB, diamond

Description:

ARL is interested in research on innovative electronic substrates, epitaxial materials, devices,

monolithic circuits, and integration techniques for digital, mixed-signal, RF, millimeter-wave to

Terahertz (THz) applications, including radar, communications, electronic warfare, and sensor

systems. Research should involve materials, devices, integrated circuits, and subsystems built

upon advanced Si-based, III-V, III-nitride, and II-VI materials, ultra-wide bandgap

semiconductors (i.e. diamond), novel device structures, nano-technology innovative circuit

topology, and multi-level, and/or heterogeneous integration technology. The research may also

include related device, circuit, subsystem, and system level CAD modeling and analysis to

achieve optimal performance.

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Army Research Directorate (ARD) Research Topic

Super-Materials Research in support of the Sciences of Extreme Materials CompetencyTitle:

ARL-BAA-0081Announcement ID:

TPOC: Victoria L. Blair, PhD - [email protected] - (410) 306-4947

ARL Office: Army Research Directorate (ARD)

Discipline: Chemistry;Data Sciences and Informatics;Materials Science;Mechanics;Physics

ARL Foundational Research Competencies: Sciences of Extreme Materials

Army Modernization Priorities:

Keywords:

Description:

This program focuses on basic and applied research investigations of materials synthesis,

processing and characterization of structural materials which perform in high temperature, highly

dynamic chemical, mechanical, and thermal environments. An example extreme environment for

this topic would be transient thermal loads, high-g loading, oxidizing environments, and

corrosive gases. Research efforts that are supported by both experimental and computational

efforts are encouraged. Structural materials of interest can include, carbon-fiber reinforced

composites, silicon carbide fiber reinforced composites, ultra-high temperature ceramics (with

and without fiber reinforcement), refractory metals, metal matrix and ceramic matrix composites.

Machine learning-driven materials discovery may be used to accelerate research progress but

must be supported with experimental methods.

Examples of research topics:

Fundamental discovery of crack propagation and failure mechanisms of materials in a

computer-simulated use-environment or experimental environment.

Processing relationship with materials properties and characteristics of interest including

strength, hardness and toughness at temperatures exceeding 1000 degrees C. Thermal

properties like thermal expansion, conductivity and emissivity.

Development of high temperature material evaluation methods and linkages back to

process-property relationships of exemplar materials.

Mechanisms and characteristics of dissimilar material joints and interfaces.

Examinations of novel processing methods to improve interfacial strength and

performance.

Examining multi-functionality, whereby an additional attribute beyond structural

performance is optimized, such as high strength, thermal shock resistant materials that is

also transparent to specific wavelengths of light.

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Army Research Directorate (ARD) Research Topic

Support to ARL Foundation Research CompetenciesTitle:

ARL-BAA-0071Announcement ID: