ERI Funding Opportunities

DEVCOM-ARL

Solicitation Number: ARL-BAA-0037

https://cftste.experience.crmforce.mil/arlext/s/baadatabaseentry/a3Ft0000002Y39NEAS/opt0037

Posted Date: November 20, 2022

Due Date: November 19, 2027

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.

DEVCOM-ARL

Solicitation Number: ARL-BAA-0099

https://cftste.experience.crmforce.mil/arlext/s/baadatabaseentry/a3F830000003XqvEAE/opt0099

Posted Date: May 9, 2024

Due Date: November 19, 2027

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.

DEVCOM-ARL

Solicitation Number: ARL-BAA-0100

https://cftste.experience.crmforce.mil/arlext/s/baadatabaseentry/a3F830000003Xr0EAE/opt0100

Posted Date: May 9, 2024

Due Date: November 19, 2027

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.

DEVCOM-ARL

Solicitation Number: ARL-BAA-0119

https://cftste.experience.crmforce.mil/arlext/s/baadatabaseentry/a3FRw00000005yzMAA/opt0119

Posted Date: May 13, 2025

Due Date: November 19, 2027

This program seeks fundamental research into advanced energy materials that can transform power and energy technologies. Within the program, three research thrusts aim to discover and extend the mechanisms by which matter, at an atomic through mesoscopic scale, may be manipulated to exhibit emergent behavior relevant to energy conversion and storage. Research topics of interest include:

Entropically-Stabilized Catalytic Materials

Theoretical and experimental investigations into the rational design of nanostructured and defect-engineered materials where configurational or vibrational entropy plays a defining role in phase stability and catalytic activity. Emphasis is placed on systems that demonstrate cooperative charge and mass transport phenomena such as triple-conducting oxides.

Redox-Responsive Electrode Materials for Multivalent Energy Storage

Exploration of electrochemical systems that utilize multi-electron cationic or anionic redox couples. Research should focus on the underlying mechanisms that govern the nucleation, growth, and reversibility of metallic phases under high-energy deposition conditions, intercalation phenomena, or other energy storage mechanisms enabling next-generation battery chemistries based on multivalent ion systems.

Coupled Atomic-Nuclear Energy Systems

Fundamental investigations into mechanisms that enable external control of nuclear state populations via atomic-scale interactions, such as mapping electromagnetic cascades linking metastable and ground states, initiating switching via mechanisms such as nuclear excitation by electron capture (NEEC) or alternate photon/particle interactions, refining isomer-production reactions, or solid-state/beam-based platforms to convert the liberated energy into practical power.