Opportunity Information: Apply for W911NF 21 S 0013
High-Throughput Materials Discovery for Extreme Conditions (HTMDEC) is a U.S. Army DEVCOM Army Research Laboratory (DEVCOM-ARL) funding opportunity focused on dramatically speeding up the discovery and development of new materials that can survive and perform in harsh, defense-relevant environments. The program is built around the idea that future Army armor and weapon systems will depend on materials that can handle extreme conditions such as high-strain-rate deformation and shock, very high acceleration (high-g) loading, intense heat, rapid ablation (including hypersonic flight regimes), and high-velocity impact (terminal ballistics). Because the design space for next-generation materials is enormous (potentially billions of candidate compositions, microstructures, and processing pathways), DEVCOM-ARL is pushing a data-driven approach that combines high-throughput experimentation and computation with artificial intelligence and machine learning to close the loop from design to testing to learning and back again.
At its core, HTMDEC is trying to move materials science away from slow, one-off experiments and toward an integrated discovery pipeline where synthesis, processing, characterization, and modeling are all scaled up and connected through robust data infrastructure. DEVCOM-ARL highlights that AI and ML can help at multiple points in this pipeline: selecting promising candidate materials, guiding experiments, extracting more information from tractable tests, bridging length and time scales, and ultimately revealing relationships between processing, structure, properties, and real system performance that might be missed by conventional approaches. A major theme is that ML for this space cannot rely solely on repurposed big-data tools (like generic image recognition methods). Instead, the Army is explicitly signaling interest in physics-informed ML and ML-augmented physics-based models that better reflect how materials actually behave under shocks, heating, localized deformation, damage, and failure, while still running fast enough to support high-throughput screening and even autonomous experimentation.
The technical scope is organized into four main thrust areas. First is Data-driven Material Design, a broad umbrella for computational and data-centric approaches that accelerate the early design phase of materials development. Second is High-Throughput Synthesis and Processing, including both adapting existing fabrication and processing approaches for rapid screening and inventing new methods that can produce many variants efficiently; this also includes interest in additive manufacturing and processing routes that create spatially varying compositions, anisotropy, and multi-material interfaces, even though those features expand the parameter space significantly. Third is High-Throughput Characterization, emphasizing automation as well as the creation of surrogate or proxy tests for extreme, transient events (like true high-strain-rate tests) that are difficult to automate directly. Fourth is ML-augmented Physics-Based Models, where the program encourages tighter integration of mechanistic modeling with ML so that predictions remain grounded in physical reality while enabling rapid evaluation across large candidate spaces.
HTMDEC is also notable for how it is structured and managed. It is run as a two-step application process: a White Paper stage followed by an invitation-only Full Proposal stage. Only applicants whose white papers are selected and invited by the Government are eligible to submit full proposals. Awards are planned as cooperative agreements (not standard grants), which typically implies a more collaborative relationship with the Government during performance. The program is executed in two funding phases: initial "Seedling awards" and longer-term "Centers." A Center is described as an option period that can be exercised from a Seedling award for up to four additional years. Seedlings generally focus on a single thrust area (or a targeted thrust area that can change by year based on Army needs), while the Center phase is expected to cover all four thrust areas, encouraging teams to collaborate, merge efforts, and build a more comprehensive, integrated capability. The program also anticipates annual project review workshops where recipients present results and interact with other funded teams, reinforcing the program's emphasis on an ecosystem approach rather than isolated projects. In addition, there is an opportunity for a Graduate Student Fellowship effort for U.S. citizens working within one of the thrust areas as part of the Center option proposal approach.
A special exception is called out for a targeted thrust area focused on Data Handling and Management (identified in the text as FY2022-2). Unlike other Seedlings that may transition into Centers, the Seedling selected for this data platform role is intended to continue as a recurring Seedling for the full duration of the HTMDEC program and to support all Centers as the approved data platform. That detail signals how central the Army views data standardization, trusted exchange, and infrastructure to making high-throughput and ML-driven discovery actually work across multiple collaborating organizations.
From an administrative standpoint, the opportunity is issued by the Department of the Army, Materiel Command, under Funding Opportunity Number W911NF-21-S-0013, categorized under Science and Technology and other Research and Development, with CFDA number 12.630. The funding instrument type is a cooperative agreement, and the listed award ceiling is $2,500,000. Eligible applicants include U.S.-based institutions of higher education, nonprofit organizations, and for-profit organizations (including both small and large businesses) located in the United States or its territories, and this eligibility applies to all entities performing substantive work on the proposal (for example, the primary recipient and key partners).
The timeline and submission mechanics in the posting emphasize changing dates across versions, so applicants were expected to pay close attention to amendments. The final deadline for full proposals was 12 November 2021, and only invited applicants could submit at that stage. The FOA was amended on 23 August 2021, including a revised white paper submission date of 10 September 2021. Earlier versions referenced a white paper deadline of 31 August 2021 at 3:00 PM local time in North Carolina, reflecting that the schedule evolved as the announcement matured from pre-release to official FOA. White papers were required to be submitted via email (not through a typical portal) to both usarmy.rtp.devcom-arl.mbx.baa3qa@mail.mil and usarmy.rtp.devcom-arl.mbx.baa3qa@army.mil. The Army also hosted an Applicant's Day presentation on 29 July 2021 and maintained program information online, underscoring that HTMDEC is intended to be a coordinated, community-engaged effort with shared direction and common goals.
In practical terms, HTMDEC is best read as a push for an end-to-end, scalable discovery engine for extreme-condition materials: generate large, high-quality datasets through high-throughput synthesis and testing; connect them to credible models of transient, high-rate, high-temperature behavior; use physics-informed ML to learn efficiently from limited but information-rich experiments; and build a collaborative data backbone that allows different teams to contribute and benefit. The expected outcome is not just improved tools and workflows, but proof-of-concept demonstrations and ultimately novel materials with unprecedented performance that DEVCOM-ARL can take forward for further analysis, validation, and defense-relevant testing.Apply for W911NF 21 S 0013
- The Dept of the Army -- Materiel Command in the science and technology and other research and development sector is offering a public funding opportunity titled "High-Throughput Materials Discovery for Extreme Conditions (HTMDEC)" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 12.630.
- This funding opportunity was created on 2021-05-14.
- Applicants must submit their applications by 2021-11-12. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- Each selected applicant is eligible to receive up to $2,500,000.00 in funding.
- Eligible applicants include: Others.
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FAQs: High-Throughput Materials Discovery for Extreme Conditions (HTMDEC)
1) What is the HTMDEC funding opportunity?
High-Throughput Materials Discovery for Extreme Conditions (HTMDEC) is a U.S. Army DEVCOM Army Research Laboratory (DEVCOM-ARL) funding opportunity aimed at dramatically accelerating the discovery and development of new materials for harsh, defense-relevant environments. The program emphasizes an integrated, data-driven discovery pipeline that connects materials design, synthesis/processing, characterization, and modeling, with strong use of artificial intelligence (AI) and machine learning (ML).
2) Which Army organization is sponsoring HTMDEC?
The opportunity is sponsored by the U.S. Army DEVCOM Army Research Laboratory (DEVCOM-ARL) and issued by the Department of the Army, Materiel Command.
3) What kinds of extreme conditions are in scope for HTMDEC?
The program targets materials that can survive and perform under conditions such as high-strain-rate deformation and shock, very high acceleration (high-g) loading, intense heat, rapid ablation (including hypersonic flight regimes), and high-velocity impact (terminal ballistics).
4) What is the main technical goal of HTMDEC?
The goal is to move materials research away from slow, one-off experimentation and toward a scalable, high-throughput discovery engine. This includes generating large, high-quality datasets; linking data to credible models for transient, high-rate, high-temperature behavior; using physics-informed ML to learn efficiently; and building a shared data backbone so multiple teams can collaborate and reuse results.
5) Why does the Army emphasize AI/ML in this program?
DEVCOM-ARL highlights that the design space for next-generation materials can be enormous (potentially billions of candidate compositions, microstructures, and processing pathways). AI/ML is positioned as a way to help select promising candidates, guide experiments, extract more information from tractable tests, bridge length/time scales, and learn relationships between processing, structure, properties, and system performance that conventional approaches may miss.
6) Does HTMDEC prefer any specific style of ML?
Yes. The program explicitly signals interest in physics-informed ML and ML-augmented physics-based models, rather than relying only on generic big-data approaches (for example, repurposed image recognition methods). The emphasis is on predictions that remain grounded in physical behavior under shock, heating, localized deformation, damage, and failure, while still running fast enough for high-throughput screening and potentially autonomous experimentation.
7) What are the four main thrust areas of HTMDEC?
The technical scope is organized into four thrust areas:
- Data-driven Material Design (computational and data-centric methods to accelerate early materials design)
- High-Throughput Synthesis and Processing (rapid fabrication/processing methods for screening many variants, including interest in additive manufacturing and complex processing routes)
- High-Throughput Characterization (automation and surrogate/proxy tests for extreme transient events that are hard to automate directly)
- ML-augmented Physics-Based Models (integrating mechanistic models with ML to keep predictions physically grounded and fast to evaluate at scale)
8) How does additive manufacturing fit into HTMDEC?
Additive manufacturing is included within the High-Throughput Synthesis and Processing thrust. The program notes interest in processing routes that create spatially varying compositions, anisotropy, and multi-material interfaces, even though those features expand the parameter space.
9) What does "high-throughput characterization" mean in this context?
It refers to scaling up materials measurement and evaluation through automation, and also developing surrogate or proxy tests for extreme, transient events (like true high-strain-rate tests) that are difficult to automate directly. The intent is to enable rapid learning loops despite practical testing constraints.
10) What type of award does HTMDEC plan to make?
Planned awards are cooperative agreements, not standard grants. This typically implies a more collaborative relationship with the Government during performance.
11) What is the application process for HTMDEC?
HTMDEC uses a two-step process: (1) a White Paper stage, followed by (2) an invitation-only Full Proposal stage.
12) Can anyone submit a full proposal?
No. Only applicants whose white papers are selected and who are invited by the Government are eligible to submit full proposals.
13) How is the program structured over time (Seedlings vs. Centers)?
The program is executed in two funding phases:
- Seedling awards (initial efforts, generally focused on a single thrust area or a targeted thrust area that may change by year based on Army needs)
- Centers (a longer-term option period that can be exercised from a Seedling award for up to four additional years; Centers are expected to cover all four thrust areas and promote collaboration/merging across teams)
14) What is expected of a Center compared to a Seedling?
Seedlings generally focus on one thrust area (or a targeted thrust area). The Center phase is expected to cover all four thrust areas and to encourage teams to collaborate and build a comprehensive, integrated capability spanning design, synthesis/processing, characterization, and ML-augmented modeling.
15) Are there program-wide meetings or reviews?
Yes. The program anticipates annual project review workshops where recipients present results and interact with other funded teams, reinforcing an ecosystem approach rather than isolated projects.
16) Is there a graduate student fellowship component?
There is an opportunity for a Graduate Student Fellowship effort for U.S. citizens working within one of the thrust areas as part of the Center option proposal approach.
17) What is the targeted Data Handling and Management exception (FY2022-2)?
The FOA calls out a special targeted thrust area focused on Data Handling and Management (identified as FY2022-2). Unlike other Seedlings that may transition into Centers, the Seedling selected for this data platform role is intended to continue as a recurring Seedling for the full duration of HTMDEC and to support all Centers as the approved data platform.
18) Why is data handling and management treated as a special case?
The posting emphasizes the central importance of data standardization, trusted exchange, and shared infrastructure to make high-throughput and ML-driven discovery work across multiple collaborating organizations and Centers.
19) What is the Funding Opportunity Number and CFDA number?
The Funding Opportunity Number is W911NF-21-S-0013. The CFDA number listed is 12.630.
20) What category of funding does this opportunity fall under?
The opportunity is categorized under Science and Technology and other Research and Development.
21) What is the award ceiling listed for HTMDEC?
The listed award ceiling is $2,500,000.
22) Who is eligible to apply?
Eligible applicants include U.S.-based institutions of higher education, nonprofit organizations, and for-profit organizations (including both small and large businesses) located in the United States or its territories.
23) Does eligibility apply only to the prime applicant?
No. The eligibility requirement applies to all entities performing substantive work on the proposal, including the primary recipient and key partners.
24) How were white papers submitted?
White papers were required to be submitted via email (not through a typical portal) to both of the following addresses:
- usarmy.rtp.devcom-arl.mbx.baa3qa@mail.mil
- usarmy.rtp.devcom-arl.mbx.baa3qa@army.mil
25) What were the key dates mentioned for submissions?
The FOA notes that dates changed across versions and applicants were expected to pay close attention to amendments. The FOA was amended on 23 August 2021, including a revised white paper submission date of 10 September 2021. Earlier versions referenced a white paper deadline of 31 August 2021 at 3:00 PM local time in North Carolina. The final deadline for full proposals was 12 November 2021, and only invited applicants could submit at that stage.
26) Was there an informational event for applicants?
Yes. The Army hosted an Applicant's Day presentation on 29 July 2021 and maintained program information online, supporting a community-engaged and coordinated program approach.
27) What outcomes is HTMDEC trying to produce?
HTMDEC aims to deliver more than improved tools and workflows. The described outcomes include proof-of-concept demonstrations and ultimately novel materials with unprecedented performance that DEVCOM-ARL can take forward for further analysis, validation, and defense-relevant testing.
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