Funding Opportunities - Advanced Manufacturing

Sponsor Title Amount Deadline Notes
DOD Army Research Office Broad Agency Announcement for Fundamental Research   Whitepaper strongly encouraged     Open till 3/31/2022 ARL’s strategy is based on seven Science and Technology (S&T) Competencies: Ballistic Sciences, Computational Sciences, Human Sciences, Materials & Manufacturing Sciences, Network & Information Sciences, Propulsion Sciences, and Protection Sciences.
DOD Army Research Laboratory Broad Agency Announcement for Basic and Applied Scientific Research   Open till 3/31/2022 W911NF-17-S-0003
The ARL BAA identifies topics of interest to the ARL Directorates (Computational and 
Information Sciences Directorate, Human Research and Engineering Directorate, Sensors and Electron Devices Directorate, Survivability/Lethality Analysis Directorate, Vehicle and Technology Directorate, and Weapons and Materials Research Directorate) and to the Army Artificial Intelligence Task Force. The Directorates focus on executing in-house research programs, with a significant emphasis on collaborative research with other organizations in an Open Campus setting. 
DOD Air Force Office of Scientific Research (AFOSR) Broad Agency Announcement   Open until superseded FA9550-21-S-0001
Our focus is on research areas that offer significant and comprehensive benefits to our national warfighting and peacekeeping capabilities. These areas are organized and managed in two scientific branches, each with two teams:
NSF Advanced Manufacturing (AM)     The AM program accelerates advances in manufacturing technologies with emphasis on multidisciplinary research that fundamentally alters and transforms manufacturing capabilities, methods and practices. Advanced manufacturing research proposals should address issues related to national prosperity and security, and advancing knowledge to sustain global leadership.
DOD Science &Technology for Advanced Manufacturing Projects (STAMP)   10/30/2021 The focus of this BAA is primarily on projects that continue to advance the systems engineering approach needed for the design, fabrication, and manufacture of structural components to address challenges in system weight, performance, affordability, and/or survivability. The foundation of this approach should include the integration of materials information, captured in computational tools, with engineering product performance analysis and manufacturing-process simulation termed commonly as Integrated Computational Materials Engineering (ICME).
NSF Engineering Design and System Engineering (EDSE)     Of particular interest is research on the design of engineering material systems that leverages the unique aspects of a particular material system to realize advanced design methods that are driven by performance metrics and incorporate processing/manufacturing considerations.
NSF Particulate and Multiphase Processes     Major research areas of interest in the program include: Multiphase flow phenomena, Particle science and technology, Multiphase transport in biological systems and Interfacial transport.
NSF Engineering for Civil Infrastructure (ECI)     The ECI program focuses on geomaterials and geostructures, structural materials (metallic, polymeric, cementitious, glass, composites, etc.), structural and non-structural systems, and building envelopes. Principal Investigators are encouraged to consider physical civil infrastructure subjected to and interacting with the natural environment during construction; under normal service conditions; and under severe loading and environmental conditions.
NSF Mechanics of Materials and Structures (MOMS)     The MOMS program supports fundamental research in mechanics as related to the behavior of deformable solid materials and structures under internal and external actions. Proposals that explore and build upon advanced computing techniques and tools to enable major advances in mechanics are particularly welcome. 
NSF Operations Engineering (OE)     The OE program supports fundamental research on advanced analytical methods for improving operations in complex decision-driven environments. The OE program particularly values cross-disciplinary proposals that leverage application-specific expertise with strong quantitative analysis in a decision-making context.  


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