Project Grant 2328678
- This Project Grant award from the National Science Foundation (NSF), under the Engineering program (CFDA 47.041), provides $649,345 to Carnegie Mellon University to investigate an innovative power field control strategy to achieve prescribed thermal histories throughout parts produced via powder bed fusion additive manufacturing. The research aims to enable the design of novel processing pathways to tailor material properties, fully utilizing the processing capabilities of open-architecture...
- The National Science Foundation awarded a $526,334 Project Grant to the University of Pittsburgh through the Engineering program (CFDA 47.041) to support research titled "CAREER: UNRAVELING FUNDAMENTAL MECHANISMS GOVERNING GRAIN REFINEMENT IN COMPLEX CONCENTRATED ALLOYS MADE BY ADDITIVE MANUFACTURING TOWARDS STRONG AND DUCTILE STRUCTURES." The five-year award, effective April 15, 2021 through March 31, 2026, will fund research investigating fundamental mechanisms governing...
- This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) supports a collaborative research project focused on developing intelligent scan sequence generation to reduce local overheating, distortion, and residual stress in laser powder bed fusion (LPBF) additive manufacturing. The $250,000 award, spanning January 1, 2025 to December 31, 2027, will enable researchers at the University of Pittsburgh to mathematically, numerically, and experimentally...
- This National Science Foundation (NSF) Designing Materials to Revolutionize and Engineer our Future (DMREF) Project Grant award, valued at $150,000 and running from October 1, 2023 to September 30, 2027, supports collaborative research to develop simulation-informed models for additive manufacturing of amorphous metals. The research team at The Washington University aims to derive meaningful measures of material structure from electron nanodiffraction and simulation data, and build predictive...
- The $148,060 Project Grant from the National Science Foundation's Division of Civil, Mechanical, and Manufacturing Innovation under the Engineering program (CFDA 47.041) will fund research at Carnegie Mellon University investigating machine learning approaches to support engineering designers in digital manufacturing. The university will mine part designs from open online repositories and curated datasets developed through in-class challenges. A machine learning pipeline will extract design...
- The National Science Foundation (NSF) Engineering program (CFDA 47.041) awarded a $300,001 Project Grant to the University of Southern California (USC) for the project "COLLABORATIVE RESEARCH: PROCESS-INFORMED LATENT SPACE REPRESENTATION, LEARNING, AND MONITORING FOR SMART PERSONALIZED MANUFACTURING." This 3-year award, effective June 1, 2024, will develop novel methodologies to enable process monitoring and geometric quality control for personalized manufacturing of one-of-a-kind...
- This National Science Foundation (NSF) Engineering Program (CFDA 47.041) Project Grant, awarded to the Regents of the University of Michigan, supports a $496,138 collaborative research effort to develop an approach for optimally determining laser scan sequences in laser powder bed fusion (LPBF) additive manufacturing. The goal is to create knowledge that enables 3D printing of complex metallic parts with fewer failed or defective prints, thereby improving the economic viability of LPBF. The...
- This National Science Foundation (NSF) Project Grant award, under the NSF Engineering program (CFDA 47.041), provides $475,399 to Auburn University to conduct fundamental research on laser nanoparticle powder-bed fusion, an additive nanomanufacturing process. The research aims to develop layer-by-layer fabrication of micro- and nano-scale functional structures and devices with tunable chemical compositions, interface interactions, and physical architectures. This work has potential...
- This National Science Foundation Project Grant of $436,084 supports research at Carnegie Mellon University from May 2022 through April 2025 under the Mathematical and Physical Sciences program (CFDA 47.049). The award will fund the development of novel methods to control interactions between polymer and nanomaterial constituents in polymer nanocomposites. Specifically, the grantee will synthesize brush particle model systems and characterize the structure evolution of liquid-crystal phase...
- The Pennsylvania State University received a five-year, $556,586 Project Grant award from the National Science Foundation Division of Civil, Mechanical, and Manufacturing Innovation. The award funds a research project titled "CAREER: Consideration of Manufacturability in Early Stage Design for Additive Manufacturing" under the NSF Engineering program (CFDA #47.041). The project aims to develop new design methodologies and tools to incorporate manufacturability considerations earlier in...
This National Science Foundation (NSF) Project Grant award, under the Engineering program (CFDA 47.041), provides $650,000 in funding to Carnegie Mellon University (CMU) from June 1, 2024 to May 31, 2027. The project aims to fully understand the mechanisms controlling shape distortion in additive manufacturing (AM) processes, particularly during the sintering of nano/microparticles. The research involves integrated experimental and theoretical work to identify critical AM process parameters that can either eliminate distortions or control them to enable "4D printing" techniques. The project will also involve collaboration with K-12 students from disadvantaged schools and develop interdisciplinary curricula to train a diverse U.S. workforce in advanced manufacturing, computational sciences, and nanomaterials. As part of the project, CMU is collaborating with Washington State University (WSU) on a sub-award. WSU's tasks include developing a mesoscale phase-field model to discover the physical mechanisms of long-range mass transport in non-homogeneous sintering, as well as creating a macroscale continuum model to simulate full-scale parts and predict shape distortion and residual stresses for industrially relevant configurations. The research outcomes have the potential to reduce the cost of AM parts, positively impacting industries such as aviation, automotive, and nuclear.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $650.0k | 3/18/24 |
GrantNumber | Description | Subgrantee | Prime Award | Dollars Obligated | Updated At |
|---|---|---|---|---|---|
1127320485108S | Washington State University | Project Grant 2328678 | $317.5k | 6/28/24 |