This $335,707 federal Project Grant award from the National Science Foundation's Mathematical and Physical Sciences (CFDA 47.049) program supports collaborative research at the University of California, Davis (UC Davis) to investigate the dynamics of short-range order in multi-principal element alloys. The project will leverage artificial intelligence techniques to analyze atom probe tomography data and develop a mathematical model for the evolution of short-range ordering in these advanced...
This $524,534 Project Grant award from the National Science Foundation (NSF) Division of Materials Research funds a collaborative research effort between The Johns Hopkins University and the University of California, Santa Barbara to elucidate high temperature deformation mechanisms in refractory multi-principal-element alloys. The research aims to develop a fundamental scientific understanding of the ultrahigh temperature (up to 1500°C) mechanical behavior of this new class of alloy...
The National Science Foundation (NSF) Division of Materials Research awarded a $482,041 Project Grant to the University of California, Santa Barbara (UCSB) under the Mathematical and Physical Sciences program (CFDA 47.049) to conduct collaborative research on elucidating high-temperature deformation mechanisms in refractory multi-principal-element alloys. The research aims to develop a fundamental scientific understanding of the ultrahigh temperature deformation behavior of this new class of...
This Project Grant award, provided by the National Science Foundation (NSF) under the Mathematical and Physical Sciences program (CFDA 47.049), aims to revolutionize the creation of novel engineering alloys by focusing on the relationship between the production process and the resulting material microstructure. The $459,000 award, granted on April 15, 2025, will enable a research team at The Johns Hopkins University to develop a data-driven platform called DRAGONS (Data-Driven Recursive...
This Project Grant award from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) provides $425,943 to Arizona State University to develop an AI-enabled automated workflow for designing ultrastrong and ultraelastic metallic alloys. The research team aims to leverage artificial intelligence, computational modeling, and experimental tools to rapidly design, synthesize, and test these complex concentrated alloys. The innovative strategies developed through...
The National Science Foundation (NSF) awarded a $75,000 Project Grant under the Engineering (CFDA 47.041) program to the University of California, Santa Barbara (UCSB) to support a collaborative research project titled "DMREF: Data-Driven Discovery of the Processing Genome for Heterogeneous Superalloy Microstructures." The project aims to revolutionize the creation of novel engineering alloys by developing a data-driven platform called "DRAGONS" (Data-Driven Recursive...
The National Science Foundation (NSF) awarded a $322,809 Project Grant under its Mathematical and Physical Sciences program (CFDA 47.049) to the University of California, San Diego (UCSD) to conduct collaborative research on designing and manufacturing ultrahigh temperature ceramics. The overarching goal is to develop ceramics with improved toughness and deformation resistance at both low and high temperatures, enabling their use in extreme environment applications like hypersonic flight,...
This $106,769 Project Grant from the National Science Foundation's Mathematical and Physical Sciences program will support the development of new methods to systematically explore and predict materials microstructures. The University of California, Davis will receive funding from September 1, 2022 through August 31, 2024 to adapt machine learning and data science techniques for materials science applications. Specifically, the university will integrate expert knowledge on physically meaningful...
This $200,000 National Science Foundation (NSF) award under the Mathematical and Physical Sciences program (CFDA 47.049) supports a collaborative research project led by the University of California, Berkeley to develop and harness quasi-one-dimensional topological materials for novel electronic, optoelectronic, and sensing functionalities. The project aims to overcome current limitations of topological insulators by focusing on quasi-1D materials, which have the potential to enable new...
This $700,000 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) will support The Johns Hopkins University's research on amorphous metal additive manufacturing. The project aims to develop simulation-informed models and computational tools to enable design of additively manufactured amorphous metals with desired strength and toughness properties. This will involve using machine learning to quantify structural order parameters...
This $1,481,906 Project Grant award from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) supports research to discover and develop new multi-principal-element hexagonal-close-packed structural alloys using advanced computational materials science and additive manufacturing methods. The University of California, Berkeley is the awardee, with the State of California Controllers Office serving as the parent organization.
The project aims to rapidly identify promising new alloy compositions and processing techniques that can yield stronger and lighter structural materials suitable for low-temperature applications, such as space exploration. Key activities include coupling high-throughput computation and experimentation with machine learning to model and synthesize new multi-element alloys based on metals like titanium, scandium, and zirconium. The resulting materials data and predictive models will be used to iteratively discover and validate additively manufactured alloys with desirable mechanical properties. This work aligns with the Materials Genome Initiative's goals of accelerating materials innovation.