Project Grant 2323767

Award Date 10/1/23
Completion Date 2/29/24
Dollars Obligated $400K
Funding Federal Agency
National Science Foundation
Awarding Federal Agency
Division of Materials Research
Federal Grant Program
47.041
Assistance Type
Project Grant
Place of Performance
Reno, NV 89557, USA
Similar Awards
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 awarded a $294,992 Project Grant to The Research Foundation for the State University of New York under the Engineering program (CFDA 47.041). The grant supports fundamental research to develop a symbolic artificial intelligence framework for automatically discovering physically interpretable constitutive laws of soft functional composites. The framework will incorporate general tensor functions, scalar and tensor-based operators, and statistical analysis for noisy...
This $598,958 Project Grant awarded by the National Science Foundation's (NSF) Engineering program (CFDA 47.041) will support research at the University of Illinois to study the mechanical behavior of two-dimensional atomic sheets with defects. The project will leverage advances in artificial intelligence and machine learning to overcome computational challenges in modeling the elasticity, strength, and fracture properties of these two-dimensional lateral heterostructures. The research aims to...
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...
This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) supports fundamental research to enable the automatic discovery of constitutive laws for soft functional composites using symbolic artificial intelligence (AI) technology. The $135,207 award to the University of Maryland, College Park will establish a symbolic AI framework for identifying physically interpretable constitutive laws of these materials, which are essential for emerging...
This $500,001 Project Grant was awarded by the National Science Foundation (CFDA #47.070 - Computer and Information Science and Engineering) to the Texas A&M Engineering Experiment Station (Tees) to conduct research on advancing autonomous, materials-on-demand manufacturing capabilities through the convergence of manufacturing, AI, and materials science. The key objectives are to develop foundational principles for shape-constrained machine learning, effective handling of...
The National Science Foundation Division of Materials Research awarded a $1.8 million Project Grant to the Texas A&M Engineering Experiment Station (doing business as Tees) to support the "DMREF: AI-GUIDED ACCELERATED DISCOVERY OF MULTI-PRINCIPAL ELEMENT MULTI-FUNCTIONAL ALLOYS" project. The funding period is from October 1, 2021 to September 30, 2025. Under this award, Tees will utilize artificial intelligence-guided methods to rapidly discover new multi-principal element alloys...
This National Science Foundation (NSF) Integrative Activities (CFDA 47.083) Project Grant award of $299,862 to the University of Nevada, Reno will support research to develop a new framework for integrating machine learning and physics-based computational models to create "digital twins" of dynamic systems. The research aims to address limitations in current hybrid data-driven modeling approaches by embedding neural networks within physics-based models to better account for modeling...
The National Science Foundation (NSF) provided a $676,990 Project Grant award under the Engineering program (CFDA 47.041) to North Carolina State University (NC State) to develop a new class of ultralight, manufacturable materials with optimized mechanical and transport properties. The key objectives are to: Characterize and understand the benefits of exploiting local uniformity and hyperuniformity in materials design, Measure mechanical and transport properties to create...
The University of Utah received a $622,222 National Science Foundation Project Grant under the NSF Engineering program (CFDA 47.041) for the period of September 1, 2021 through August 31, 2025. The grant funds collaborative research on physics-informed artificial intelligence to parallelly design metal matrix composites and their additive manufacturing processes. The NSF Engineering program seeks to improve quality of life and economic strength through innovative engineering research and...

The National Science Foundation (NSF) awarded a $399,916 Project Grant under its Engineering program (CFDA 47.041) to the University of Nevada, Reno (UNR) to fund research on developing ultrastrong and ultraelastic metallic alloys using artificial intelligence (AI) enabled automated design.

The goal of this 16-month project is to leverage AI, computational modeling, and experimental tools to rapidly design, synthesize, and test new metallic alloy compositions that can withstand extreme stress and recoverable elastic deformation. The research team will employ a two-stage automated workflow transitioning from a data-driven to a physics-based approach, integrating AI techniques and physical models to enhance the understanding of deformation mechanisms in complex materials. This innovative AI-enabled research workflow aims to revolutionize the design and manufacturing processes of ultrastrong and ultraelastic metallic alloys, which have applications in structural and functional materials. The project will also provide educational opportunities for undergraduate and graduate students across materials science, computer science, and mechanical engineering disciplines, while promoting diversity, equity, and inclusion.

Generated 8/13/24, 9:24 AM