Project Grant 2429339
- 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...
- 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 Division of Civil, Mechanical, and Manufacturing Innovation awarded Northwestern University a $379,022 Project Grant under the Engineering federal grant program (CFDA 47.041) from September 1, 2021 to August 31, 2024. The grant funds collaborative research on artificial intelligence-driven multi-scale design of materials under processing constraints. The Engineering program seeks to improve quality of life and economic strength by fostering innovation and...
- This $500,000 Project Grant awarded by the National Science Foundation (NSF) Engineering program (CFDA 47.041) supports research at Northeastern University to advance "Mechanics Informatics" - a theoretical framework for learning material properties from a single, optimized mechanical test. The project aims to develop new computational methods, including inverse learning algorithms and uncertainty quantification, to automate the design, testing, and analysis of materials and...
- This Project Grant award of $500,000 from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program supports the development of a computational pipeline that integrates AI-driven optimization techniques with advanced simulations to streamline the design of mechanical metamaterials (MMs). The goal is to automate and accelerate the complex, iterative design process for these materials, which exhibit unique mechanical properties and have...
- 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...
- This Project Grant award of $280,405.00 from the National Science Foundation (NSF) Engineering program (CFDA 47.041) funds a collaborative research effort to develop a data science-based framework for learning, predicting, and simulating nanoscale fabrication processes. The research aims to enhance the understanding and modeling of the synthesis of large populations of advanced materials that are orders of magnitude smaller than human hair. Key objectives include enabling the reliable...
- The National Science Foundation awarded a $333,267 Project Grant to the University of Nebraska under the Engineering federal grant program (CFDA 47.041) for research titled "COLLABORATIVE RESEARCH: A METAMODELING MACHINE LEARNING FRAMEWORK FOR MULTISCALE BEHAVIOR OF NANO-ARCHITECTURED CRYSTALLINE-AMORPHOUS COMPOSITES." The period of performance for this research is January 1, 2022 through December 31, 2024. The grant funds collaborative research at the University of Nebraska to develop...
- This $1,060,000 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program aims to revolutionize the discovery of new solid-state materials for advanced energy storage, neuromorphic computing, and smart sensor applications. The project will leverage advanced artificial intelligence (AI), machine learning (ML), and automated synthesis tools to develop a transformative approach for designing solid-state ion conductors using multi-element...
- This $192,372 Project Grant from the National Science Foundation Directorate for Mathematical and Physical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049) supports the development of new methods to systematically explore and predict material microstructures using artificial intelligence techniques. The awardee, George Mason University, will adapt leading data science and machine learning methods to discover a practical representation of microstructure state space that...
This $400,000 federal Project Grant award from the National Science Foundation's (NSF) Division of Civil, Mechanical, and Manufacturing Innovation (CMMI) program (CFDA 47.041, Engineering) aims to revolutionize the design and manufacturing of advanced nanocomposite materials using artificial intelligence (AI). The research focus is on understanding and controlling amorphous-crystalline interfaces within these materials, which can enhance their strength, durability, and reliability. The award seeks to develop a physics-based framework for tuning the metastable amorphous-crystalline interfaces through physical vapor deposition (PVD) processing. Key research tasks involve investigating how PVD parameters affect the local structural and chemical environments at the interfaces, and then using computational approaches like self-propelling energy landscape sampling algorithms, transition state theory, machine learning, and Bayesian optimization to model the deformation mechanisms and accelerate exploration of the complex phase space. This research could lead to significant improvements in materials for critical applications in energy, defense, transportation, and other sectors.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $400.0k | 8/25/25 |