Project Grant DESC0019691

This SBIR Phase I award from the National Science Foundation's (NSF) Technology, Innovation, and Partnerships (TIP) program, with a total funding amount of $274,985, is focused on developing an artificial intelligence (AI) system to accelerate semiconductor production using physics-embedded lithographic foundation models. The project aims to alleviate design and manufacturing complexities associated with the shift to extreme ultraviolet (EUV) lithography in semiconductor manufacturing, which has...

This National Science Foundation project grant of $697,756 will fund research at the University of California, Los Angeles from July 1, 2022 to June 30, 2025 to develop atomic layer etching processes for layer-by-layer removal of metal films. The research aims to gain a thorough understanding of plasma surface modification and self-limiting surface reaction mechanisms for industrially significant metals such as nickel and copper. The project will integrate computational chemistry modeling with...

This Project Grant from the National Science Foundation Division of Civil, Mechanical, and Manufacturing Innovation supports research to advance manufacturing processes for semiconductor electronic and quantum devices at the atomic scale. Funded for $292,392 over two years from January 1, 2023 through December 31, 2024, the award supports the University of Maryland, College Park under the NSF Engineering program (CFDA 47.041). The research aims to develop robust manufacturing techniques with...

This $271,320 National Science Foundation project grant supports research at Arizona State University to develop machine learning-assisted ultrafast physical vapor deposition of high-quality, large-area functional thin films. The goal is to apply machine learning algorithms to optimize thin film growth conditions and accelerate the development of thin films with targeted electronic and optical properties. This will enable faster and lower-cost manufacturing of functional oxides, chalcogenides...

This National Science Foundation project grant of $272,581 supports research at Texas A&M Engineering Experiment Station to develop machine learning-assisted ultrafast physical vapor deposition of functional thin films. The goal is to produce high-quality, large-area functional thin films for applications in electronics, photonics, and energy industries. Researchers will apply machine learning algorithms to training data from experimental thin film growth and literature to optimize...

Applied Imaging Solutions LLC received a $400,000 Cooperative Agreement from the National Institute of Standards and Technology (NIST) under the Science, Technology, Business and/or Education Outreach program (CFDA 11.620), effective October 1, 2025, through September 30, 2027. The award funds the development of an interpretable artificial intelligence (AI) and deep learning system integrated with a hyperspectral imaging platform designed to enable real-time, label-free detection of critical...

Intelligent Automation, LLC received a $250,000 Project Grant award from the Department of Energy Office of Science on February 22, 2021 to develop non-linear machine learning based data reduction software for high-performance computing. The award was made under the Office of Science Financial Assistance Program (CFDA 81.049), which supports scientific discoveries and major scientific tools to transform understanding of nature and advance U.S. energy and economic security. The software developed...

This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $1,200,000 to Purdue University to develop scalable and ultra-low-power neural accelerators based on 2D ferroelectric semiconductors. The research aims to address hardware needs for future artificial intelligence (AI) platforms by utilizing the unique properties of ferroelectric semiconductors to design energy-efficient circuits and...

This federal Project Grant award, funded by the National Science Foundation's Engineering program (CFDA 47.041), supports the development of a multiscale simulation tool that fuses quantum, atomistic, and mesoscale models through machine learning. The goal is to establish a simulation framework and database that can advance the understanding of how semiconductors deform under light exposure, a phenomenon known as photoplasticity. The $182,000 award to Iowa State University of Science and...

This Project Grant from the National Science Foundation's Division of Civil, Mechanical, and Manufacturing Innovation provides $779,240 to support research at the University of Notre Dame advancing lithography-free manufacturing techniques for metal nanostructures separated by nanogaps. Specifically, the award funds work through August 2025 to define benchtop fabrication methods for integrating opposing metal surfaces separated by sub-5 nm nanogaps into applications in plasmonics and molecular...