I-Corps: Translation Potential of an Artificial Intelligence (AI)-Powered Materials Characterization Platform for Automated Microscopy and Spectroscopy Analytics

This I-Corps project is based on the development of an artificial intelligence (AI)-powered software platform that automates data analysis for material characterization. Analysis of imaging and analytical data is manual, time-consuming, and difficult to reproduce, creating a major bottleneck in research, product development, manufacturing optimization, and quality assurance. This technology rapidly converts complex microscopy and spectroscopy data into standardized, quantitative information to support faster and more reliable decision making. The applications include advanced manufacturing, semiconductors, batteries, catalysts, aerospace, pharmaceuticals, biotechnology, and other industries that depend on advanced materials characterization. It may reduce analysis time and improve consistency and reproducibility, and may accelerate materials innovation, improve manufacturing productivity, and strengthen U.S. competitiveness. This I-Corps project utilizes experiential learning coupled with first-hand investigation of the industry ecosystem to assess the translation potential of an artificial intelligence (AI)-powered software platform for automated quantitative materials characterization. This technology integrates advanced microscopy and spectroscopy with computer vision, machine learning, deep learning, and multimodal data analytics. In addition, it automatically extracts and quantifies microstructural and compositional features from microscopy and spectroscopy data, including particle size distributions, layer thickness, pore structures, elemental distributions, and interfacial chemistry, while generating reproducible structure–property–performance correlations. This technology may reduce analysis time by up to two orders of magnitude while improving reproducibility and scalability compared to conventional manual workflows. The applications include research, industrial research and development, manufacturing, and quality assurance. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.