Project Grant 2225675

The Johns Hopkins University received a three-year, $600,000 Project Grant from the National Science Foundation Division of Civil, Mechanical, and Manufacturing Innovation under the Engineering (47.041) federal grant program. The grant will support research utilizing integrated physics-based modeling, machine learning, and experiments to develop a "digital twin" of acoustic emission experiments that can predict deformation mechanisms in metals. Specifically, the university will (1) model acoustic emission wave propagation from slip avalanches in nickel micropillars, (2) assess existing models and develop new physics-based theories linking acoustic emissions to dislocation plasticity, (3) predict three-dimensional slip localization from surface acoustic measurements, and (4) train deep learning models to enable forward prediction of acoustic emissions and inverse prediction of underlying deformation mechanisms. The grant will also fund in situ microscopy experiments on nickel microcrystals to validate model predictions and gain new understanding of deformation mechanisms during loading. Outcomes from this research will be incorporated into a new graduate course and high school outreach activities will engage underrepresented students in research internships.