Federal Grant Award Summary

Virginia Polytechnic Institute & State University (Virginia Tech) received a $486,349 Project Grant from the National Science Foundation's Division of Materials Research under the Mathematical and Physical Sciences program (CFDA 47.049) on February 1, 2026, with a completion date of January 31, 2029. The award supports the development of an integrated experimental, computational, and machine learning framework designed to predict corrosion resistance in high-entropy alloys—advanced metal alloys containing several elements in nearly equal amounts. The research integrates laboratory measurements and physics-based descriptors to accelerate materials discovery beyond traditional trial-and-error testing methodologies, enabling identification of superior alloy compositions and the mechanisms governing protective surface film formation and breakdown.

The project delivers multiple products and services with broad applicability across critical industrial sectors including energy, transportation, marine, aerospace, and biomedical engineering. Virginia Tech will generate predictive machine learning models, experimental datasets, computational simulations, and software tools that are being made publicly available to maximize research impact and utility. Additionally, the award incorporates workforce development components through graduate and undergraduate student training in materials science, electrochemistry, machine learning, and data science, alongside outreach activities targeting K-12 students to expand STEM field participation and pipeline development.