Ad Astra Fellow Startup Funding, University College Dublin (2025–2030)
Project: TO BE DETERMINED
Description: Check back soon!
Synthesis Advanced Research Challenge, Toyota Research Institute (2024–2026)
Project: Direct Introduction of Competition and Kinetics to Materials Mechanism and Reaction Network Prediction
Description: Solid-state synthesis continues to be driven by trial-and-error experimentation, with no coherent design rules or underlying theory. Though there has been considerable interest in predicting the outcomes of solid-state reactions and automating the selection of precursors and synthesis conditions, most approaches developed to date rely entirely on bulk thermodynamics, ignoring the kinetics of nucleation and growth. Our proposed work provides a new approach for predictive materials synthesis, combining machine learning, molecular dynamics simulations, and chemical reaction networks to calculate solid-state reaction kinetics, rationally explain synthesis outcomes, and select precursors that are likely to lead to efficient formation of desired product phases.
![]() | Tartan Advanced Research Supercomputing Environment, Carnegie Mellon University |
![]() | Advanced Cyberinfrastructure Coordination Ecosystem Services & Support (ACCESS), US National Science Foundation (NSF) |
![]() | National Artificial Intelligence Research Resource (NAIRR) Pilot, NSF and partners |
![]() | Zulip |