Designing materials.
Discovering possibilities.

First-principles calculations, statistical mechanics, and thermodynamic modeling connect local atomic environments to material response. Collaborations with experimental teams test these connections in bulk materials and manufactured microstructures.

Data-driven models and automated computational workflows help navigate large composition spaces. Research directions include geometric learning, interpretable AI, and integrating information across materials classes.

Collaborative studies combine computational analysis with synthesis and characterization to examine adsorption, local chemical environments, and the mechanisms behind selective material behavior.