Atomistic Simulations for Heterogeneous Catalysis (CHE 577)
Most undergrads don't get hands-on research experience until grad school, if ever. This course changes that. It's a Course-Based Undergraduate Research Experience (CURE): a real, credit-bearing class where you're not following a lab manual, you're generating original data on open research questions in catalysis and energy materials.
Using first-principles simulations, molecular dynamics, and machine-learning (ML)-assisted modeling, you'll work on faculty-guided research themes including:
Solid-liquid interfaces and surface chemistry
Electrocatalysis for energy conversion
Structure-property relationships in metals and their oxides
ML-assisted screening of materials and active sites
Each theme is a self-contained module scoped to be genuinely doable in a semester, with weekly check-ins, structured tutorials (including a full set on the Schrödinger platform), and direct guidance from the instructor. You're never just “running software” alone.
By the end of the course you'll be able to formulate your own research questions, design and run computational experiments, analyze high-dimensional simulation data, and communicate findings through posters, talks, and written reports; the same skill set driving AI-accelerated materials discovery at places like Microsoft, Google, and Meta.
