Chemical Engineering 577 - AtomisticSimulations/Catalysis

This course will provide students with a strong theoretical foundation in atomistic modeling techniques, including density functional theory (DFT), molecular dynamics (MD), and machine learning (ML)-based approaches. Through a combination of lectures and hands-on computational exercises, students will explore how these methods are applied to heterogeneous catalysis, from elucidating reaction mechanisms to designing more efficient catalysts.

Open to all juniors and seniors in Engineering, Physics, Chemistry, and Biochemistry & Molecular Biology, and all graduate students.