Teaching

From first-principles simulations to artificial intelligence, major advances in computational methods have ushered in a new age of materials science. In this course, we survey the major developments and limitations in computational materials design and discovery that have emerged since the start of the Materials Genome Initiative. Topics include but are not limited to: material informatics, high-throughput simulations, periodic density functional theory, material databases, machine-learned potentials, and generative artificial intelligence. Programming exercises and literature discussions will reinforce the major concepts covered in class.

This course covers foundational concepts in reaction kinetics as it relates to chemical systems of the modern-day chemical engineer. Representative topics include rate laws for homogeneous and heterogeneous reactions, fundamental concepts in catalysis, transition state theory, complex reaction networks, reactor archetypes, and how these areas of study can be used to understand and engineer societally relevant chemical processes. The course seeks to merge both the historical foundations of chemical kinetics with recent advances from the academic literature so that they can be applied in active areas of research across disciplinary boundaries.