Computational Design of Materials
CHEM 275
Subject & Catalog Number
Course Information
Description
This course covers theoretical background and practical hands-on applications of modern computational atomistic methods used to understand and design properties of advanced functional materials. Topics include classical interatomic potentials and machine learning methods, quantum first-principles electronic structure models based on wave functions and density functional theory, Monte Carlo sampling and molecular dynamics simulations of phase transitions and free energies, fluctuations and transport properties. Applications include atomistic and electronic effects in materials for energy conversion and storage, catalysis, alloys, polymers, and low-dimensional materials.
Course Notes
CHEM 275 is also offered as Applied Physics 275 and Applied Computation 275. Students may may only take one for credit.
Recommended Prep
Undergraduate coursework in quantum mechanics and solid-state physics, physical chemistry, linear algebra, thermodynamics and statistical mechanics.
Available for Harvard Cross Registration
