27-734-B   Methods of Computational Materials Science

Course description

This course introduces students to the theory and practice of computational materials science from the electronic to the microstructural scale. Both the underlying physical models and their implementation as computational algorithms will be discussed. Topics will include: Density functional theory, Molecular dynamics, Monte Carlo methods, Phase field models, Cellular automata and Data science. Examples and homework problems will be taken from all areas of materials science. Coursework will utilize both software packages and purpose-built computer codes. Students should be comfortable writing, compiling, and running simple computer programs in MatLab, Python, or comparable environments.

Learning objectives

The goal of the course is to learn the practice and understand the theory of computational materials science, which is now widely used to guide the design and accelerate the discovery of materials. The focus is on the fundamental theory and computer implementation of classical and quantum methods for materials simulations and their application to solve case studies.

Prerequisite

Materials science fundamentals, Python programming