27-534 Methods of Computational Materials Science

9 units, Carnegie Mellon University

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. Topics include density functional theory, molecular dynamics, Monte Carlo simulations, and phase field models. An overview of machine learning for materials research is also provided. Examples and homework problems are drawn from various areas of materials science. Coursework utilizes both software packages and purpose-built computer codes. Students should be comfortable writing and running simple computer programs in MATLAB, Python, or comparable environments.

Prerequisites: none listed

Offered: Spring 2027, Spring 2026

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