In this course, graduate students will be taught the theory and application of computer modeling of materials at the atomic scale. Specific topics include: classical and modern first principles atomistic modeling approaches, statistical mechanics, molecular statics and dynamics, density functional theory, and kinetic Monte Carlo sampling. The approximations, advantages, and limitations involved with each approach will be highlighted. A significant focus of the course will be to provide a "hands-on" training on these computational techniques through software such as LAMMPS, GROMACS, and Quantum-Espresso. To illustrate computational modeling research, a number of practical case studies from advanced materials and nanotechnology will be highlighted. The course will also include an individual or group project. Some advanced topics, such as accelerated molecular dynamics, multiscale modeling, coarse-graining approaches, and DFT+U will also be introduced.

Students from diverse fields of study are welcome to attend the course. A number of approaches and case studies from hard materials as well as polymers and biological systems will be covered. Projects from diverse research areas are also encouraged.