This is a lab class which is a crash course in skills for computational physical chemistry. Click here for the syllabus. The companion github page for this class can be found at this link.
Lecture Notes
- Lecture 1 - Introduction
- Lecture 2 - Data organization and analysis
- Lecture 3 - Introduction to Molecular Dynamics, and running jobs on a cluster
- Lecture 4 - Parallel Tempering
- Lecture 5 - Umbrella Sampling and Metadynamics
- Lecture 6 - Structure prediction, alphafold, and VMD
- Lecture 7 - Simulating simple models with LAMMPS
- Lecture 8 - Introduction to Electronic Structure Theory
- Lecture 9 - Introduction to DFT and chem-informatics
- Lecture 10 - Ab initio molecular dynamics
Past versions of this class
- Material from 2022 can be found at this link.