This lesson is being piloted (Beta version)

Quantum Mechanics Tools

This lesson created for the Molecular Sciences Software Institute (MolSSI) teaches users fundamentals of performing quantum chemistry calculations. The material is designed for undergraduate students, or other early career students, who have basic familiarity with python syntax, plotting with matplotlib, and using numpy. If students are unfamiliar with these python skills, we recommend the Python Data and Scripting for Computational Molecular Science lesson from MolSSI. To see the full MolSSI’s education mission statement, please see here.

This material was used at the MolSSI workshop at the MERCURY Confernece on Computational Chemistry in 2019.

Many instructors like to provide their students with pre-filled jupyter notebooks that contain some of the larger code blocks and examples. You can find complete jupyter notebooks for each lesson in the code folder of the GitHub repository from which you could develop notebooks for students.

This lesson is under development, please report issues to the GitHub repository


Students should be familiar with the syntax of python programming, plotting with matplotlib, and using the numpy library in a jupyter notebook.


Setup Download files required for the lesson
00:00 1. Geometry optimization How do I optimize the geometry of a molecule?
01:30 2. Intramolecular Potential Energy Surfaces How do I calculate a potential energy surface for an intramolecular coordinate in a molecule?
03:00 3. Intermolecular Potential Energy Surfaces How do I calculate a potential energy surface for the interaction between two molecules?
04:30 4. Basis set convergence of molecular properties: Geometry and Vibrational Frequency Do the calculated molecular properties of a molecule converge with increasing basis set size?
06:00 5. Computation of standard redox potentials How can you calculate the redox potential of a reaction?
07:30 6. Version Control with Git and GitHub How does version control track the changes in a collaborative project?
08:30 7. Making Changes to an Existing Code How do I make changes to a code and then push it to GitHub?
09:50 Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.