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Computational Chemistry Resources: Workshops and Tutorials

Here are a bunch of resources that might be useful for anyone who wants an introduction to comp. chem., or data science with chemistry applications. I hope to continue adding resources, but at least for now most of the resources were created by MolSSI Education- they have some really excellent workshops and tutorials. Go ahead and visit their website to learn more about what they do: http://education.molssi.org

For an introduction to the command line/Terminal and installing software packages: https://education.molssi.org/getting-started-computational-chemistry/

Recommended for 1 year graduate students, or undergraduates with little to no experience with the command line/Terminal

  • What is Comp Chem?
  • What is the Terminal?
  • What is a text editor?
  • How to access remote computing resources
  • Using Anaconda to install software
  • Jupyter Notebooks

For an introduction to Python: https://education.molssi.org/python_scripting_cms/

Recommended for 1st year graduate students, or undergraduates.

  • How to parse files for specific data
  • How to write a file
  • Reading and writing tabular data
  • Data plotting with Matplotlib.pyplot
  • Writing a Python function (Example used is how to calculate the distance between two atoms)
  • Writing from the Linux command line, vs. Jupyter Notebook
  • Version control with git and keeping a project history

Python for data analysis and visualization: https://education.molssi.org/python-data-analysis/

Recommended for 1st year graduate students, or undergraduates with some experience with basic Bash commands (i.e., navigating the Terminal/command line) and who have introductory Python skills (i.e., know about booleans, loops, importing packages, parsing files).

  • Working with Numpy arrays
  • Using Pandas and dataframes
  • Using Scipy for data fitting

Quantum chemistry basics: https://education.molssi.org/qm-tools/

Recommended for 1st year graduate students, or undergraduates who have some introductory Python skills, are familiar with Matplotlib and Jupyter Notebooks.

  • Geometry optimizations
  • Intra- and intermolecular potential energy surfaces
  • Basis set convergence of geometry and vibrational frequencies
  • Example of computing standard redox potentials
  • Version control with Git and Github
  • Code editing

Brief review of elementary quantum chemistry: http://vergil.chemistry.gatech.edu/notes/quantrev/quantrev.html

This was created by Prof. David Sherrill at Georgia Institute of Technology.

  • Very comprehensive quantum chemistry theoretical background, maybe nice for prepping/ reviewing for your preliminary exam.

A Hitch-Hiker's Guide to Molecular Thermodynamics (a fun text): http://alan-cooper.org.uk/wp-content/uploads/2014/10/hhguide.pdf

This was created by Prof. Alan Cooper at Glasgow University

  • He does a great job at making thermodynamics engaging and fun to read.

Biomolecular Interactions (lecture slides): http://alan-cooper.org.uk/wp-content/uploads/2015/03/Biomol-Interactions-lecture-notes.pdf

Also created by Prof. Alan Cooper at Glasgow University

  • Theoretical and experimental basis of intermolecular interactions
  • Electrostatics
  • Van der Waals
  • Dispersion
  • Hydrogen bonding
  • Hydrophobic effect

Online Eyring equation calculator: https://www.unige.ch/sciences/chiorg/lacour/correl

  • First order kinetics
  • Thermodynamics

For funsies: https://www.playphrase.me/#/search

This is a website where you can type in certain words and it will find movie clips with those words. Great for adding comedic relief into group meeting slides.