The Atomistic Cookbook

This cookbook contains recipes for atomic-scale modelling for materials and molecules, with a particular focus on machine learning and statistical sampling methods. Most of the examples rely heavily on software developed by the laboratory of computational science and modeling (COSMO, see its github page) but the cookbook is open for recipes using all types of modeling tools and techniques. Rather than focusing on the usage of a specific package, this cookbook provides concrete examples of the solution of modeling problems, often using a combination of several tools.

Downloading and running the recipes

Each recipe can be viewed online as an interactive HTML page, but can also be downloaded as a stand-alone .py script of .ipynb Jupyter notebook. To simplify setting up an environment that contains all the dependencies needed for each recipe, you can also download an environment.yml file that you can use with conda to create a custom environment to run the example.

# Pick a name for the environment and replace <environment-name> with it
conda env create --name <environment-name> --file environment.yml

# when you want to use the environment
conda env activate --name <environment-name>

Additional data needed for each example is usually either downloaded dynamically, or can be found in a data folder for each example, or downloaded as a data.zip file at the end of each recipe in the website.

Table of contents

• Recipes grouped by topic
• Recipes grouped by software used
• List of all recipes
• Contributing a recipe

Recipe of the day

Want to try something new? Each day, one of the recipes in the cookbook is highlighted on the front page. There is one to suit everyone’s taste!