Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Project.

Deep learning for molecules and materials book

🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.

Curated list of known efforts in materials informatics, i.e. in modern materials science

JARVIS-Tools: an open-source software package for data-driven atomistic materials design. Publications: https://scholar.google.com/citations?user=3w6ej94AAAAJ https://www.youtube.com/watch?v=2-XHeC8gbeY

Graph deep learning library for materials

A list of databases, datasets and books/handbooks where you can find materials properties for machine learning applications.

Things that you should (and should not) do in your Materials Informatics research.

A toolkit for visualizations in materials informatics.

Data Analysis program and framework for materials science data analytics, based on the managing framework SIMPL framework.

ChemML is a machine learning and informatics program suite for the chemical and materials sciences.

RadonPy is a Python library to automate physical property calculations for polymer informatics.

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A Highly Opinionated List of Open Source Materials Informatics Resources

Open-source library for analyzing the results produced by ABINIT

A machine learning environment for atomic-scale modeling in surface science and catalysis.

Python package to aid materials design and informatics

Catalyst Micro-kinetic Analysis Package for automated creation of micro-kinetic models used in catalyst screening

Predict materials properties using only the composition information!

A Bayesian global optimization package for material design ｜ Adaptive Learning | Active Learning