materials-informatics

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

Curated list of known efforts in materials informatics

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

Fork this repo for a quick start. If "Project Timeline" or "License" appeared on your nav bar, Look Below!

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

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

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.

Open-source library for analyzing the results produced by ABINIT

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

A Highly Opinionated List of Open Source Materials Informatics Resources

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

Predict materials properties using only the composition information!

General purpose tools for high-throughput catalysis

A PyTorch Implementation of "Optimization of Molecules via Deep Reinforcement Learning".

A toolkit for visualizations in materials informatics.

Python package to aid materials design and informatics

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

Pytorch implementation of the paper "Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules"