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.
CALPHAD tools for designing thermodynamic models, calculating phase diagrams and investigating phase equilibria.
Official implementation of All Atom Diffusion Transformers (ICML 2025)
Deep and Machine Learning for Microscopy
A python library for calculating materials properties from the PES
Provides a layer based user interface and utility functions for creating complex materials in Blender.
Agenda, Minutes, Presentations
Defect structure-searching employing chemically-guided bond distortions
🍀 A small collection of creative nodes to generate color palette and store values for Blender
Benchmark Suite for Machine Learning Interatomic Potentials for Materials
Elementary Multiperspective Material Ontology (EMMO)
LLM-powered agents for scientific research automation
Fitting thermodynamic models with pycalphad - https://doi.org/10.1557/mrc.2019.59
A DEM toolkit for rapid simulation & quantitative analysis of granular systems
This library tackles the construction and efficient execution of computational chemistry workflows
A tool for streamlining data analysis and visualisation for thermoelectrics and charge carrier transport in computational materials science.
MatDGL is a neural network package that allows researchers to train custom models for crystal modeling tasks. It aims to accelerate the research and application of material science.
Introduction to Decorators - Tutorial given at PyCon Online 2020 and 2021
The official PyTorch implementation for paper "SurfaceNet: Adversarial SVBRDF Estimation from a Single Image"
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