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amptorch

AMPTorch: Atomistic Machine Learning Package (AMP) - PyTorch

ase-espresso

ase interface for Quantum Espresso

awesome-cv

:page_facing_up: Awesome CV is LaTeX template for your outstanding job application

ceph

Ceph is a distributed object, block, and file storage platform

cgcnn

Crystal graph convolutional neural networks for predicting material properties.

dft-book-espresso

New version of dft-book for Quantum Espresso

f19-06625

Course repository for Chemical and Reactive Systems (06-625) at CMU, Fall 2019

fireworks

The Fireworks Workflow Management Repo.

nuclearitycalculation

A set of functions for surface nuclearity calculations using GASPy-dev and pymatgen

ocp

https://opencatalystproject.org/

open-catalyst-dataset

Workflow for creating and analyzing the Open Catalyst Dataset

plumed_ipi_ase_example

purpleair_ifttt

pymatgen

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

schnet_train_example

simple-nn

SIMPLE-NN(SNU Interatomic Machine-learning PotentiaL packagE – version Neural Network)

standard_tasks

techela

Techela in a Flask

vasp

New ASE compliant Python interface to VASP

xtb

Semiempirical Extended Tight-Binding Program Package

zulissi.github.io

A beautiful, simple, clean, and responsive Jekyll theme for academics