tildeMaterials informatics framework for ab initio data repositories
Stars: ✭ 19 (-32.14%)
ONCVPseudoPackCollection of ONCVPSP pseudopotentials for density-functional theory calculations
Stars: ✭ 6 (-78.57%)
SMACTPython package to aid materials design
Stars: ✭ 46 (+64.29%)
ai4materialsDeep learning for crystal-structure recognition and analysis of atomic structures
Stars: ✭ 26 (-7.14%)
yamtbxmy crystallographic toolbox
Stars: ✭ 17 (-39.29%)
hipercHigh Performance Computing Strategies for Boundary Value Problems
Stars: ✭ 36 (+28.57%)
nequipNequIP is a code for building E(3)-equivariant interatomic potentials
Stars: ✭ 312 (+1014.29%)
DMFTwDFTDMFTwDFT: An open-source code combining Dynamical Mean Field Theory with various Density Functional Theory packages
Stars: ✭ 39 (+39.29%)
MolDQN-pytorchA PyTorch Implementation of "Optimization of Molecules via Deep Reinforcement Learning".
Stars: ✭ 58 (+107.14%)
masci-toolsTools, utility, parsers useful in daily material science work
Stars: ✭ 18 (-35.71%)
ESPEIFitting thermodynamic models with pycalphad - https://doi.org/10.1557/mrc.2019.59
Stars: ✭ 46 (+64.29%)
OpenMaterial3D model exchange format with physical material properties for virtual development, test and validation of automated driving.
Stars: ✭ 23 (-17.86%)
atomate2atomate2 is a library of computational materials science workflows
Stars: ✭ 67 (+139.29%)
uglymolMacromolecular viewer for crystallographers (WebGL)
Stars: ✭ 28 (+0%)
pdbtbxA library to open/edit/save (crystallographic) Protein Data Bank (PDB) and mmCIF files in Rust.
Stars: ✭ 13 (-53.57%)
PeakPoX-ray diffraction data analysis for high pressure and high temperature experiments
Stars: ✭ 14 (-50%)
debyerDebye's scattering equation & other analysis of atomistic models.
Stars: ✭ 32 (+14.29%)
DeepchemDemocratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
Stars: ✭ 3,324 (+11771.43%)
amsetElectronic transport properties from first-principles calculations
Stars: ✭ 57 (+103.57%)
pfhubThe CHiMaD Phase Field Community Website
Stars: ✭ 25 (-10.71%)
olympusOlympus: a benchmarking framework for noisy optimization and experiment planning
Stars: ✭ 38 (+35.71%)
aiida-vaspA plugin to AiiDA for running simulations with VASP
Stars: ✭ 32 (+14.29%)
snapRepository for spectral neighbor analysis potential (SNAP) model development.
Stars: ✭ 27 (-3.57%)
lamipyComposite laminates engineering simulations in Python.
Stars: ✭ 32 (+14.29%)
RHEOS.jlRHEOS - Open Source Rheology data analysis software
Stars: ✭ 23 (-17.86%)
pytopomatPython Topological Materials (pytopomat) is a code for easy, high-throughput analysis of topological materials.
Stars: ✭ 19 (-32.14%)
matador⚗️ matador is an aggregator, manipulator and runner of first-principles calculations, written with a bent towards battery 🔋 electrode materials.
Stars: ✭ 23 (-17.86%)
chemiscopeAn interactive structure/property explorer for materials and molecules
Stars: ✭ 41 (+46.43%)
pyGAPSA framework for processing adsorption data and isotherm fitting
Stars: ✭ 36 (+28.57%)
mamlPython for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.
Stars: ✭ 174 (+521.43%)
CatKitGeneral purpose tools for high-throughput catalysis
Stars: ✭ 48 (+71.43%)
uf3UF3: a python library for generating ultra-fast interatomic potentials
Stars: ✭ 19 (-32.14%)
atomaiDeep and Machine Learning for Microscopy
Stars: ✭ 77 (+175%)
thermo pwThermo_pw is a driver of quantum-ESPRESSO routines for the automatic computation of ab-initio material properties.
Stars: ✭ 34 (+21.43%)
tdmmsTwo-dimensional materials manufacturing system
Stars: ✭ 17 (-39.29%)
data-resources-for-materials-scienceA list of databases, datasets and books/handbooks where you can find materials properties for machine learning applications.
Stars: ✭ 81 (+189.29%)
phoebeA high-performance framework for solving phonon and electron Boltzmann equations
Stars: ✭ 33 (+17.86%)
CrabNetPredict materials properties using only the composition information!
Stars: ✭ 57 (+103.57%)