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MatPES is an initiative by the [Materials Virtual Lab] and the [Materials Project] to address critical deficiencies in potential energy surface (PES) datasets for materials.
The main features of materialyzeai/matpes are: Datasets and Databases.
Projects with overlapping indexed features include: deepmodeling/ais-square. divelab/airs — [license-image]:https://img.shields.io/badge/license-GPL3.0-green.svg [license-url]:https://github.com/divelab/AIRS/blo… facebookresearch/fairchem — ocp is the Open Catalyst Project's library of state-of-the-art machine learning algorithms for catalysis. jla-gardner/load-atoms — load-atoms is a Python package for Loading Open Access Datasets for Atomistic Materials Science (LOAD-AtoMS). See the… materials-consortia/optimade — The OPTIMADE Specification. airi-institute/nabladft — nablaDFT: Large-Scale Conformational Energy and Hamiltonian Prediction benchmark and dataset.
license-image:https://img.shields.io/badge/license-GPL3.0-green.svg license-url:https://github.com/divelab/AIRS/blob/main/LICENSE contributing-image:https://img.shields.io/badge/contributions-welcome-brightgreen.svg?style=flat
ocp is the Open Catalyst Project's library of state-of-the-art machine learning algorithms for catalysis.
nablaDFT: Large-Scale Conformational Energy and Hamiltonian Prediction benchmark and dataset
