materialyze/matpes

Dataset Summary Potential energy surface datasets with near-complete coverage of the periodic table are used to train foundation potentials (FPs), i.e., machine learning interatomic potentials (MLIPs) with near-complete coverage of the periodic table. MatPES is an initiative by the Materialyze Lab and the Materials Project to address critical deficiencies in such PES datasets for materials. Accuracy. MatPES is computed using static DFT calculations with stringent converegence… See the full description on the dataset page: https://huggingface.co/datasets/materialyze/matpes.