Machine learning is rapidly transforming molecular dynamics simulations by enabling the construction of highly accurate interatomic potentials derived from high‐level quantum calculations. This ...
Training datasets for Matlantis’s core AI technology are now developed using r²SCAN, doubling accuracy in atomistic simulations compared to previous version CAMBRIDGE, Mass., July 16, 2025 (GLOBE ...
illustrating the comprehensive zero-shot benchmark of 19 universal machine learning interatomic potentials and the dominant impact of training data composition for surface energy prediction. A ...
Researchers used machine learning interatomic potential (MLIP) calculations to narrow down the search for candidate dopants for a new type of photocatalytic tin oxide. MLIP calculations successfully ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results