Machine learning is rapidly transforming molecular dynamics simulations by enabling the construction of highly accurate interatomic potentials derived from high‐level quantum calculations. This ...
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 ...
Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...
MLIP calculations successfully identify suitable dopants for a novel photocatalytic material, report researchers from the Institute of Science Tokyo. As demonstrated in their study, published in the ...
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