The rapid development of foundation potentials (FPs) in machine learning interatomic potentials demonstrates the possibility for generalizable learning of the universal potential energy surface. The ...
The ability to predict materials properties from atomistic simulations is essential for modern materials design. Machine learning interatomic potentials (MLIPs), trained on data from electronic ...
Liquid Bi shows a peculiar dispersion of the acoustic mode, which is related to the Peierls distortion in the crystalline state. These results will provide valuable inspiration to researchers ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results