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A dual-cutoff machine-learned potential for condensed organic systems obtaine...
Machine-learned potentials (MLPs) trained on ab initio data combine the computational efficiency of classical interatomic potentials with the accuracy and generality of the... -
A data-science approach to predict the heat capacity of nanoporous materials
The heat capacity of a material is a fundamental property that is of significant practical importance. For example, in a carbon capture process, the heat required to regenerate...