Recent advances and outstanding challenges for machine learning interatomic potentials
Machine learning interatomic potentials (MLIPs) enable materials simulations at extended
length and time scales with near-ab initio accuracy. They have broad applications in the …
length and time scales with near-ab initio accuracy. They have broad applications in the …
[PDF][PDF] Recent advances and outstanding challenges for machine learning interatomic potentials
TW Ko, SP Ong - materialsvirtuallab.org
Atomistic simulations are an important tool in the study of materials. The reliability of an
atomistic simulation is critically dependent on the quality of the given potential energy …
atomistic simulation is critically dependent on the quality of the given potential energy …
[引用][C] Recent advances and outstanding challenges for machine learning interatomic potentials.
TW Ko, SP Ong - Nature Computational Science, 2023 - europepmc.org
Recent advances and outstanding challenges for machine learning interatomic potentials. -
Abstract - Europe PMC Sign in | Create an account https://orcid.org Europe PMC Menu About …
Abstract - Europe PMC Sign in | Create an account https://orcid.org Europe PMC Menu About …
[引用][C] Recent advances and outstanding challenges for machine learning interatomic potentials
TW Ko, SP Ong - Nature computational science, 2023 - pubmed.ncbi.nlm.nih.gov
[PDF][PDF] Recent advances and outstanding challenges for machine learning interatomic potentials
TW Ko, SP Ong - materialsvirtuallab.org
Atomistic simulations are an important tool in the study of materials. The reliability of an
atomistic simulation is critically dependent on the quality of the given potential energy …
atomistic simulation is critically dependent on the quality of the given potential energy …