Machine Learning Interatomic Potentials for Catalysis: Developing a robust MLIP training framework
收藏DataCite Commons2025-11-03 更新2026-02-08 收录
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https://dataverse.bsc.es/citation?persistentId=doi:10.82201/01DGGC
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资源简介：
Heterogeneous catalysts are valued for their enhanced performance, but analyzing their electronic structures over large systems and extended periods is costly with ab-initio methods such as DFT. Recently, machine-learned interatomic potentials (MLIPs) have allowed for much faster calculations of energies and forces, facilitating more detailed catalytic studies.
提供机构：
BSC Dataverse
创建时间：
2025-10-31
