Systematic softening in universal machine learning interatomic potentials

Systematic softening in universal machine learning interatomic potentials

Abstract Machine learning interatomic potentials (MLIPs) have introduced a new paradigm for atomic simulations. Recent advancements have led to universal MLIPs (uMLIPs) that are pre-trained on diverse datasets, providing opportunities for universal force fields and foundational machine learning mode...

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Bibliographic Details
Main Authors: Bowen Deng, Yunyeong Choi, Peichen Zhong, Janosh Riebesell, Shashwat Anand, Zhuohan Li, KyuJung Jun, Kristin A. Persson, Gerbrand Ceder
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:npj Computational Materials
Online Access:https://doi.org/10.1038/s41524-024-01500-6
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