Universal Machine Learning Interatomic Potentials: Surveying Solid Electrolytes

Review/Survey Paper for Machine learning potentials. Review/survey candidate for mapping the literature, mechanisms, methods, and open questions in Machine learning potentials.

Citation: Amir Hajibabaei, Kwang S. Kim. Universal Machine Learning Interatomic Potentials: Surveying Solid Electrolytes. The Journal of Physical Chemistry Letters 2021. https://doi.org/10.1021/acs.jpclett.1c01605

Acknowledgement: Curated by MaterialsAtlas Open Resources from OpenAlex, Crossref, and manual landmark-paper review.