DOE OSTI · 2480608
Computational prediction of solvation structures in calcium battery electrolytes
Abstract
This study demonstrates comprehensive approaches for predicting solvation structures in Ca-ion battery electrolytes by integrating ab initio calculations and machine learning force fields.
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Jeong, Heonjae [The Joint Center for Energy Storage Research (JCESR), Argonne National Laboratory, Lemont, Illinois 60439, USA, Materials Science Division, Argonne National Laboratory, Lemont, Illinois 60439, USA, Department of Electronic Engineering, Gachon University, Seongnam, Gyeonggi 13120, South Korea] (ORCID:000000034452049X), Wang, Haimeng [The Joint Center for Energy Storage Research (JCESR), Argonne National Laboratory, Lemont, Illinois 60439, USA, Materials Science Division, Argonne National Laboratory, Lemont, Illinois 60439, USA] (ORCID:0000000180060932), Cheng, Lei [The Joint Center for Energy Storage Research (JCESR), Argonne National Laboratory, Lemont, Illinois 60439, USA, Materials Science Division, Argonne National Laboratory, Lemont, Illinois 60439, USA]. 2024-12-09. Computational prediction of solvation structures in calcium battery electrolytes. https://doi.org/10.1039/d4ta06675h
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