Computational prediction of solvation structures in calcium battery electrolytes

Jeong, Heonjae; Wang, Haimeng; Cheng, Lei

doi:10.1039/D4TA06675H

Computational prediction of solvation structures in calcium battery electrolytes

Journal Article · Mon Dec 09 00:00:00 EST 2024 · Journal of Materials Chemistry. A

DOI:https://doi.org/10.1039/D4TA06675H· OSTI ID:2480608

^[1]; ^[2]; Cheng, Lei ^[2]

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
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

This study demonstrates comprehensive approaches for predicting solvation structures in Ca-ion battery electrolytes by integrating ab initio calculations and machine learning force fields.

View Accepted Manuscript (Publisher)

Sponsoring Organization:: USDOE

OSTI ID:: 2480608

Journal Information:: Journal of Materials Chemistry. A, Journal Name: Journal of Materials Chemistry. A Journal Issue: 47 Vol. 12; ISSN JMCAET; ISSN 2050-7488

Publisher:: Royal Society of Chemistry (RSC)Copyright Statement

Country of Publication:: United Kingdom

Language:: English

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