Atomic insights into the oxidative degradation mechanisms of sulfide solid electrolytes

Chuntian Cao, Matthew R. Carbone, Cem Komurcuoglu, Jagriti S. Shekhawat, Kerry Sun, Haoyue Guo, Sizhan Liu, Ke Chen, Seong Min Bak, Yonghua Du, Conan Weiland, Xiao Tong, Daniel A. Steingart, Shinjae Yoo, Nongnuch Artrith, Alexander Urban*, Deyu Lu*, Feng Wang*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Electrochemical degradation of solid electrolytes is a major roadblock in the development of solid-state batteries. Combining X-ray absorption spectroscopy characterization, first-principles simulations, and machine learning, here we report the atomic-scale oxidative degradation mechanisms of sulfide electrolytes using Li3PS4 (LPS) as a model system. The degradation begins with a decrease of Li neighbor affinity to S atoms, followed by the formation of S-S bonds as the PS4 tetrahedron deforms. After the first cycle, the PS4 motifs become strongly distorted, and PS3 motifs start to form. The distortion of PS4 and the formation of S-S bonds are correlated with an increased interfacial impedance. We identify the spectral fingerprints of the local structural evolution and use them as a proxy for the electrochemical stability of phosphorus sulfide electrolytes, as demonstrated in argyrodite Li6PS5Cl. This study provides guidance for controlling macroscopic reactions through microstructural engineering and can advance the rational design of sulfide electrolytes.

Original languageEnglish
Article number101909
Number of pages23
JournalCell Reports Physical Science
Volume5
Issue number4
DOIs
Publication statusPublished - 17 Apr 2024

Bibliographical note

Publisher Copyright:
© 2024 The Authors

Funding

This work was funded in part by the US Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office, contract DE-SC0012704. This research used 8-BM, 7-ID-2, and 28-ID-2 of the National Synchrotron Light Source II and the Theory and Computational Facility and Proximal Probes Facility of the Center for Functional Nanomaterials (CFN), which are DOE Office of Science User Facilities operated for the DOE Office of Science by Brookhaven National Laboratory under contract DE-SC0012704. Beamline 7-ID-2 is funded and operated by the National Institute of Standards and Technology. We also acknowledge computing resources from Columbia University's Shared Research Computing Facility project, which is supported by NIH Research Facility Improvement Grant 1G20RR030893-01, and associated funds from the New York State Empire State Development, Division of Science Technology and Innovation (NYSTAR) Contract C090171, both awarded on April 15, 2010. The research used the Scientific Data and Computing Center at Brookhaven National Laboratory under contract DE-SC0012704. K.S. and D.A.S. would like to acknowledge the financial support by ICL Group. We thank Yusuf Celebi for technical support. D.L. thanks Dr. John Vinson for helpful discussions. C.C. S.Y. N.A. A.U. D.L. and F.W. conceived the idea and designed the project. C.K. J.S.S. H.G. and A.U. performed structural calculations and analyses. M.R.C. performed the spectrum calculations. M.R.C. and C.C. performed machine learning analysis. K.S. and D.A.S. performed the synthesis of argyrodite electrolytes. C.C. performed the electrochemistry measurements. S.L. and K.C. performed the XRD and SEM measurements. C.C. S.-M.B. Y.D. and C.W. performed XAS measurements. X.T. performed XPS measurements. C.C. M.R.C. A.U. and D.L. co-wrote the manuscript. All authors discussed the results and contributed to the manuscript. The authors declare no competing interests.

FundersFunder number
ICL Group
U.S. Department of Energy
National Institute of Standards and Technology
Columbia University
Office of Science
New York State Empire State Development
Brookhaven National Laboratory
Wind Energy Technologies Office7-ID-2, 28-ID-2, DE-SC0012704
Empire State Development's Division of Science, Technology and InnovationC090171
National Institutes of Health1G20RR030893-01

    Keywords

    • Density Functional Theory
    • lithium ion batteries
    • lithium phophorus sulfide
    • machine learning
    • solid electrolyte
    • X-ray absorption spectroscopy

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