Cutting-Edge Developments at the Interface of Inorganic Solid-State Electrolytes

Yi Chen, Ji Qian*, Ke Wang, Li Li, Feng Wu, Renjie Chen*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

1 Citation (Scopus)

Abstract

Inorganic solid-state electrolytes (ISEs) are critical components of solid-state batteries (SSBs), and their interfacial properties play a decisive role in battery performance. This paper systematically reviews the recent advances in the interfaces of ISEs. It begins by defining and classifying ISEs—encompassing oxides, sulfides, and halides—while highlighting their fundamental characteristics, potential applications, and existing interface challenges. The discussion extends to the composition, structure, and reaction phenomena at the interfaces of SSBs, focusing on how these factors influence internal resistance, cycling stability, and safety. We detail advanced microscopic and spectroscopic techniques employed to investigate interfacial microstructures and chemical properties, as well as electrochemical impedance spectroscopy and nuclear magnetic resonance for electrical and structural analysis, while also highlighting emerging modalities for interface characterization in SSBs. Additionally, we explore the role of informatics strategies, particularly high-throughput computing and machine learning, in predicting interfacial stability, calculating ionic transport properties, and screening new materials to optimize interface engineering. Despite noteworthy progress in understanding ISE interfaces, challenges remain that hinder the commercialization of SSBs. Future research efforts should prioritize the optimization of interfacial structures and properties through multi-scale and multi-technique approaches to further accelerate SSB development.

Original languageEnglish
JournalAdvanced Materials
DOIs
Publication statusAccepted/In press - 2025

Keywords

  • high-throughput experiments
  • inorganic solid-state electrolyte
  • interface characterization method
  • machine learning
  • solid-state battery interface

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