Buried No longer: recent computational advances in explicit interfacial modeling of lithium-based all-solid-state battery materials

All-solid-state ceramic batteries with Li metal anodes promise substantial gains in energy density, owing to the metal’s high theoretical capacity and low reduction potential, as well as enhanced safety. However, realizing these benefits requires optimization of buried grain boundaries and interfaces within and between a cell’s bulk components, through intentionally designed interfaces, targeted grain boundary engineering, rational synthesis strategies, and beyond. In this Review, we examine recent atomistic simulations that provide insights into such solutions by elucidating ion transport, electron transfer, and chemical reactivity in solid state electrolyte grain boundaries, cathode | electrolyte interfaces, cathode | cathode grain boundaries, and electrolyte interfaces in anode-free solid-state batteries. We also discuss the advantages and limitations of the various computational methods applied. Lastly, we highlight universal machine learning potentials, challenging datasets, and opportunities for tighter integration with experiments, all of which broaden the scope of modeling. These developments enable unprecedented large-scale simulations of buried solid | solid interfaces, potentially accelerating progress to understand and improve ASSB performance in silico .

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Publication Details

Journal
Frontiers in Energy Research
Published
2025-08-13
DOI
https://doi.org/10.3389/fenrg.2025.1621807
Citations
2
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
1.04

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article

Buried No longer: recent computational advances in explicit interfacial modeling of lithium-based all-solid-state battery materials

Julia H. Yang, Amanda Whai Shin Ooi, Xinqiang Rao
2 citations
Frontiers in Energy Research
Machine Learning in Materials Science
1.04
article

Buried No longer: recent computational advances in explicit interfacial modeling of lithium-based all-solid-state battery materials

Julia H. Yang, Amanda Whai Shin Ooi, Xinqiang Rao
article en
2 citations

Abstract

All-solid-state ceramic batteries with Li metal anodes promise substantial gains in energy density, owing to the metal’s high theoretical capacity and low reduction potential, as well as enhanced safety. However, realizing these benefits requires optimization of buried grain boundaries and interfaces within and between a cell’s bulk components, through intentionally designed interfaces, targeted grain boundary engineering, rational synthesis strategies, and beyond. In this Review, we examine recent atomistic simulations that provide insights into such solutions by elucidating ion transport, electron transfer, and chemical reactivity in solid state electrolyte grain boundaries, cathode | electrolyte interfaces, cathode | cathode grain boundaries, and electrolyte interfaces in anode-free solid-state batteries. We also discuss the advantages and limitations of the various computational methods applied. Lastly, we highlight universal machine learning potentials, challenging datasets, and opportunities for tighter integration with experiments, all of which broaden the scope of modeling. These developments enable unprecedented large-scale simulations of buried solid | solid interfaces, potentially accelerating progress to understand and improve ASSB performance in silico .

Frontiers in Energy ResearchVol. 13
Georgia Institute of Technology (US), KLA (United States) (US)
Georgia Institute of Technology
Openalex Percentile: Top 23%
Machine Learning in Materials Science
1.04
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Buried No longer: recent computational advances in explicit interfacial modeling of lithium-based all-solid-state battery materials — Julia H. Yang, Amanda Whai Shin Ooi, et al. · Frontiers in Energy Research (2025) | TGRS Research Map | TGRS