Study of Void Evolution in Lithium Solid‐State Batteries: Integrating High‐Throughput Phase‐Field Modeling, Experimental Validation, and Machine Learning

Abstract This study develops a coupled mechanical‐electrochemical multiphase‐field model to describe the evolution of interface voids during the discharge of solid‐state lithium batteries. The model accounts for void collapse induced by the viscoplastic flow of lithium metal under stacking forces and incorporates the microscopic mechanisms of vacancy formation, diffusion, and aggregation, revealing the relationship between vacancy accumulation and void growth. It also accurately captures the effect of stress on vacancy aggregation. Using the Butler‐Volmer equation, the study explores the dynamic shrinkage of voids during the electrochemical stripping process at the interface. Based on this model, the synergistic effects of stacking force and external current on void formation and evolution are systematically examined. Additionally, high‐throughput phase‐field simulations, experimental validation, and machine learning techniques are employed to analyze void growth patterns in different electrolyte materials under varying operating conditions. The results show that in the Li‐LLZO system, void growth is primarily influenced by the combined effects of stacking pressure and current density, whereas in the Li‐Argyrodite system, stacking pressure plays a more dominant role. These findings deepen the understanding of void evolution in solid‐state batteries and provide a quantitative foundation for optimizing battery operation and enhancing interface stability.

Authors

Institutions

Publication Details

Journal
Advanced Energy Materials
Published
2025-06-08
DOI
https://doi.org/10.1002/aenm.202501616
Citations
7
Primary Topic
Advancements in Battery Materials
Type
article
Field-Weighted Citation Impact
5.11

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Study of Void Evolution in Lithium Solid‐State Batteries: Integrating High‐Throughput Phase‐Field Modeling, Experimental Validation, and Machine Learning

Jiashun Shi, Lin Chen, Haowen Gao, Ming‐Sheng Wang et al.
7 citations
Advanced Energy Materials
Advancements in Battery Materials
5.11
article

Study of Void Evolution in Lithium Solid‐State Batteries: Integrating High‐Throughput Phase‐Field Modeling, Experimental Validation, and Machine Learning

Jiashun Shi, Lin Chen, Haowen Gao, Ming‐Sheng Wang, Yu Wang
article en
7 citations

Abstract

Abstract This study develops a coupled mechanical‐electrochemical multiphase‐field model to describe the evolution of interface voids during the discharge of solid‐state lithium batteries. The model accounts for void collapse induced by the viscoplastic flow of lithium metal under stacking forces and incorporates the microscopic mechanisms of vacancy formation, diffusion, and aggregation, revealing the relationship between vacancy accumulation and void growth. It also accurately captures the effect of stress on vacancy aggregation. Using the Butler‐Volmer equation, the study explores the dynamic shrinkage of voids during the electrochemical stripping process at the interface. Based on this model, the synergistic effects of stacking force and external current on void formation and evolution are systematically examined. Additionally, high‐throughput phase‐field simulations, experimental validation, and machine learning techniques are employed to analyze void growth patterns in different electrolyte materials under varying operating conditions. The results show that in the Li‐LLZO system, void growth is primarily influenced by the combined effects of stacking pressure and current density, whereas in the Li‐Argyrodite system, stacking pressure plays a more dominant role. These findings deepen the understanding of void evolution in solid‐state batteries and provide a quantitative foundation for optimizing battery operation and enhancing interface stability.

Advanced Energy MaterialsVol. 15(32)
Xiamen University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Guangdong Province
Openalex Percentile: Top 4%
Advancements in Battery Materials
5.11
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.