Battery game changer: AI identifies key conditions for all-solid-state battery electrolyte materials

Battery game changer: AI identifies key conditions for all-solid-state battery electrolyte materials

https://www.eurekalert.org/news-releases/1114905

Publish Date: 2026-02-10 00:33:00

Source Domain: www.eurekalert.org

Lithium-ion batteries serve as the core energy storage devices in various industries and everyday products, including smartphones, electric vehicles, and ESS (energy storage systems). However, conventional lithium-ion batteries use liquid electrolytes, posing a risk of fire or explosion when subjected to external impact or overheating. Recent electric vehicle fire incidents have heightened concerns about their safety. As an alternative to overcome these limitations, ‘all-solid-state batteries’-which use non-flammable solid materials as electrolytes-are gaining attention as next-generation battery technology.

However, amorphous solid electrolytes-the core material for all-solid-state batteries-have faced limitations in analyzing lithium-ion transport mechanisms due to the irregularity of their internal structure. Consequently, performance improvements have been achieved empirically by altering electrolyte composition or compression conditions, making it difficult to systematically explain the causes of performance differences.

A research team led by Dr. Byungju, Lee at the Computational Science Research Center of the Korea Institute of Science and Technology (KIST, President Sang-Rok Oh) has identified key factors governing lithium ion movement in amorphous solid electrolytes through AI-based atomic simulations. The team analyzed lithium-ion movement by distinguishing it into ‘ease of movement between sites’ and ‘connectivity of movement paths’. They confirmed that overall performance is more significantly influenced by the difficulty of ions moving from one site to the next than by path connectivity.

In fact, while ion conductivity performance varied by up to fivefold depending on lithium ion mobility, the effect of pathway connectivity was limited to approximately a twofold difference. This provides a quantitative basis for interpreting performance variations that were previously difficult to explain due to…

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