Insights into interfacial reactions between Li-argyrodite solid electrolyte and lithium metal via machine learning-based molecular dynamics

Lithium argyrodite electrolyte is widely regarded as one of the most promising solid electrolytes due to its high Li-ion conductivity, non-flammability and other favourable properties. Nevertheless, it becomes thermodynamically unstable in contact with metallic lithium, resulting in the formation of a solid electrolyte interphase (SEI) containing hazardous species, while the intrinsic mechanisms remain unknown. This study aims to elucidate atomistic insights into the interfacial interactions, charge transfer and amorphous structural evolution within the Li/Li 6 PS 5 Cl/Li symmetric cell. Machine learning-based molecular dynamics (MLMD), trained using data from first-principles calculations, is employed to perform isothermal simulations at 300 and 350 K, respectively. Comprehensive investigations into interfacial reactions are conducted to reveal the spatiotemporal distribution of reduction reaction products of PS n 3− groups and the fraction of reduction reactions. Simultaneously, the oxidation of lithium atoms is observed in the metallic anode, particularly in regions adjacent to the central electrolyte. Additionally, the structural evolution of the symmetric cell is characterized by analyzing atomic trajectories and radial distribution functions. A two-stage Li-ion diffusion process is identified, featuring an initially rapid diffusion rate accompanied by a pronounced charge difference between the Li metal and the electrolyte, followed by a quasi-steady slower diffusion stage with a gradually diminished charge difference. Upon elevating the temperature from 300 to 350 K, both the reduction reactions and Li-ion migration are accelerated, as evidenced by the greater amount of reduction products and the higher diffusion coefficient and conductivity of Li-ions.

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Publication Details

Journal
Journal of Energy Storage
Published
2026-05-22
DOI
https://doi.org/10.1016/j.est.2026.122769
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
0.00

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article

Insights into interfacial reactions between Li-argyrodite solid electrolyte and lithium metal via machine learning-based molecular dynamics

Kai Luo, Ruitian He
Journal of Energy Storage
Machine Learning in Materials Science
article

Insights into interfacial reactions between Li-argyrodite solid electrolyte and lithium metal via machine learning-based molecular dynamics

Kai Luo, Ruitian He
article en

Abstract

Lithium argyrodite electrolyte is widely regarded as one of the most promising solid electrolytes due to its high Li-ion conductivity, non-flammability and other favourable properties. Nevertheless, it becomes thermodynamically unstable in contact with metallic lithium, resulting in the formation of a solid electrolyte interphase (SEI) containing hazardous species, while the intrinsic mechanisms remain unknown. This study aims to elucidate atomistic insights into the interfacial interactions, charge transfer and amorphous structural evolution within the Li/Li 6 PS 5 Cl/Li symmetric cell. Machine learning-based molecular dynamics (MLMD), trained using data from first-principles calculations, is employed to perform isothermal simulations at 300 and 350 K, respectively. Comprehensive investigations into interfacial reactions are conducted to reveal the spatiotemporal distribution of reduction reaction products of PS n 3− groups and the fraction of reduction reactions. Simultaneously, the oxidation of lithium atoms is observed in the metallic anode, particularly in regions adjacent to the central electrolyte. Additionally, the structural evolution of the symmetric cell is characterized by analyzing atomic trajectories and radial distribution functions. A two-stage Li-ion diffusion process is identified, featuring an initially rapid diffusion rate accompanied by a pronounced charge difference between the Li metal and the electrolyte, followed by a quasi-steady slower diffusion stage with a gradually diminished charge difference. Upon elevating the temperature from 300 to 350 K, both the reduction reactions and Li-ion migration are accelerated, as evidenced by the greater amount of reduction products and the higher diffusion coefficient and conductivity of Li-ions.

Journal of Energy StorageVol. 169
Shanghai Jiao Tong University (CN), University College London (GB), Tsinghua University (CN)
National Natural Science Foundation of China, Engineering and Physical Sciences Research Council
Openalex Percentile: Top 11%
Machine Learning in Materials Science
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