Unveiling the Lithium-Ion Transport Mechanism in Li2ZrCl6 Solid-State Electrolyte via Deep Learning-Accelerated Molecular Dynamics Simulations
Abstract
Lithium zirconium chlorides (LZCs) present a promising class of cost-effective solid electrolyte for next-generation all-solid-state batteries. The unique crystal structure of LZCs plays a crucial role in facilitating lithium-ion mobility, which further affects its electrochemical performance. To understand the underlying mechanism governing ion transport, we employed deep learning-accelerated molecular dynamics simulation on Li2ZrCl6 (trigonal {\alpha}- and monoclinic \b{eta}-LZC), focusing specifically on the zirconium coordination environment. Our results reveal that disordered {\alpha}-LZC exhibits the highest ionic conductivity, while \b{eta}-LZC demonstrates significantly lower conductivity, closely aligning with experimental findings. The study confirms that across all phases, lithium migration proceeds via site-to-site hopping mechanism, where variations in site residence times critically impact the overall ionic conductivity. In {\alpha}-LZCs, lithium ions prefer to anisotropically diffuse across interlayers as the result of lower energy barrier, driven primarily by collective diffusion. In contrast, lithium ions in \b{eta}-LZC primarily isotropically diffuse within intralayer, hindered by higher energy barriers and determined by individual diffusion. The variation in ZrCl62- octahedral unit softening, induced by the specific layered arrangement of zirconium atoms, emerges as a critical determinant of the energy barriers across the LZC phases. These atomic-scale insights into the transport processes provide valuable guidance for the rational design and optimization of LZCs-based electrolytes, accelerating their practical application in advanced energy storage technologies.
Keywords
Cite
@article{arxiv.2508.05598,
title = {Unveiling the Lithium-Ion Transport Mechanism in Li2ZrCl6 Solid-State Electrolyte via Deep Learning-Accelerated Molecular Dynamics Simulations},
author = {Hanzeng Guo and Volodymyr Koverga and Selva Chandrasekaran Selvaraj and Anh T. Ngo},
journal= {arXiv preprint arXiv:2508.05598},
year = {2025}
}
Comments
it has supporting information, ACS Applied Energy Materials 2025