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PEMD: a high-throughput simulation and analysis framework for solid polymer electrolytes

  • Shendong Tan
  • , Bochun Liang
  • , Dexin Lu
  • , Chaoyuan Ji
  • , Wenke Ji
  • , Zihui Li
  • , Tingzheng Hou*
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

5 Downloads (CityUHK Scholars)

Abstract

Solid polymer electrolytes exhibit limitations in room-temperature ionic conductivity and electrochemical stability. While molecular simulations and electronic-structure theory are able to sample these key properties at the molecular scale, the field currently lacks integrated, automated tools for end-to-end assessment. We introduce polymer electrolyte modeling and discovery (PEMD), an open-source Python framework that unifies polymer construction, force field parameterization, multiscale simulation, and property analysis for polymer electrolytes. The comprehensive analysis suite spans transport properties, transport mechanisms, and electrochemical stability. PEMD achieves a 100% success rate in constructing a collection of 656 homopolymers. The automated molecular dynamics workflow reproduces experimental ionic conductivities for 18 reported systems (Spearman ρ = 0.819; MAE = 0.684 in log 10 (S cm−1)). Specifically, for poly(ethylene oxide)/LiTFSI electrolytes, PEMD captures the canonical non-monotonic dependence of ionic conductivity on salt concentration with built-in default settings. The workflow is further applied at scale to compute ionic conductivities for 200 polymer electrolytes. Moreover, automated oxidation window screening on 15 representative polymer electrolytes recovers experimental rankings for the oxidation potential (Spearman ρ = 0.754; MAE = 0.473 V). With standardized protocols and traceable workflows, PEMD provides a reliable platform for high-throughput screening and data-driven design of solid polymer electrolytes. © 2026 The Author(s). Published by the Royal Society of Chemistry.
Original languageEnglish
Pages (from-to)193-202
Number of pages10
JournalDigital Discovery
Volume5
Issue number1
Online published12 Dec 2025
DOIs
Publication statusPublished - 1 Jan 2026

Funding

This work was supported by the National Natural Science Foundation of China (22409121), the Natural Science Foundation of Guangdong Province (2025A1515012161), Shenzhen All-Solid-State Lithium Battery Electrolyte Engineering Research Centre Upgrade Project (XMHT20240108008), the Shenzhen Technical Plan Project (JCYJ20240813112111015), the Shenzhen Stable Support Program for Higher Education Institutions (WDZC20231126215806001).

Publisher's Copyright Statement

  • This full text is made available under CC-BY-NC 3.0. https://creativecommons.org/licenses/by-nc/3.0/

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