MOF‐Derived High‐Entropy Biphasic Sulfides for Zn‐I 2 ‐S Synergistic Batteries with Machine‐Learning‐Assisted Prediction and In Situ Synchrotron Spectroscopy

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Authors: Ziming Qiu, Guoqiang Yuan, Xingye Lu, Xinling Lv, Xinyu Qin, Wanchang Feng, Shuai Cao, Jin Yan, Mohsen Shakouri, Jianfei Huang, Bin He, Zheng Liu
+2 more Yecan Pi, Huan Pang
Cited by: 20
References: 31

Abstract

ABSTRACT The practical application of aqueous zinc batteries remains constrained by the intrinsic limitations of monocomponent systems, such as the shuttle effect in Zn‐I 2 batteries and the sluggish kinetics in Zn─S batteries. To overcome these limitations, we developed a Zn‐S‐I 2 synergistic battery that synergistically exploits the complementary advantages of dual redox couples. A bifunctional high‐entropy sulfide (HES) catalyst anchored on N‐doped carbon nanosheets was engineered via a surfactant‐assisted metal‐organic framework (MOF) derivatization route. The entropy‐stabilized HES forms a unique wurtzite/zincblende biphasic structure, creating abundant grain boundaries and synergistic active sites. Electrochemical studies demonstrate that the synergistic battery exhibits outstanding electrochemical performance and cycling stability. Machine learning (ML) models were established to predict electrochemical behavior under various operating conditions. Operando synchrotron‐based spectroscopy combined with theoretical calculations revealed that the biphasic HES synergistically catalyzes multi‐step conversion reactions, simultaneously lowering energy barriers and suppressing shuttle effects. This work offers new insights into high‐entropy electrocatalysts for complex multi‐step energy storage reactions.

Fields of Study & Subjects

Advanced battery technologies research Electrocatalysts for Energy Conversion CO2 Reduction Techniques and Catalysts

Publication details

Journal / source
Advanced Materials
Publisher
Wiley
Volume
38
Issue
11
Pages
e23371–e23371
Publication date
2 January 2026
Language
EN