MOF-Derived High-Entropy Biphasic Sulfides for Zn-I₂-S Synergistic Batteries with Machine-Learning-Assisted...

The practical application of aqueous zinc batteries remains constrained by the intrinsic limitations of monocomponent systems, such as the shuttle effect in Zn-I₂ batteries and the sluggish kinetics in Zn─S batteries. To overcome these limitations, we developed a Zn-S-I₂ 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.