AI‐Assisted Design of 2D‐Material Electrode for Next‐Generation Wearable Aqueous Zinc Batteries

Aqueous zinc‐based batteries (ZBs), distinguished by their inherent safety, eco‐friendliness, and uncomplicated packaging, stand out as promising energy storage devices for wearable integrated systems. Two‐dimensional (2D) materials, characterized by their sheet‐like nanostructure with large lateral dimensions and atomic‐level thickness, are pivotal to advanced energy storage. Despite the distinctive properties of 2D materials, their self‐agglomeration and structural volatility impede application in ZBs. This review first outlines how flexible battery architectures can be rationally designed by harnessing the mechanical compliance, ionic highways, and defect chemistry of 2D building blocks, with emphasis on flexibility, impact resistance, and wide‐temperature operation demanded by on‐body applications. Then, a comprehensive overview of advancements in artificial‐intelligence (AI)‐accelerated methods, covering data‐driven discovery of highly conductive 2D phases, AI‐tailored surface terminations, machine‐learning‐promoted electrolyte and electrode formulations that suppress dendrites and hydrogen evolution, and their practical implantations in smart factories. Furthermore, this review elaborates experimental strategies for integrating 2D nanosheets into bendable electrodes. Beyond energy storage, we discuss seamless integration of ZBs with wearable sensors and energy harvesters. This review highlights the challenges and prospects for the development of ZBs in wearable integrated systems and offers perspectives on future opportunities from the integration of ZBs with machine learning.