Kesterite-based optoelectronic synaptic memristors: a mini-review on material design and neuromorphic application

With the rapid development of big data and artificial intelligence, the conventional Von Neumann architecture faces increasingly prominent issues of separation of storage and computing as well as high energy consumption, which severely hinder the progress of next-generation intelligent computing. Memristors, serving as fundamental components that enable in-memory computing and brain-inspired neuromorphic computing, naturally possess intrinsic benefits, namely high-density storage, smoothly adjustable conductance, and low power consumption, thus emerging as promising solutions to break through this bottleneck. Among various resistive switching materials, kesterite-based chalcogenides have become the promising choice for optoelectronic synaptic memristors due to their superior optoelectronic characteristics, rich elemental availability, green nature, and economic viability. This work concisely summarizes the research progress of kesterite-based optoelectronic synaptic memristors in terms of resistive switching performance optimization, synaptic behavior simulation, and neuromorphic applications, focusing on the effects of resistive switching layer thickness, elemental composition, heterojunction and composite structures, electrode engineering, as well as testing environment and operating modes. Furthermore, it discusses the current challenges and future development trends, providing an important guideline for designing, optimizing, and practically deploying high-performance neuromorphic devices based on kesterite.This review comprehensively summarizes various optimization strategies (thickness, composition, structure, electrode, environment, operation mode), synaptic behavior simulation, neuromorphic applications, and key challenges for emerging kesterite-based optoelectronic synaptic memristors.