Biomimetic Synapses Based on Halide Perovskites for Neuromorphic Vision Computing: Materials, Devices, and Applications - Sun, Zhongwen; Zhao, Xuan; Si, Haonan; Liao, Qingliang; Zhang, Yue (Nano-Micro Letters, 2026)
The demand for accurate perception of the physical world has led to a dramatic increase in visual sensing data, accompanied by challenges in the energy efficiency of data processing. However, conventional vision systems with separated sensor and processing units struggle to handle increasingly intricate and large-scale data. As such, a rethinking of architecture design is necessary. Inspired by human visual systems, neuromorphic vision computing systems in which computation tasks are moved partly to the sensory or memory units offer transformative solutions to these challenges. As crucial hardware support, biomimetic synapses that replicate synaptic functions and dynamics are urgent for the development of future computing, while further progress requires materials that can support synaptic weight modulation. Given their excellent optical, electrical, and ion migration properties, halide perovskite materials have emerged as promising candidates for biomimetic synapses. Here we review the latest efforts of synaptic devices based on halide perovskite materials for neuromorphic vision computing. We demonstrate the operating mechanism of perovskite synapses and introduce their potential applications in realizing neuromorphic vision computing. We address challenges and future directions related to biomimetic perovskite synapses. Highlights: 1 Insightful discussion of the unique properties of perovskite materials in terms of optical, electrical, and ion migration properties, along with extensively analysis of different categories of perovskite materials for biomimetic synapses. 2 Comprehensive exploration of the structures and working mechanisms of perovskite synapses, emphasizing their transformative opportunities in neuromorphic vision computing. 3 Prospective outlook on the approach to the performance optimization methods of synaptic devices, covering material optimization, device structure design, and external physical signal regulation.