Biomimetic Synapses Based on Halide Perovskites for Neuromorphic Vision Computing: Materials, Devices, and Applications

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Authors: Zhongwen Sun, Xuan Zhao, Haonan Si, Qingliang Liao, Yue Zhang
Cited by: 5
References: 198

Abstract

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.

Fields of Study & Subjects

Advanced Memory and Neural Computing Perovskite Materials and Applications Machine Learning in Materials Science

Publication details

Journal / source
Nano-Micro Letters
Publisher
Springer Science and Business Media LLC
Volume
18
Issue
1
Pages
246–246
Publication date
9 February 2026
Language
EN