Two-Dimensional InSe Artificial Synapses with fJ Energy Consumption

作者：Na Xu, Mengyuan Duan, Kun Zhang, Weifeng Zhang, Caihong Jia · 发表于：ACS Applied Energy Materials · 年份：2025 · DOI：10.1021/acsaem.4c03324 · 被引用次数：7 · 研究领域：Advanced Memory and Neural Computing、Phase-change materials and chalcogenides、Photoreceptor and optogenetics research

As Moore’s Law approaches its physical limits, the traditional von Neumann architecture faces challenges, and memristors offer hope as a new type of device structure. In this study, we realized the ultralow energy consumption (1.1 fJ) artificial synapse based on 2D InSe with small effective electron mass and high electron mobility. Furthermore, we simulated the synaptic behaviors of post-tetanic potentiation, classical conditioning, spike-rate-dependent plasticity (SRDP), and Bienenstock–Cooper–Munro (BCM) learning rule. This study not only provides a simulation of synaptic behavior but also achieves edge recognition in images through an effective adjustability.