High Precision Conductance Modulation in CuCrP2S6 Synaptic Devices for Enhanced Neuromorphic Computing

神经形态工程学 材料科学 电导 调制(音乐) 记忆电阻器 光电子学 纳米技术 人工神经网络 电子工程 计算机科学 人工智能 凝聚态物理 物理 声学 工程类
作者
Xin Cheng,Zhipeng Zhong,Yu Zhuang,Wan Wang,Qianyi Yang,Xiang Li,Wu Shi,Xiangjian Meng,Yanan Cao,Jianlu Wang,Junhao Chu,Hai Huang
出处
期刊:Advanced Functional Materials [Wiley]
标识
DOI:10.1002/adfm.202504017
摘要

Abstract Artificial synapses are essential components for realizing neuromorphic computing at the physical level. Although numerous artificial synaptic devices have been fabricated in recent years, their performance is often limited by their resistance state modulation capabilities and stability. Developing artificial synaptic devices with a high number of intermediate states, excellent linearity, and ultralow power consumption remains a challenge. This work presents a neuromorphic synaptic device based on a van der Waals layered ionic conductor material, CuCrP 2 S 6 (CCPS). By precisely controlling the ionic conductivity of the device, it exhibits exceptional biomimetic synaptic behaviors, including long‐term potentiation (LTP) and depression (LTD) with up to 8000 intermediate states (13‐bit), an exceptional nonlinearity of <0.31, and operating energy consumption of <45 pJ per pulse. Importantly, the LTP and LTD behaviors demonstrate outstanding stability, sustaining reliable modulation over 32 cycles. A convolutional neural network (CNN) based on the device's synaptic performance achieves recognition accuracy approaching full precision simulation in image recognition tasks. Additionally, the device shows significant advantages in processing complex auditory signals, achieving a recognition accuracy of 96.4% for sound signals, highlighting its potential in complex sound recognition applications.
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