TY - JOUR
T1 - High Precision Conductance Modulation in CuCrP2S6 Synaptic Devices for Enhanced Neuromorphic Computing
AU - Cheng, Xin
AU - Zhong, Zhipeng
AU - Zhuang, Yezhao
AU - Wang, Wan
AU - Yang, Qianyi
AU - Li, Xiang
AU - Shi, Wu
AU - Meng, Xiangjian
AU - Cao, Yanan
AU - Wang, Jianlu
AU - Chu, Junhao
AU - Huang, Hai
N1 - Publisher Copyright:
© 2025 Wiley-VCH GmbH.
PY - 2025/10/15
Y1 - 2025/10/15
N2 - 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, CuCrP2S6 (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.
AB - 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, CuCrP2S6 (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.
KW - artificial intelligence
KW - ionic synaptic device
KW - multi-state neuromorphic computing
KW - nonlinearity factor
UR - https://www.scopus.com/pages/publications/105004219028
U2 - 10.1002/adfm.202504017
DO - 10.1002/adfm.202504017
M3 - 文章
AN - SCOPUS:105004219028
SN - 1616-301X
VL - 35
JO - Advanced Functional Materials
JF - Advanced Functional Materials
IS - 42
M1 - 2504017
ER -