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

  • Xin Cheng
  • , Zhipeng Zhong
  • , Yezhao Zhuang
  • , Wan Wang
  • , Qianyi Yang
  • , Xiang Li
  • , Wu Shi
  • , Xiangjian Meng
  • , Yanan Cao
  • , Jianlu Wang
  • , Junhao Chu
  • , Hai Huang*
  • *Corresponding author for this work
  • Fudan University
  • Anhui University of Science and Technology
  • CAS - Shanghai Institute of Technical Physics

Research output: Contribution to journalArticlepeer-review

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, 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.

Original languageEnglish
Article number2504017
JournalAdvanced Functional Materials
Volume35
Issue number42
DOIs
StatePublished - 15 Oct 2025
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • artificial intelligence
  • ionic synaptic device
  • multi-state neuromorphic computing
  • nonlinearity factor

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