Optoelectronic Synergy Reservoir Computing System Based on CuI-TiO x Heterojunction Memristor for High Precision Image Processing

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Authors: Lei Fan, Jinze Li, Xin Su, Siqi Luo, Xiuxia Wang, Xiude Yang, Ping Li, Bo Wu, Haishen Huang, Bai Tao Sun, Guangdong Zhou
Cited by: 1
References: 49

Abstract

Reservoir computing (RC) system based on photoelectronic memristors has attracted increasing attention because of its inherently nonlinearity, history-dependent dynamics, and fading memory for real-time processing complex task. However, relying on its natural relaxation process leads to the RC system with low efficiency. Here, we propose an Au/CuI/TiO x /FTO heterojunction optoelectronic synergistic memristor and demonstrate its application as a single-node physical reservoir computing (PRC) system. The device synergistically integrates oxygen-vacancy migration in TiO x with the photosensitivity of CuI, enabling precise. This approach generates rich, high-dimensional reservoir states with enhanced separability. The memristor exhibits diverse synaptic plasticity and supports over 32 distinct conductance states (>5-bits precision). Furthermore, a predictive model was established to capture device dynamics, achieving an accuracy of 82.8% for the standard RC model, while the accuracy of the heterojunction memristor-assisted RC model increased to 97.26%. The research demonstrates that heterojunction optoelectronic collaborative memristors exhibit significant potential in efficient temporal encoding and high-precision single-node PRC, providing a promising solution for edge intelligence and low-power neuromorphic hardware.

Fields of Study & Subjects

Advanced Memory and Neural Computing Neural Networks and Reservoir Computing Ferroelectric and Negative Capacitance Devices

Publication details

Journal / source
ACS Applied Electronic Materials
Publisher
American Chemical Society (ACS)
Volume
8
Issue
8
Pages
3684–3693
Publication date
13 April 2026
Language
EN