Optoelectronic Synergy Reservoir Computing System Based on CuI-TiO <sub> <i>x</i> </sub> Heterojunction Memristor for High Precision Image Processing

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/TiOx/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 TiOx 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.

Authors

Institutions

Publication Details

Journal
ACS Applied Electronic Materials
Published
2026-04-13
DOI
https://doi.org/10.1021/acsaelm.6c00484
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Lei Fan, Guangdong Zhou, Jinze Li, Xiude Yang et al.
ACS Applied Electronic Materials
Advanced Memory and Neural Computing
article

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

Lei Fan, Guangdong Zhou, Jinze Li, Xiude Yang, Bo Wu, Xiuxia Wang, Siqi Luo, Ping Li, Xin Su
article en

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/TiOx/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 TiOx 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.

ACS Applied Electronic MaterialsVol. 8(8)
Southwest University (CN), Zunyi Normal College (CN), Frontier Science Foundation (CH), Department of Physics, Mathematics and Informatics (BY), Shanghai Center for Brain Science and Brain-Inspired Technology (CN), Xi'an Jiaotong University (CN)
National Natural Science Foundation of China, Chongqing Graduate Student Research Innovation Project, Fundamental Research Funds for Central Universities of the Central South University
Openalex Percentile: Top 20%
Advanced Memory and Neural Computing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.