In-Plane Anisotropic Two-Dimensional ReSe<sub>2</sub> Optoelectronic Memristor for a Polarization-Sensitive Neuromorphic Vision System

A polarization-sensitive neuromorphic vision system (PNVS) that synchronously possesses the capacities of polarized light perception and neuromorphic computing enables the detection of potential information or hidden features. While developing a polarization-sensitive optoelectronic memristor presents an intriguing avenue for building the foundational hardware of PNVS, it has proven challenging. In this work, a polarization-sensitive optoelectronic memristor based on the in-plane anisotropic two-dimensional ReSe<sub>2</sub> is proposed. Thanks to the meticulous device structure design, the angle-dependent synaptic plasticity of the device is demonstrated. Further, the image preprocessing and recognition functions are implemented under the circumstances of 0 and 90° polarized light, and the learning accuracy is improved from 81.1 to 86.8 and 90.4%, respectively. To reveal the mining capacity of hidden information, the surface flaw detection application is finally demonstrated through enhancement in the degree of linear polarization (DoLP). This study provides an approach to developing polarization-sensitive neuromorphic devices for future polarization vision systems used in intelligent vehicles and robot vision.

Authors

Institutions

Publication Details

Journal
ACS Nano
Published
2025-06-27
DOI
https://doi.org/10.1021/acsnano.5c08221
Citations
16
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
11.69

Funders

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

In-Plane Anisotropic Two-Dimensional ReSe2 Optoelectronic Memristor for a Polarization-Sensitive Neuromorphic Vision System

Jingyao Bian, Xiaoning Zhao, Qi Meng, Yichun Liu et al.
16 citations
ACS Nano
Advanced Memory and Neural Computing
11.69
article

In-Plane Anisotropic Two-Dimensional ReSe2 Optoelectronic Memristor for a Polarization-Sensitive Neuromorphic Vision System

Jingyao Bian, Xiaoning Zhao, Qi Meng, Yichun Liu, Ya Lin, Ye Tao, Zhuangzhuang Li, Zhongqiang Wang, Yongxing Zhu
article en
16 citations

Abstract

A polarization-sensitive neuromorphic vision system (PNVS) that synchronously possesses the capacities of polarized light perception and neuromorphic computing enables the detection of potential information or hidden features. While developing a polarization-sensitive optoelectronic memristor presents an intriguing avenue for building the foundational hardware of PNVS, it has proven challenging. In this work, a polarization-sensitive optoelectronic memristor based on the in-plane anisotropic two-dimensional ReSe<sub>2</sub> is proposed. Thanks to the meticulous device structure design, the angle-dependent synaptic plasticity of the device is demonstrated. Further, the image preprocessing and recognition functions are implemented under the circumstances of 0 and 90° polarized light, and the learning accuracy is improved from 81.1 to 86.8 and 90.4%, respectively. To reveal the mining capacity of hidden information, the surface flaw detection application is finally demonstrated through enhancement in the degree of linear polarization (DoLP). This study provides an approach to developing polarization-sensitive neuromorphic devices for future polarization vision systems used in intelligent vehicles and robot vision.

ACS NanoVol. 19(27)
Northeast Normal University (CN), Integrated Optoelectronics (Norway) (NO), Bohai University (CN)
National Natural Science Foundation of China, Higher Education Discipline Innovation Project, National Science Fund for Distinguished Young Scholars
Affordable and clean energy
Openalex Percentile: Top 1%
Advanced Memory and Neural Computing
11.69
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.