A desert locust-inspired wavelength-selective polarization vision system using two-dimensional ferroelectric heterostructures

A bionic vision system integrates image sensing, memory, and computing capabilities, overcoming the limitations of traditional von Neumann architectures. However, integrating polarization-sensitivity and wavelength-selectivity while maintaining exceptional energy-efficiency, non-volatile and high-speed storage remains challenging for advanced application scenarios. Here, we present a bionic polarization vision system (BPVS) based on graphene (Gr)/CuInP<sub>2</sub>S<sub>6</sub> (CIPS)/Gr/h-BN/PdSe<sub>2</sub> (GCGhP) ferroelectric heterostructures, which achieves polarization-sensitive and wavelength-selective vision simulation. Optical excitation-induced ferroelectric polarization reversal confines the operational wavelength to the ultraviolet band. The anisotropy of PdSe<sub>2</sub> introduces polarization sensitivity, while the ferroelectric polarization mechanism ensures ultra-low power consumption of 0.15 pJ/7.44 fJ (optical enhancement/electrical suppression per spike). The system mimics polarimetric synaptic plasticity and realizes memory imaging at multiple polarization angles. A bionic polarization vision neural network designed for polarization image demosaicking achieves super-resolution reconstruction. Our findings provide an effective pathway for advanced and energy-efficient polarization-sensitive bionic neuromorphic computing and vision systems.

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Publication Details

Journal
Materials Horizons
Published
2025-12-09
DOI
https://doi.org/10.1039/d5mh01714a
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
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article

A desert locust-inspired wavelength-selective polarization vision system using two-dimensional ferroelectric heterostructures

Jianxian Yi, Guigang Zhou, Qijie Liang, Wenbo Li et al.
Materials Horizons
Advanced Memory and Neural Computing
article

A desert locust-inspired wavelength-selective polarization vision system using two-dimensional ferroelectric heterostructures

Jianxian Yi, Guigang Zhou, Qijie Liang, Wenbo Li, Chunlei Zhang, Jiwei Chen, Zi-Yu Chen, Yingjie Luo, Qian Zhang, Xiankai Lin, Yi Fang, Shihong Ma, Guitian Qiu
article en

Abstract

A bionic vision system integrates image sensing, memory, and computing capabilities, overcoming the limitations of traditional von Neumann architectures. However, integrating polarization-sensitivity and wavelength-selectivity while maintaining exceptional energy-efficiency, non-volatile and high-speed storage remains challenging for advanced application scenarios. Here, we present a bionic polarization vision system (BPVS) based on graphene (Gr)/CuInP<sub>2</sub>S<sub>6</sub> (CIPS)/Gr/h-BN/PdSe<sub>2</sub> (GCGhP) ferroelectric heterostructures, which achieves polarization-sensitive and wavelength-selective vision simulation. Optical excitation-induced ferroelectric polarization reversal confines the operational wavelength to the ultraviolet band. The anisotropy of PdSe<sub>2</sub> introduces polarization sensitivity, while the ferroelectric polarization mechanism ensures ultra-low power consumption of 0.15 pJ/7.44 fJ (optical enhancement/electrical suppression per spike). The system mimics polarimetric synaptic plasticity and realizes memory imaging at multiple polarization angles. A bionic polarization vision neural network designed for polarization image demosaicking achieves super-resolution reconstruction. Our findings provide an effective pathway for advanced and energy-efficient polarization-sensitive bionic neuromorphic computing and vision systems.

Materials HorizonsVol. 13(5)
Sun Yat-sen University (CN), Songshan Lake Materials Laboratory (CN)
Openalex Percentile: Top 60%
Advanced Memory and Neural Computing
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