journal article·2026

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

Xiankai Lin, Qian Zhang, Wenbo Li, Fang Yi, Shihong Ma, Guitian Qiu, Jianxian Yi, Jiwei Chen, Yingjie Luo, Chunlei Zhang, Guigang Zhou, Ziling Chen, Qijie Liang

Materials Horizons· Volume 13· Issue 5
Publisher page

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)/CuInP2S6 (CIPS)/Gr/h-BN/PdSe2 (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 PdSe2 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.
Source: europepmc · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Advanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices · 2D Materials and Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Songshan Lake Materials Laboratory, Songshan Lake Mat Lab, Dongguan, 523808, China

School of Materials, Shenzhen Campus of Sun Yat-sen University, No. 66, Gongchang Road, Guangming District, Shenzhen, 518107, China

School of Materials Science and Engineering, Sun Yat-sen University, Guangzhou, 510275, P. R. China

Funding

National Natural Science Foundation of China · Basic and Applied Basic Research Foundation of Guangdong Province · National Key Research and Development Program of China

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