Self‐Powered Photonic Synaptic Device Based on ZnO/P3HT Microwires for Energy‐Efficient Neuromorphic Computing

ABSTRACT Artificial synapses are core components of neuromorphic systems emulating neural functions, yet many existing devices suffer from high power consumption and limited mechanical flexibility. Here, we report a self‐powered flexible photonic synaptic device based on a ZnO/poly(3‐hexylthiophene) (P3HT) composite microwire. The type‐II ZnO/P3HT heterojunction generates an intrinsic electric field, enabling efficient photo‐generated charge separation at 0 V bias and supporting the emulation of key synaptic plasticity, including short‐term memory, long‐term memory, and spike‐timing‐dependent plasticity. It achieves recognition accuracies of 92.0%, 88.0%, and 81.4% at noise levels of 0%, 30%, and 60%, respectively, after 3000 training epochs at 0 V bias. The device maintains stable performance after 2000 bending cycles. With the integration of self‐powered operation, mechanical flexibility, and robust noise tolerance, this ZnO/P3HT microwire photonic synaptic device holds great promise for low‐power neuromorphic systems, particularly in wearable electronics, flexible robotics, and vision‐based intelligent devices.

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Publication Details

Journal
Laser & Photonics Review
Published
2026-07-27
DOI
https://doi.org/10.1002/lpor.71637
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
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article

Self‐Powered Photonic Synaptic Device Based on ZnO/P3HT Microwires for Energy‐Efficient Neuromorphic Computing

Shun‐Xin Li, Mei‐Yan Xu, Bo Zou, Hai Wang et al.
Laser & Photonics Review
Advanced Memory and Neural Computing
article

Self‐Powered Photonic Synaptic Device Based on ZnO/P3HT Microwires for Energy‐Efficient Neuromorphic Computing

Shun‐Xin Li, Mei‐Yan Xu, Bo Zou, Hai Wang, Yue Wang, Yingli Ma, Jin‐Cheng Lei, Hongyi Zhao, Xin Chen
article en

Abstract

ABSTRACT Artificial synapses are core components of neuromorphic systems emulating neural functions, yet many existing devices suffer from high power consumption and limited mechanical flexibility. Here, we report a self‐powered flexible photonic synaptic device based on a ZnO/poly(3‐hexylthiophene) (P3HT) composite microwire. The type‐II ZnO/P3HT heterojunction generates an intrinsic electric field, enabling efficient photo‐generated charge separation at 0 V bias and supporting the emulation of key synaptic plasticity, including short‐term memory, long‐term memory, and spike‐timing‐dependent plasticity. It achieves recognition accuracies of 92.0%, 88.0%, and 81.4% at noise levels of 0%, 30%, and 60%, respectively, after 3000 training epochs at 0 V bias. The device maintains stable performance after 2000 bending cycles. With the integration of self‐powered operation, mechanical flexibility, and robust noise tolerance, this ZnO/P3HT microwire photonic synaptic device holds great promise for low‐power neuromorphic systems, particularly in wearable electronics, flexible robotics, and vision‐based intelligent devices.

Laser & Photonics Review
Jilin University (CN), State Key Laboratory on Integrated Optoelectronics (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 16%
Advanced Memory and Neural Computing
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Self‐Powered Photonic Synaptic Device Based on ZnO/P3HT Microwires for Energy‐Efficient Neuromorphic Computing — Shun‐Xin Li, Mei‐Yan Xu, et al. · Laser & Photonics Review (2026) | TGRS Research Map | TGRS