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光伏发电技术 储能系统 GaN器件 深度学习 ★ 5.0

基于可重构有机光伏器件的视觉突触

Visual synapse based on reconfigurable organic photovoltaic cell

作者 Xiangrong Pu1Fan Shu2Qifan Wang1Gang Liu2Zhang Zhang1
期刊 半导体学报
出版日期 2025年1月
卷/期 第 46 卷 第 2 期
技术分类 光伏发电技术
技术标签 储能系统 GaN器件 深度学习
相关度评分 ★★★★★ 5.0 / 5.0
关键词 Xiangrong Pu Fan Shu Qifan Wang Gang Liu Zhang Zhang 半导体学报(英文版) Journal of Semiconductors
语言:

中文摘要

受大脑分层协同处理视觉信息的启发,本文利用PM6:Y6体系优异的光响应特性,构建了一种垂直结构的光可调有机忆阻器,系统研究了其阻变特性、光电探测能力及光突触行为模拟。该器件实现了稳定的渐进式电阻调控,成功模拟了电压控制的长时程增强/抑制(LTP/LTD)及多种光电协同调节的突触可塑性,并仿真实现了人类视觉神经系统的图像感知与识别功能。以非易失性Au/PM6:Y6/ITO忆阻器作为人工突触与神经元模型,构建了分层协同处理的SLP-CNN级联神经网络,利用其线性可调光电导特性实现网络权重更新,图像识别准确率达93.4%,较单层模型提升19.2%。

English Abstract

The hierarchical and coordinated processing of visual information by the brain demonstrates its superior ability to min-imize energy consumption and maximize signal transmission efficiency.Therefore,it is crucial to develop artificial visual synapses that integrate optical sensing and synaptic functions.This study fully leverages the excellent photoresponsivity proper-ties of the PM6:Y6 system to construct a vertical photo-tunable organic memristor and conducts in-depth research on its resis-tive switching performance,photodetection capability,and simulation of photo-synaptic behavior,showcasing its excellent per-formance in processing visual information and simulating neuromorphic behaviors.The device achieves stable and gradual resis-tance change,successfully simulating voltage-controlled long-term potentiation/depression(LTP/LTD),and exhibits various photo-electric synergistic regulation of synaptic plasticity.Moreover,the device has successfully simulated the image percep-tion and recognition functions of the human visual nervous system.The non-volatile Au/PM6:Y6/ITO memristor is used as an artificial synapse and neuron modeling,building a hierarchical coordinated processing SLP-CNN cascade neural network for visual image recognition training,its linear tunable photoconductivity characteristic serves as the weight update of the net-work,achieving a recognition accuracy of up to 93.4%.Compared with the single-layer visual target recognition model,this scheme has improved the recognition accuracy by 19.2%.
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SunView 深度解读

该有机光伏忆阻器技术为阳光电源智能运维系统提供创新思路。其光电协同突触可塑性机制可应用于iSolarCloud平台的边缘智能诊断:利用光伏组件自身光响应特性实现分布式故障识别,无需额外传感器。分层协同SLP-CNN架构可优化ST储能系统的BMS电池状态预测,通过模拟神经突触的渐进式权重调节实现自适应学习,提升SOC/SOH估算精度。该技术的非易失性存储特性适合SG逆变器的MPPT算法在线优化,在光照波动场景下实现快速响应。有机材料的柔性与低成本特性为开发新型光伏板集成智能传感器提供方向,推动光储系统向感知-计算一体化演进。