光敏性
钙钛矿(结构)
量子效率
光电子学
材料科学
记忆电阻器
三元运算
计算机科学
折叠(高阶函数)
卤化物
人工神经网络
图像传感器
人工智能
电子工程
化学
工程类
程序设计语言
结晶学
无机化学
作者
Qi Chen,Tingting Han,Jianmin Zeng,Zhilong He,Yulin Liu,Jinglin Sun,Minghua Tang,Zhang Zhang,Pingqi Gao,Gang Liu
出处
期刊:Nanomaterials
[Multidisciplinary Digital Publishing Institute]
日期:2022-06-28
卷期号:12 (13): 2217-2217
被引量:14
摘要
In-sensor computing can simultaneously output image information and recognition results through in-situ visual signal processing, which can greatly improve the efficiency of machine vision. However, in-sensor computing is challenging due to the requirement to controllably adjust the sensor’s photosensitivity. Herein, it is demonstrated a ternary cationic halide Cs0.05FA0.81MA0.14 Pb(I0.85Br0.15)3 (CsFAMA) perovskite, whose External quantum efficiency (EQE) value is above 80% in the entire visible region (400–750 nm), and peak responsibility value at 750 nm reaches 0.45 A/W. In addition, the device can achieve a 50-fold enhancement of the photoresponsibility under the same illumination by adjusting the internal ion migration and readout voltage. A proof-of-concept visually enhanced neural network system is demonstrated through the switchable photosensitivity of the perovskite sensor array, which can simultaneously optimize imaging and recognition results and improve object recognition accuracy by 17% in low-light environments.
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