解耦(概率)
去极化
铁电性
材料科学
光电子学
电介质
医学
工程类
控制工程
内分泌学
作者
Guangcheng Wu,F. Yu,Jiali Yi,Huawei Liu,Xiulian Fan,Cheng Li,Chenguang Zhu,Xingxia Sun,Yong Liu,Shuai Qin,Tanghao Xie,Shengman Li,Yu Zhou,Dong Li,Anlian Pan
出处
期刊:ACS Nano
[American Chemical Society]
日期:2025-05-29
卷期号:19 (22): 20980-20990
被引量:8
标识
DOI:10.1021/acsnano.5c04090
摘要
Highly sensitive sensors are critical for in-sensor computing, an ultrafast and low-power machine vision technology. However, capturing sharp images without motion blur in low-light and high-speed situations remains challenging due to weak photoresponse. Here, we present a heterostructure ferroelectric phototransistor leveraging opto-electrical decoupling for fast perception and in-sensor computing. The channel is preprogrammed to a low-resistance state via ferroelectric polarization, while light modulates the drain current through light-induced ferroelectric depolarization. This mechanism enables a record-high MoTe2-based photoresponsivity of 3.05×104 A/W by optimizing the balance between depolarization and screening fields. The sensors can perceive light pulses as short as 200 μs, achieving an operating frequency of 5 kHz and an energy consumption of 74 fJ. Utilizing a light-programmable neutral point, a 3 × 3 sensor array was developed as the optical kernel for scene-specific in-sensor computing, achieving a license plate recognition accuracy of 92.4% with significantly reduced motion blur. These results demonstrate the potential of this technology for high-speed, low-light machine vision applications.
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