神经形态工程学
材料科学
晶体管
图像传感器
光电子学
纳米技术
人工智能
人工神经网络
计算机科学
电气工程
工程类
电压
作者
Tu Zhao,Wenbo Yue,Qunrui Deng,Wenjie Chen,Cheng‐Ming Luo,Ruhong Zhou,Meng Sun,Xueming Li,Yujue Yang,Nengjie Huo
出处
期刊:PubMed
日期:2025-04-15
卷期号:: e2419208-e2419208
标识
DOI:10.1002/adma.202419208
摘要
In commercial artificial vision system (AVS), the sensing, storage, and computing units are usually physically separated due to their architecture and performance gaps, which thus increases the volume, complexity, and energy loss. This work develops a neuromorphic transistor integrating these different modules within one single device. Leveraging the gate-tunable out-of-plane electric field, the device achieves the multi-mode integration of photo-sensor, optical memory, and visual synapse. When operating at negative top gate voltage (VTG), a strong photo-gating effect enables highly sensitive photo-response with responsivity of ≈6.515 kA W-1 and detectivity up to ≈3.92 × 1014 Jones. Due to the charge storage effect, it can also act as a non-volatile multi-level (>4 bits) optical memory with a long endurance of over 10 000 s and a high writing/erasing ratio of up to 106. At zero or positive VTG, the transistor switches to visual synapse mode with neuromorphic computing capability, providing a pathway for complex biological learning and flexible synaptic plasticity. By further combining the synaptic plasticity with an artificial neural network (ANN), it achieves precise image recognition and classification with an accuracy of up to 95.26%. This work develops a multi-mode transistor that integrates key components of an AVS, addressing the existing challenges of all-in-one integration and manufacturing complexity.
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