响应度
光电子学
光电二极管
光电探测器
神经形态工程学
材料科学
紫外线
探测器
光子学
光学
物理
计算机科学
人工神经网络
机器学习
作者
Xiaoxi Li,Guang Zeng,Yuchun Li,Qiu-Jun Yu,Meng-Yang Liu,Li‐Yuan Zhu,Wen-Jun Liu,Yingguo Yang,David Wei Zhang,Hong-Liang Lü
出处
期刊:Nano Research
[Springer Science+Business Media]
日期:2022-07-19
卷期号:15 (10): 9359-9367
被引量:29
标识
DOI:10.1007/s12274-022-4574-1
摘要
Deep ultraviolet (DUV) phototransistors are key integral of optoelectronics bearing a wide spectrum of applications in flame sensor, military detector, oil spill detection, biological sensor, and artificial intelligence fields. In order to further improve the responsivity of UV photodetectors based on β-Ga2O3, in present work, high-performance β-Ga2O3 phototransistors with local back-gate structure were experimentally demonstrated. The phototransistor shows excellent DUV photoelectrical performance with a high responsivity of 1.01 × 107 A/W, a high external quantum efficiency of 5.02 × 109%, a sensitive detectivity of 2.98 × 1015 Jones, and a fast rise time of 0.2 s under 250 nm illumination. Besides, first-principles calculations reveal the decent stability of β-Ga2O3 nanosheet against oxidation and humidity without significant performance degradations. Additionally, the hexagonal boron nitride (h-BN)/β-Ga2O3 phototransistor can behave as a photonic synapse with ultralow power consumption of ~ 9.6 fJ per spike, which shows its potential for neuromorphic computing tasks such as facial recognition. This β-Ga2O3 phototransistor will provide a perspective for the next generation optoelectrical systems.
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