Highly sensitive and stable beta-Ga2O3 DUV phototransistor with local back-gate structure and its neuromorphic application
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作者
Li, Xiao-Xi; Zeng, Guang; Li, Yu-Chun; Yu, Qiu-Jun; Liu, Meng-Yang; Zhu, Li-Yuan; Liu, Wenjun; Yang, Ying-Guo; Zhang, David Wei; Lu, Hong-Liang
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刊物名称
NANO RESEARCH
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年、卷、文献号
2022, 15, 1998-0124
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关键词
Li, Xiao-Xi; Zeng, Guang; Li, Yu-Chun; Yu, Qiu-Jun; Liu, Meng-Yang; Zhu, Li-Yuan; Liu, Wenjun; Yang, Ying-Guo; Zhang, David Wei; Lu, Hong-Liang
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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 beta-Ga2O3, in present work, high-performance beta-Ga2O3 phototransistors with local back-gate structure were experimentally demonstrated. The phototransistor shows excellent DUV photoelectrical performance with a high responsivity of 1.01 x 10(7) A/W, a high external quantum efficiency of 5.02 x 10(9)%, a sensitive detectivity of 2.98 x 10(15) Jones, and a fast rise time of 0.2 s under 250 nm illumination. Besides, first-principles calculations reveal the decent stability of beta-Ga2O3 nanosheet against oxidation and humidity without significant performance degradations. Additionally, the hexagonal boron nitride (h-BN)/beta-Ga2O3 phototransistor can behave as a photonic synapse with ultralow power consumption of similar to 9.6 fJ per spike, which shows its potential for neuromorphic computing tasks such as facial recognition. This beta-Ga2O3 phototransistor will provide a perspective for the next generation optoelectrical systems.
