整流器(神经网络)
电子线路
材料科学
晶体管
电气工程
CMOS芯片
光电子学
精密整流器
控制重构
电压
计算机科学
工程类
嵌入式系统
功率因数
随机神经网络
机器学习
循环神经网络
人工神经网络
作者
Zhe Sheng,Yue Wang,Wennan Hu,Haoran Sun,Jianguo Dong,Rui Yu,David Wei Zhang,Peng Zhou,Zengxing Zhang
出处
期刊:Nano Research
[Springer Science+Business Media]
日期:2022-08-11
卷期号:16 (1): 1252-1258
被引量:17
标识
DOI:10.1007/s12274-022-4724-5
摘要
The unique features of ambipolar two-dimensional materials open up a great opportunity to build gate-programmable devices for reconfigurable circuit applications, e.g., PN junctions for rectifier circuits. However, current-reported rectifier circuits usually consist of one gate-programmable PN junction as the rectifier and one resistor as the load, which are not conductive to voltage output and large-scale integration. Here we propose an approach of complementary gate-programmable PN junctions to assemble reconfigurable rectifier circuit, which include two symmetric back-to-back black phosphorus (BP)/hexagonal boron nitride (h-BN)/graphene heterostructured semi-gate field-effect transistors (FETs) and perform complementary NP and PN junction like complementary metal-oxide-semiconductor (CMOS) circuit. The investigation exhibits that the circuit can effectively reconfigure the circuit with/without rectifying ability, and can process alternating current (AC) signals with the frequency prior 1 KHz and reconfiguration speed up to 25 µs. We also achieve the reconfigurable rectifier circuit memory via complementary semi-floating gate FETs configuration. The complementary configuration here should be of low output impedance and low static power consumption, being beneficial for effective voltage output and large-scale integration.
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