能量收集
摩擦电效应
电容器
电气工程
整流器(神经网络)
泄漏(经济)
CMOS芯片
能量(信号处理)
计算机科学
功率(物理)
纳米发生器
材料科学
电压
工程类
物理
人工智能
随机神经网络
量子力学
人工神经网络
宏观经济学
循环神经网络
复合材料
经济
作者
Joanne Si Ying Tan,Jeong Hoan Park,Jiamin Li,Yilong Dong,Kwok Hoe Chan,Ghim Wei Ho,Jerald Yoo
出处
期刊:IEEE Journal of Solid-state Circuits
[Institute of Electrical and Electronics Engineers]
日期:2021-05-26
卷期号:56 (10): 2913-2923
被引量:12
标识
DOI:10.1109/jssc.2021.3080383
摘要
This article presents a fully energy-autonomous temperature-to-time converter (TTC), entirely powered up by a triboelectric nanogenerator (TENG) for biomedical applications. Existing sensing systems either consume too much power to be sustained by energy harvesting or have poor accuracy. Also, the harvesting of low-frequency energy input has been challenging due to high reverse leakage of a rectifier. The proposed dynamic leakage suppression full-bridge rectifier (DLS-FBR) reduces the reverse leakage current by more than 1000 $\times $ , enabling harvesting from sparse and sporadic energy sources; this enables the TTC to function with a TENG as the sole power source operating at <1-Hz human motion. Upon harvesting 0.6 V in the storage capacitor, the power management unit (PMU) activates the low-power TTC, which performs one-shot conversion of temperature to pulsewidth. Designed for biomedical applications, the TTC enables a temperature measurement range from 15 °C to 45 °C. The energy-autonomous TTC is fabricated in 0.18- $\mu \text{m}$ 1P6M CMOS technology, consuming 0.14 pJ/conversion with 0.014-ms conversion time.
科研通智能强力驱动
Strongly Powered by AbleSci AI