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您的检索式：作者名="Alberto Libanori"
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| 1 | Triboelectric Nanogenerator Enabled Smart Shoes for Wearable Electricity Generation显示文摘The parallel evolution of wearable electronics,artificial intelligence,and fifth-generation wireless technology has created a technological paradigm with the potential to change our lives profoundly.Despite this,addressing limitations linked to continuous,sustainable,and pervasive powering of wearable electronics remains a bottleneck to overcome in order to maximize the exponential benefit that these technologies can bring once synergized.A recent groundbreaking discovery has demonstrated that by using the coupling effect of contact electrification and electrostatic induction,triboelectric nanogenerators(TENGs)can efficiently convert irregular and low-frequency passive biomechanical energy from body movements into electrical energy,providing an infinite and sustainable power source for wearable electronics.A number of human motions have been exploited to properly and efficiently harness this energy potential,including human ambulation.Shoes are an indispensable component of daily wearing and can be leveraged as an excellent platform to exploit such kinetic energy.In this article,the latest representative achievements of TENG-based smart electricity-generating shoes are comprehensively reviewed.We summarize ways in which not only can biomechanical energy be scavenged via ambulatory motion,but also biomonitoring of health parameters via tracking of rhythm and strength of pace can be implemented to aid in theranostic fields.This work provides a systematical review of the rational structural design,practical applications,scenario analysis,and performance evaluation of TENG-based smart shoes for wearable electricity generation.In addition,the perspective for future development of smart electricity-generation shoes as a sustainable and pervasive energy solution towards the upcoming era of the Internet of Things is discussed. | Yongjiu Zou Alberto Libanori Jing Xu Ardo Nashalian Jun Chen | 2020 | Research2020，，1： | 6 |
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