Theoretical systems of triboelectric nanogenerators

摩擦电效应 纳米发生器 材料科学 电容 电容器 静电感应 机械能 接触带电 电压 电气工程 电容感应 整流器(神经网络) 能量收集 功率(物理) 电极 物理 工程类 计算机科学 随机神经网络 机器学习 循环神经网络 复合材料 量子力学 人工神经网络
作者
Simiao Niu,Zhong Lin Wang
出处
期刊:Nano Energy [Elsevier]
卷期号:14: 161-192 被引量:1118
标识
DOI:10.1016/j.nanoen.2014.11.034
摘要

Triboelectric nanogenerator (TENG) technology based on contact electrification and electrostatic induction is an emerging new mechanical energy harvesting technology with numerous advantages. The current area power density of TENGs has reached 313 W/m2 and their volume energy density has reached 490 kW/m3. In this review, we systematically analyzed the theoretical system of triboelectric nanogenerators. Starting from the physics of TENGs, we thoroughly discussed their fundamental working principle and simulation method. Then the intrinsic output characteristics, load characteristics, and optimization strategy is in-depth discussed. TENGs have inherent capacitive behavior and their governing equation is their V–Q–x relationship. There are two capacitance formed between the tribo-charged dielectric surface and the two metal electrodes, respectively. The ratio of these two capacitances changes with the position of this dielectric surface, inducing electrons to transfer between the metal electrodes under short circuit conditions. This is the core working mechanism of triboelectric generators and different TENG fundamental modes can be classified based on the changing behavior of these two capacitances. Their first-order lumped-parameter equivalent circuit model is a voltage source in series with a capacitor. Their resistive load characteristics have a “three-working-region” behavior because of the impedance match mechanism. Besides, when TENGs are utilized to charge a capacitor with a bridge rectifier in multiple motion cycles, it is equivalent to utilizing a constant DC voltage source with an internal resistance to charge. The optimization techniques for all TENG fundamental modes are also discussed in detail. The theoretical system reviewed in this work provides a theoretical basis of TENGs and can be utilized as a guideline for TENG designers to continue improving TENG output performance.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
传奇3应助润润轩轩采纳,获得10
刚刚
刚刚
2秒前
和谐乌龟发布了新的文献求助10
2秒前
zZ完成签到,获得积分10
2秒前
科研小白完成签到,获得积分10
2秒前
LYY发布了新的文献求助10
3秒前
wangfu完成签到,获得积分10
3秒前
ding应助Dddd采纳,获得10
4秒前
yin发布了新的文献求助10
4秒前
大模型应助张张采纳,获得10
4秒前
Akim应助吾问无为谓采纳,获得10
5秒前
5秒前
神勇的冰姬完成签到,获得积分10
6秒前
7秒前
7秒前
7秒前
7秒前
8秒前
tony完成签到,获得积分10
8秒前
Uynaux发布了新的文献求助30
8秒前
SONG完成签到,获得积分10
8秒前
SYLH应助干秋白采纳,获得10
9秒前
9秒前
风雨1210发布了新的文献求助10
10秒前
文艺书雪完成签到 ,获得积分10
10秒前
独行侠完成签到,获得积分10
10秒前
11秒前
我测你码发布了新的文献求助10
11秒前
又要起名字完成签到,获得积分10
11秒前
11秒前
11秒前
damian完成签到,获得积分10
12秒前
LiShin发布了新的文献求助10
12秒前
渝州人应助凤凰山采纳,获得10
13秒前
sweetbearm应助凤凰山采纳,获得10
13秒前
我是老大应助科研通管家采纳,获得10
13秒前
大个应助科研通管家采纳,获得10
13秒前
yizhiGao应助科研通管家采纳,获得10
13秒前
华仔应助科研通管家采纳,获得10
13秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527884
求助须知:如何正确求助?哪些是违规求助? 3108006
关于积分的说明 9287444
捐赠科研通 2805757
什么是DOI,文献DOI怎么找? 1540033
邀请新用户注册赠送积分活动 716904
科研通“疑难数据库(出版商)”最低求助积分说明 709794