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Recent Progress in Application‐Oriented Self‐Powered Microelectronics

Advanced Energy Materials

November 2023
13(47)

DOI:10.1002/aenm.202302699

Authors:

Lingfei Qi

Guizhou University

Lingji Kong

Southwest Jiaotong University

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With the rapid development of the Internet of Things (IoTs), numerous distributed wide‐area low‐power electronic devices have been utilized in various fields, such as wireless monitoring sensors and wearable electronics. Due to the dispersion and mobility of microelectronic devices, their energy supply faces serious challenges. The inconvenience and non‐environmental friendliness of using traditional centralized low entropy energy and chemical batteries to power distributed microelectronic devices are becoming increasingly prominent. Environmental energy harvesting technology with high entropy characteristics is considered an effective solution for low‐power electronic devices. This paper comprehensively reviews the recent progress in microelectronic technologies based on energy harvesting and signal sensing. First, state‐of‐the‐art micro‐power electronic devices in humans, animals, and the environment are introduced. Secondly, the available micro‐energy sources in the environmentare elaborated and summarized. Then, the principles and characteristics of ambient microenergy harvesting technologies based on different mechanisms are classified, summarized, and analyzed. In addition, this work comprehensively summarizes the applications of self‐powered micro‐electronics technology in 11 different fields, including human, animal, and environment. Finally, research challenges, technical difficulties, and research gaps in self‐powered microelectronics based on micro‐energy harvesting technology are discussed and summarized.

The architecture of the self‐powered microelectronic world.

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Applications of environmental monitoring devices. (a) Rail vibration energy harvester for intelligent transportation. Reproduced with permission.[¹¹³] Copyright 2022, Elsevier. (b) Wave energy harvester for the smart ocean. Reproduced with permission.[¹¹⁴] Copyright 2022, Elsevier. (c) Hybrid energy self‐powered sensing device for smart home. Reproduced with permission.[¹¹⁵] Copyright 2020, Elsevier. (d) Breeze‐driven TENG for smart agriculture. Reproduced with permission.[¹¹⁶] Copyright 2022, Elsevier. (e) TENG‐based vibration sensor for the smart industry. Reproduced with permission.[¹¹⁷] Copyright 2022, Elsevier. (f) Hybrid TENG‐ENG environmental monitoring sensor. Reproduced with permission.[¹¹⁸] Copyright 2021, Elsevier.

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Classification of ambient micro‐energy. The source of a) thermal energy, b) solar energy, c) mechanical energy, d) RF energy, and e) biochemical energy.

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Various energy harvesting technologies. a) Photovoltaic. b) Thermoelectric. c) RF energy harvesting. d) Biofuel cell. e) Triboelectric. f) Piezoelectric. g) Electromagnetic. h) Magnetostrictive. i) Electrostatic.

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REVIEW

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Recent Progress in Application-Oriented Self-Powered

Microelectronics

Lingfei Qi, Lingji Kong,* Yuan Wang, Juhuang Song, Ali Azam, Zutao Zhang,*

and Jinyue Yan*

With the rapid development of the Internet of Things (IoTs), numerous

distributed wide-area low-power electronic devices have been utilized in

various ﬁelds, such as wireless monitoring sensors and wearable electronics.

Due to the dispersion and mobility of microelectronic devices, their energy

supply faces serious challenges. The inconvenience and non-environmental

friendliness of using traditional centralized low entropy energy and

chemical batteries to power distributed microelectronic devices are becoming

increasingly prominent. Environmental energy harvesting technology with

high entropy characteristics is considered an eﬀective solution for low-power

electronic devices. This paper comprehensively reviews the recent progress

in microelectronic technologies based on energy harvesting and signal

sensing. First, state-of-the-art micro-power electronic devices in humans,

animals, and the environment are introduced. Secondly, the available

micro-energy sources in the environmentare elaborated and summarized.

Then, the principles and characteristics of ambient microenergy harvesting

technologies based on diﬀerent mechanisms are classiﬁed, summarized, and

analyzed. In addition, this work comprehensively summarizes the applications

of self-powered micro-electronics technology in 11 diﬀerent ﬁelds,

including human, animal, and environment. Finally, research challenges,

technical diﬃculties, and research gaps in self-powered microelectronics

based on micro-energy harvesting technology are discussed and summarized.

L. Qi, Y. Wang, J. Song

School of Mechanical Engineering

Guizhou University

Guiyang, Guizhou 550025, PR China

L. Kong, A. Azam, Z. Zhang

School of Mechanical Engineering

Southwest Jiaotong University

Chengdu 610031, China

E-mail: klj@my.swjtu.edu.cn;zzt@swjtu.edu.cn

L. Kong, A. Azam

Yibin Research Institute

Southwest Jiaotong University

Yibin 610031, P. R. China

J. Yan

Department of Building Environment and Energy Engineering

The Hong Kong Polytechnic University

Hongkong China

E-mail: jinyue.yan@mdh.se

The ORCID identiﬁcation number(s) for the author(s) of this article

can be found under https://doi.org/10.1002/aenm.202302699

DOI: 10.1002/aenm.202302699

1. Introduction

The advent of the IoTs era has pro-

moted the development of thousands

of distributed IoT nodes and wireless

sensors.[1] 5G, as the new generation of

mobile communication technology with

high speed, low latency, and large con-

nection, its rapid construction brings

the vision of the Internet of Everything

(IoE) one step closer.[2] In the rapidly

developing information age, various dis-

tributed micro-electronics such as sen-

sors are the basic hardware support to

realize the Internet of Everything. As

shown in Figure 1, many microelec-

tronic devices are distributed worldwide,

from humans to animals, land to ocean,

and rural areas to urban cities. How-

ever, the energy supply of countless dis-

tributed micropower electronic devices

is a huge challenge to achieving IoE

goals.[3,4 ] On the one hand, the grid

power supply method with low entropy,

high installation cost, and large voltage

cannot adapt to the distributed and low-

power characteristics of wide-area micro-

electronic devices.[5] Meanwhile, the tra-

ditional battery power supply has critical

shortcomings such as limited life, low reliability, and potential

environmental pollution.[6] Providing reliable, continuous, and

clean energy for these distributed micropower devices is a key dif-

ﬁculty that urgently needs to be addressed in the interconnected

world of all things.

In response to the above issues and driven by the aim of

energy conservation and emission reduction, various emerging

energy harvesting technologies are constantly emerging.[7] The

energy sources available for harvesting in the environment

are diverse, such as thermal energy,[8] solar energy,[9] radiowave

energy,[10] biochemical energy,[11] and mechanical energy.[12] Due

to the universality, low grade, and cleanliness of these microen-

ergy sources in the environment, they are considered eﬀective

alternative sources of power for distributed microelectronic

devices.[13–19 ] Correspondingly, according to diﬀerent energy

sources, environmental energy harvesting technologies can

be divided into the following main categories: thermal energy

harvesting technology,[20] solar energy harvesting technology,[21]

radio wave energy harvesting technology,[22] biochemical

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Figure 1. The architecture of the self-powered microelectronic world.

energy harvesting technology,[23] and mechanical energy har-

vesting technology.[24]

Thermal energy has received widespread attention as a re-

newable energy source due to its wide distribution and huge

energy storage. Since the discovery of thermoelectric phenom-

ena by Seebeck in 1821,[25] thermoelectric generators (TEG) have

been widely studied to recover thermal energy from the hu-

man body,[26] automobile exhaust waste heat,[27] and industrial

heat.[28] Most of the thermal energy of the human body is re-

leased in the form of heat with a total power of up to 60–180 W,

which can fully meet the power requirements of wearable elec-

tronic devices.[29] Vehicle exhaust heat is also a huge thermal

energy source, which accounts for 57–62% of the total fuel en-

ergy of the vehicle.[6] The principle of thermal energy harvest-

ing is based on the temperature diﬀerence between two ther-

moelectric materials, which drives electrons and holes to move

between the two materials to generate current. Therefore, ther-

moelectric material is the main factor aﬀecting the energy har-

vesting eﬃciency of TEG. With the continuous advancement of

thermoelectric power generation technology, TEG has been used

in smart factories,[30] smart transportation,[31] and human intel-

ligent health monitoring.[32–34 ]

Solar energy is generally divided into photovoltaic energy and

solar thermal energy. Especially, photovoltaic technology is be-

coming increasingly mature and has been widely applied and

promoted.[35] The principle of photovoltaic power generation is

based on the photoelectric eﬀect of semiconductors, which con-

verts the radiation energy of the sun into electrical energy.[36–38]

Generally, photovoltaic power generation includes standalone

photovoltaic power generation and grid-connected photovoltaic

power generation.[39] In the microelectronics world, standalone

micro photovoltaic power generation systems have been applied

in various ﬁelds, such as transportation,[40] wearable devices,[41,42]

buildings,[43] and environmental monitoring.[44]

Compared to other ambient energy sources, radio frequency

(RF) energy has a lower power density.[45] Besides, RF energy is

electromagnetic waves with diﬀerent frequency bands, which are

penetrable and widely distributed. Therefore, radio frequency en-

ergy harvesting technology has also received great attention re-

cently. The principle of RF energy harvesting technology is to

convert RF energy into electric energy and supply power for wire-

less sensor networks (WSN) and IoTs nodes.[46–48 ] Overall, the

RF energy harvesting system mainly consists of an antenna, a

matching impedance circuit, a rectiﬁer and boost circuit, and an

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energy storage device.[49] The most important component is an

antenna, which captures electromagnetic waves. Therefore, the

antenna is also a key component aﬀecting the eﬃciency of RF

energy harvesting. The development of 5G technology has pro-

moted the exponential growth of wireless network sources such

as cellular networks and Wi-Fi signals, providing excellent oppor-

tunities for advancing RF energy harvesting technology.[50,51] It

can be predicted that radio frequency energy harvesting systems

will play a huge role in many ﬁelds such as smart cities and smart

homes.[52,53 ]

Biochemical energy is another low-grade renewable energy

source that can be harvested from microbial metabolic reac-

tions in living organisms. Based on this, biofuel cells (BFC)

have been developed to convert the chemical energy of or-

ganic matter into electrical energy.[54–56] All the soil, wastew-

ater, urban, agricultural, and human waste can all be used

as fuel for BFC. Especially, human-based BFC technology has

been widely studied to convert various metabolic wastes from

the human body, such as sweat,[57] saliva,[58] urine,[59] and

tears,[60] into usable electrical energy. The electricity generated

by these biofuel cells can be used to power the biosensors of

the organism itself. Unlike traditional rigid power sources that

are large and heavy, non-invasive BFCs are lightweight, ﬂexi-

ble, and comfortable, providing an attractive alternative way to

power wearable devices.[61] BFCs have been developed in vari-

ous wearable devices such as textiles, patches, and contact lenses,

which have great application potential in biomedicine, ﬁtness,

defense, etc.[62–64 ]

In addition to the micro-energy sources mentioned above, me-

chanical energy is also a widely distributed renewable micro-

energy, including vibration energy that exists in automobile

suspensions,[65] rails,[66] and machines,[67] ubiquitous wind en-

ergy in the air,[68,69] wave energy in oceans and rivers,[ 70,71]

biomechanical energy in human and animal motion,[72–74 ] sound

energy in traﬃc environments and cities.[75,76 ] Moreover, me-

chanical energy can be converted into electrical energy through

various mechanisms, such as piezoelectric,[77] triboelectric,[78]

electromagnetic,[79] electrostatic,[80] and magnetostrictive.[81] In

recent years, wearable mechanical energy harvesting devices inte-

grated into the human body have been extensively studied. These

wearable mechanical energy harvesters can capture energy from

walking, running, jumping, joint movements, and blinking. The

harvested mechanical energy from human motion can be used to

supply power for wearable smart electronic devices and human

body monitoring sensors.[82–84 ] In addition, mechanical energy

harvesting has broad prospects in aerospace,[85] biomedicine,[86]

environmental monitoring,[87] smart cities,[88] smart oceans,[89]

and smart industries.[90]

Some researchers have summarized self-powered microelec-

tronics technology in speciﬁc ﬁelds, such as wearable devices,

transportation, and the ocean. However, these review studies do

not fully reﬂect the development of self-powered microelectron-

ics. In this review study, the latest developments in the ﬁeld

of self-powered microelectronics in various ﬁelds are compre-

hensively summarized, discussed, and analyzed in detail. First,

state-of-the-art micro-power electronic devices in humans, ani-

mals, and the environment are introduced. Secondly, the avail-

able micro-energy sources in the environment have been elabo-

rated and summarized. Then, the principles and characteristics

of ambient microenergy harvesting technologies based on diﬀer-

ent mechanisms were classiﬁed, summarized, and analyzed. In

addition, this paper comprehensively reviews and summarizes

the applications of self-powered micro-electronics technology in

11 diﬀerent ﬁelds, including human, animal, and environment.

Finally, research challenges, technical diﬃculties, and research

gaps in self-powered microelectronics based on micro-energy

harvesting technology are discussed and summarized. This pa-

per comprehensively reviews the latest research progress in self-

powered microelectronics technology, contributing to promoting

further development of this ﬁeld.

2. State-of-the-Art of the Self-Powered

Microelectronics

In recent years, with the rapid development of IoTs, wide-

area low-power micropower electronic devices have been widely

used in various ﬁelds, which poses new challenges to the en-

ergy supply of microelectronic devices. Researchers have re-

cently developed many micro-energy harvesters for supplying

power to micro-power electronics. Before summarizing the de-

velopment process of self-powered microelectronics technol-

ogy, it is necessary to elaborate on the current application

status of microelectronic devices in the environment. Over-

all, micro-power electronic devices in the environment in-

clude the following three major categories: human wearable de-

vices, animal wearable devices, and environmental monitoring

sensors.

2.1. Human Wearable Microelectronics

With the growing demand for mobile electronics and health

monitoring devices, human wearable devices emerge endlessly,

which can be found throughout the body. To ensure the con-

tinuous operation of human wearable electronic devices, self-

powered wearable devices based on human environmental en-

ergy harvesting technology have been widely studied. Figure 2

shows a variety of wearable devices existing in the human body,

including glasses, helmets, masks, backpacks, watches, wrist-

bands, gloves, exoskeleton systems, shoes, socks, and ﬁve hu-

man environment energy sources (mechanical energy, thermal

energy, biochemical energy, solar energy, and RF energy). In

addition, as a branch of wearable microelectronic devices, im-

plantable devices are also widely developed for human health

monitoring.[91] Figure 2a–c shows three types of wearable mi-

croelectronic devices present in the human head area, including

a triboelectric nanogenerator (TENG) based micro-motion sen-

sor integrated with glasses,[92] a self-powered triboelectric audi-

tory sensor,[93] and a smart mask integrated a TENG used for

monitoring human respiration.[94] The wearable electronic de-

vices present in the middle torso area of the human body are

shown in Figure 2d–g. As shown in Figure 2d, a wearable back-

pack based on mechanical motion rectiﬁers can harvest human

kinetic energy to power portable electronics.[95] Figure 2e shows

a smartwatch based on an embedded electromagnetic generator

with enormous application potential in health monitoring and

sports training.[96] Figure 2f shows a wristband-type electromag-

netic energy harvester, which is proven that can eﬀectively har-

vest human kinetic energy.[97] Figure 2g shows a smart glove

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Figure 2. Human smart wearable devices. a) Glasses integrated eye motion sensor. Reproduced under the terms of the CC–BY license.[92] Copyright

2017, the authors, published by the American Association for the Advancement of Science. b) Self-powered triboelectric auditory sensor for hearing aids.

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based on the t triboelectric bending sensor used in the multi-

dimensional human-machine interface.[98] Figure 2h–j shows

wearable electronic devices present in the lower limb area of

the human body. As shown in Figure 2h, an exoskeleton sys-

tem captures human walking negative work to prolong the run-

time of exoskeleton robots.[99] Figure 2i shows a hybrid TENG

embedded in shoes, which can convert linear motion to rota-

tional motion.[74] Figure 2j shows a deep learning-enabled smart

sock, which can obtain human motion information by analyz-

ing gait.[100 ] Figure 2k–o shows the ﬁve diﬀerent micro-energy

sources that exist in the human body environment and their re-

covery mechanisms. As shown in Figure 2k, a non-resonant en-

ergy harvesting system based on a hybrid electromagnetic gen-

erator (EMG) is designed, which shows great potential for pow-

ering wireless sensor networks.[101 ] Figure 2l shows a wearable

thermoelectric generator proposed to harvest human body heat

for sensor self-powering.[102 ] AsshowninFigure2m,awire-

less wearable sweat biosensor based on freestanding TENG is

used to monitor the human state during exercise.[103 ] Figure 2n

shows a wearable ﬂexible solar cell.[104 ] As shown in Figure 2o,

a stretchable 3D microstrip antenna is proposed to harvest RF

energy.[105]

2.2. Animal Wearable Microelectronics

With increasing global warming and environmental pollution,

the survival of animals is seriously aﬀected. Especially for en-

dangered wild animals, it is necessary to monitor their physiol-

ogy and behavior. Animal monitoring methods mainly include

camera-based computer vision, sensor-based acoustic monitor-

ing, radio wave-based radar monitoring, and molecular meth-

ods using genetic information.[106 ] The detection technology

based on wearable electronic devices has the advantages of

convenience, wide coverage, and fast response, making it a

good method for monitoring animals. The operation of elec-

tronic tags integrating various sensors and signal transmit-

ters requires a large amount of distributed energy. Tradition-

ally, most ways to power these electronic devices are through

lithium batteries. However, traditional batteries’ instability and

limited lifespan lead to potential environmental pollution and

high maintenance costs. Many wearable devices that integrate

energy harvesting and animal monitoring functions have been

developed.[107,108 ] These wearable devices can be divided into at-

tached devices[109,110 ] and implantable devices.[111,112 ] The collar

and foot ring are attached to the surface of the animal body, which

has low installation and maintenance costs, but poor reliability.

Implant devices are embedded into animals, with high reliability,

but installation and maintenance costs are high and may cause

certain harm to animals.

2.3. Environmental Monitoring Microelectronics

In addition to the presence of microelectronic devices in hu-

mans and animals, various microelectronic devices are also

present in various ﬁelds of the environment, especially envi-

ronmental monitoring sensors. Due to the large number of

microelectronic devices in the environment, there is an ur-

gent need for environmentally friendly power supply meth-

ods to replace chemical batteries to reduce environmental pol-

lution caused by excessive battery usage. Distributed environ-

mental energy harvesters are considered the best battery re-

placement. Technologies such as wind energy harvesting, vi-

bration energy harvesting, thermal energy harvesting, solar en-

ergy harvesting, wave energy harvesting, and radio frequency

energy harvesting have been widely studied. Figure 3 shows

the microelectronic devices and corresponding energy harvest-

ing devices in six ﬁelds: transportation, ocean, home, agricul-

ture, industry, and natural environment. As shown in Figure 3a,

in the ﬁeld of rail transit, the power source of microelec-

tronic devices such as monitoring sensors can be served by

the rail vibration energy harvesting system.[113 ] As shown in

Figure 3b, in the marine ﬁeld, power equipment based on

wave energy harvesters can provide electrical energy for ma-

rine monitoring sensors.[114 ] As shown in Figure 3c, in the

home ﬁeld, energy harvesting technologies such as triboelec-

tric power generation and photovoltaic power generation can

achieve power supply for household microelectronic devices.[115]

As shown in Figure 3d, the breeze-driven TENG can eﬀec-

tively harvest wind energy to power microelectronic devices of

intelligent agriculture.[116 ] As shown in Figure 3e, in indus-

trial ﬁelds such as smart factories, TENG-based vibration en-

ergy harvesters can drive the monitoring sensors for machine

vibration status.[117 ] As shown in Figure 3f, in the ﬁeld of en-

vironmental monitoring, ambient kinetic energy can also be

collected through TENG-ENG equipment to drive monitoring

sensors.[118 ]

3. Available Ambient Micro-Energy

Micro-energy in the environment has the advantages of clean-

liness, wide distribution, easy capture, and large storage ca-

pacity. Environmental energy harvesting and regeneration tech-

nologies have been greatly developed in recent years. Figure 4

by Springer Nature. k) Hybridized electromagnetic-triboelectric nanogenerator for harvesting human vibration. Reproduced with permission.[101 ] Copy-

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Figure 3. Applications of environmental monitoring devices. (a) Rail vibration energy harvester for intelligent transportation. Reproduced with

Elsevier.

demonstrates the ﬁve common available micro-energy sources in

the environment. All these ﬁve micro-energy sources can be con-

verted into electrical energy through speciﬁc energy conversion

mechanisms and used to power microelectronic devices in the

environment. The output power of ambient micro-energy har-

vesting devices varies from μW to TW, which can meet the power

demand of the environmental microelectronics (usually with a

power requirement of μW to mW). The following sections will

brieﬂy introduce the ﬁve ambient micro-energy sources

3.1. Thermal Energy

Heat energy is widely distributed in the natural environment

and industrial production process, mainly divided into primary

and secondary energy waste heat, as shown in Figure 4a. Other

energy conversion mechanisms do not process primary energy

heat, such as geothermal and solar thermal energy. In addition,

primary energy heat has very large reserves, making great con-

tributions to the solution of a centralized power supply.[ 119] The

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Figure 4. Classiﬁcation of ambient micro-energy. The source of a) thermal energy, b) solar energy, c) mechanical energy, d) RF energy, and e) biochemical

energy.

secondary energy heat, such as industrial waste heat, vehicle ex-

haust waste heat, and human body heat, is usually generated dur-

ing primary energy consumption.[120 ] For example, when con-

verting gasoline into electricity in a car, much energy is released

as waste heat. The generation of waste heat seriously aﬀects the

energy conversion eﬃciency of primary energy. Hence how to use

waste heat has attracted much attention. Thermoelectric genera-

tors based on the Seebeck eﬀect are widely used to convert ther-

mal energy directly into electricity.[121] In order to improve energy

conversion eﬃciency, some researchers proposed hybrid energy

harvesters which can simultaneously convert thermal energy and

other forms of energy into usable electrical energy.[122]

3.2. Solar Energy

Solar energy has the advantages of universality, harmlessness,

and durability. Therefore, with the continuous reduction of fos-

sil fuels, solar energy has become an important component of

renewable energy and has been continuously developed.[123 ] The

annual radiation energy received by the Earth from the sun is

enormous, exceeding the annual energy consumption of fossil

fuels.[124 ] Although the total amount of solar radiation reach-

ing the Earth’s surface is large, the energy ﬂux density is low.

At the same time, aﬀected by natural conditions such as geo-

graphical location and season, solar radiation is unstable and

intermittent.[125 ] Solar energy harvesting technology is relatively

mature, but low eﬃciency and high cost are the factors that limit

its promotion. There are two approaches to utilizing solar en-

ergy: photoelectric conversion and photothermal conversion, as

shown in Figure 4b. In photovoltaic systems, light energy is con-

verted into electricity generated by the photovoltaic eﬀect, which

Alexand re-Ed Mond Becquere ﬁrst discovered in 1839.[126 ] So-

lar thermal conversion technology stores solar energy as thermal

energy.[127]

3.3. Radio Frequency Energy

Radiofrequency (RF) is a high-frequency alternating electromag-

netic wave with a frequency range of 3 kHz to 3 GHz.[128] Due

to the high frequency and strong penetrability of the electro-

magnetic wave, RF has a strong long-distance transmission ca-

pability in the air.[129,130] However, RF has a low power den-

sity, which varies between 0.2 nW cm−2and 1 μWcm

−2.[131]

RF waves are commonly present in the environment, and their

sources can mainly be classiﬁed into anthropogenic RF and two

natural sources (solar RF and atmosphere RF), as shown in

Figure 4d. Many electronic devices, such as televisions, mobile

phones, routers, base stations, etc, generate anthropogenic RF.

Two natural RF sources are electromagnetic radiation from the

sun and electromagnetic waves from gas and water vapor. In ad-

dition to being an information carrier, RF waves can be used

as an energy medium to power wireless sensors.[132 ] The fu-

sion technology based on wireless power transfer and wireless

information transmission has attracted wide attention, such as

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wireless power communication and radio frequency identiﬁca-

tion systems.[133 ] In recent years, radio frequency energy har-

vesting technology has developed rapidly and has been applied

in many ﬁelds, such as environmental monitoring,[134 ] medical

care,[135 ] and RF identiﬁcation.[136 ]

3.4. Biochemical Energy

Biochemical energy is formed during the metabolic process

of humans and other biological organisms.[137 ] As shown

in Figure 4e, biofuels refer to fuels generated by living or-

ganisms, including plant bodies, human and animal excre-

ment (sweat, tears, urine, respiration, etc.), and other indus-

trial and agricultural waste.[138 ] Biofuels are receiving attention

due to their pollution-free characteristics and good economic

performance.[139 ] Due to the low power density of biochemical

energy, most currently studied biochemical batteries are used in

low-power devices such as wearable electronic products.[140 ] The

main biochemical energy in the human body is glucose, lactic

acid, and water. After digestion and absorption, food is converted

into glucose to provide energy for the body. Lactic acid is pro-

duced by the body after strenuous exercise.[141 ]. Under the action

of catalysts, biofuel cells (BFC) can convert glucose and lactate

into electricity through electrochemical reactions.[142,143 ] Wat er is

an important part of the human body, making up ≈70% of body

weight. In addition to being excreted in the urine, some water

is also excreted as sweat and breathing. Using the interaction of

nano-materials and water molecules, hydroelectric eﬀect genera-

tors (HEG) can convert humidity changes caused by sweat evap-

oration and respiration into electricity.[144,145] In addition to col-

lecting biochemical energy, BFC and HEG can also be used as

self-powered glucose, lactic acid concentration sensors, and hu-

midity sensors.[146,147 ]

3.5. Mechanical Energy

Mechanical energy is composed of kinetic energy and potential

energy. The potential energy can also be divided into gravitational

and elastic potential energy. As shown in Figure 4c, mechanical

energy is the most ubiquitous and accessible energy source in the

surrounding environment, such as vibration, wind, wave, biome-

chanical, and sound energy. Mechanical energy has a high degree

of randomness and irregularity, such as rail track vibration, irreg-

ular motion of the human body, and ﬂuid ﬂow.[148] According to

the entropy theory of distributed energy,[149] the energy harvest-

ing systems can convert the disorderly distributed energy into

orderly electric energy to solve the energy supply problem of the

distributed electrical devices. The frequency of mechanical en-

ergy distributed in the environment varies from a few hertz to

hundreds.

Furthermore, mechanical energy density ranges from hun-

dreds of microwatts to milliwatts per cubic centimeter.[150] The

frequency of human motion is relatively low (usually below tens

of hertz), and the motion amplitude is a few millimeters or a few

centimeters.[151 ] Wave energy has a high power density, reach-

ing the TW power level, but the frequency is not high.[152 ] Most

mechanical energy is manifested in the form of vibration. There-

fore, harvesting vibration energy has attracted great attention in

recent years.[153 ] In addition, the frequency range of vibration

energy is very wide, such as the vibration frequency of railway

tracks as low as a few hertz,[154 ] and the vibration frequency of

industrial machinery as high as hundreds of hertz.[155 ] The con-

cept of wind energy capture has been widely studied and devel-

oped for decades, and micro wind energy collectors at low wind

speeds have great potential in self-power supply.[156,157] There

are abundant sound sources in the environment, and the fre-

quency of sound waves is high, but the low sound energy density

is still a serious challenge for the application of sound energy

harvesting.[158 ] In addition, atmospheric water (such as rain, fog,

moisture, etc.) is a ubiquitous environmental resource, and its

current total amount is equivalent to three times the world’s to-

tal annual water consumption.[159 ] Therefore, fog harvesting, as

a typical atmospheric water harvesting scheme, has recently re-

ceived widespread attention from the scientiﬁc community.[ 160]

In order to harvest fog in the atmosphere, a series of fog harvest-

ing schemes based on bionic principles have been proposed.[161 ]

However, the speed and eﬃciency of fog harvesting are still a

major diﬃculty. Mechanical energy harvesting technology based

on diﬀerent energy conversion mechanisms has been developed

widely, which has broad prospects in the self-powered ﬁelds in

the future.

4. Energy Harvesting Technologies for

Microelectronics

In recent years, to eﬃciently harvest ambient distributed energy,

various energy harvesting technologies have been developed,

asshowninFigure5.

[73,162,163 ] The energy harvesting technolo-

gies mainly fall into ﬁve categories: thermoelectric generators-

based thermal energy harvesting, photovoltaic cells-based solar

energy harvesting, radio frequency (RF) energy harvesting, bio-

fuel cells-based biochemical energy harvesting, and mechanical

energy harvesting which can be further divided into triboelectric,

piezoelectric, electromagnetic, electrostatic, and magnetostric-

tive. A comparison between various energy harvesting technolo-

gies is shown in Figure 6. From this ﬁgure, it can be seen that

energy harvesting technologies can provide enough power for

many electrical facilities. The ﬁrst four energy harvesting tech-

nologies usually rely less on external mechanical structures and

they are mostly “static” energy harvesting technologies. Mechan-

ical energy harvesting technologies are closely related to the me-

chanical structure and are mostly a “dynamic” energy harvest-

ing technology. Combining the energy conversion mechanism

with diﬀerent mechanical structures can adapt to various appli-

cation environments, thereby improving energy harvesting eﬃ-

ciency. Usually, one method to improve energy harvesting per-

formance is to develop new materials or structures for energy

conversion mechanisms, while another method is to optimize ex-

ternal mechanical structures, such as monostable structures,[164 ]

bistable structures,[165 ] multistable structures,[166 ] internal reso-

nance structure,[167 ] multi-degree-of-freedom structures,[168] and

frequency up-conversion (FUC) structure.[169–171 ] In order to fur-

ther improve energy collection eﬃciency and achieve comple-

mentary advantages among diﬀerent energy conversion mech-

anisms, many researchers have also proposed hybrid energy col-

lection technology.[44,172,173] This section summarizes the basic

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Figure 5. Various energy harvesting technologies. a) Photovoltaic. b) Thermoelectric. c) RF energy harvesting. d) Biofuel cell. e) Triboelectric. f) Piezo-

electric. g) Electromagnetic. h) Magnetostrictive. i) Electrostatic.

structure and working principle of each energy harvesting tech-

nology. Especially the mechanical energy harvesting technology

considered the most promising distributed micro energy system,

will be emphasized in this section.

4.1. Heat Scavenging Based on Thermoelectric Mechanism

Researchers from various countries have developed various heat

energy collection devices to recover heat energy from the environ-

ment; one is a thermoelectric generator (TEG) based on the ther-

moelectric eﬀect, as shown in Figure 5a. The Seebeck eﬀect is the

basic principle of TEG, which means that the temperature gra-

dient in thermoelectric material will establish a potential diﬀer-

ence across the material.[174 ] A TEG system consists of p-type and

n-type semiconductors, where the p-type has excess holes and

the n-type has excess electrons. When heat ﬂows from the high-

temperature surface to the low-temperature surface through the

thermoelectric material, the electrons and holes of the semicon-

ductor also move, thus realizing the conversion of thermal energy

to electricity.[121] The output voltage of the TEG is proportional to

the temperature gradient, which can be expressed as:[175 ]

V=𝛼ΔT(1)

where Vis the output voltage, ΔTis the temperature gradient

of the thermoelectric material, and 𝛼is the Seebeck coeﬃcient.

Increasing the Seebeck coeﬃcient 𝛼can eﬀectively improve the

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Figure 6. Comparison of diﬀerent energy harvesting technologies (EEH: electrostatic energy harvester; PV: Photovoltaic; RF: radio frequency; BC: Bio-

fuel cell; TENG: triboelectric nanogenerator; PEG: piezoelectric generator; EMG: electromagnetic generator; MEH: mechanical energy harvester; TEG:

thermoelectric generator.).

output power of TEG. Therefore, the output power can be in-

creased by electrical series and thermal parallel connection of

thermoelectric elements. The eﬃciency of TEG can be evaluated

using the ﬁgure of merit ZT, which is expressed as:[25]

ZT =𝜎𝛼2T

𝜅(2)

where 𝜎is the electrical conductivity, Tis the average operating

temperature, and 𝜅is the thermal conductivity. Thermoelectric

materials with high Seebeck coeﬃcient 𝛼, high electrical con-

ductivity 𝜎, and low thermal conductivity 𝜅have larger ZT val-

ues, which help to improve the energy conversion eﬃciency of

TEG.

As an emerging energy harvesting technology, TEG has the

following advantages: high durability, high precision, small

size, long life, safety and reliability, scalability, and no moving

parts.[176–178 ] However, TEG also has some drawbacks, such as

low energy conversion eﬃciency and poor adaptability to me-

chanical deformation.[30,179,180 ] Since the operation of TEG is

driven by the temperature diﬀerence, TEG has been widely used

in waste heat recovery,[181] wearable sensing,[ 182] environmental

monitoring sensing,[183 ] and thermoelectric cooling.[184 ]

4.2. Solar Energy Harvesting

As one of the most promising renewable energy harvesting tech-

nologies, solar energy harvesting technology is gradually matur-

ing. Photovoltaic (PV) cells can eﬃciently convert solar energy

into electricity based on the photovoltaic eﬀect,[14] as shown in

Figure 5b. A PV cell in the most typical structure consists of a p-

type semiconductor, n-type semiconductor, and electrodes. When

sunlight hits a PV cell, new hole-electron pairs are created on the

semiconductor.[37] Subsequently, under the action of the electric

ﬁeld of the p-n junction, the hole-electron pairs are separated,

and an electric potential is generated between the electrodes. As

an important basis for evaluating the power generation perfor-

mance of PV cells, the formula of the I-V characteristic curve is

as follows:[38]

I=Isc −Id−V+IRS

Rsh

(3)

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where Isc is the short-circuit current, Idis the dark current, RSis

the series resistance, and Rsh is the shunt resistance. Energy con-

version eﬃciency 𝜂pv is also one of the most important parame-

ters to evaluate the performance of PV cells, which represents the

ratio of output energy to input solar energy, which is expressed

as:

𝜂pv =Pmax

=Voc ×Isc ×FF

×100%(4)

where Pmax is the maximum power output, Pinis the input power

of solar energy, and Voc is the open circuit voltage. FF is the ﬁll

factor, which represents the maximum power of the PV cell. With

the continuous updates of photovoltaic materials,[185 ] new solar-

tracing designs[186 ] and eﬀective power management systems[187 ]

can eﬀectively improve conversion eﬃciency. The energy conver-

sion eﬃciency of the latest PV cells has exceeded 40%.[188 ]

As a “static” energy harvesting technology, PV cells have the ad-

vantages of relatively high conversion eﬃciency, high current and

low internal impedance, and satisfactory DC output, which play a

vital role in the ﬁeld of self-powered applications.[189,190 ] The main

disadvantages of PV cells are high dependence on weather and

environmental conditions and high cost.[39,191 ] The widespread

distribution of solar energy and the maturation of PV technology

has driven the development of PV self-powered applications. A

large number of PV self-powered technologies have been devel-

oped in intelligent transportation,[192 ] wearable devices,[193 ] im-

plantable devices,[194 ] environmental monitoring,[40] and build-

ing systems.[195 ]

4.3. Radio Frequency Energy Harvesting

Since the ﬁrst radio frequency (RF) energy harvester was de-

signed for pacemakers in 1969, RF energy harvesting has re-

ceived widespread attention.[196 ] At the same time, radio fre-

quency energy harvesting technology has made great progress

in recent years.[197 ] The RF energy harvesting system converts

electromagnetic waves in the frequency band of 3 kHz-300 GHz

into direct current, as shown in Figure 5c. According to the spatial

distance between electromagnetic wave and the emission source,

the RF wave is in the order of reactive near-ﬁeld (<R1), radiating

near-ﬁeld (R1-R2) and far-ﬁeld (>R2) from near to far.[46] R1and

R2are the radius of the reactive near-ﬁeld region and the radiat-

ing near-ﬁeld region, respectively, which are expressed as:

R1=0.62√D3

𝜆(5)

R2=2D2

𝜆(6)

where 𝜆is the wavelength of the RF wave and Dis the maximum

diameter of the emission source. The power supply coil of the

near-ﬁeld RF energy harvesting system can be made by jet print-

ing, which has high power but limited working distance.[198 ] In

contrast, far-ﬁeld RF energy harvesting systems can operate at

distances up to thousands of kilometers, but their output power

is low. The power PnT of the transmitting coil and the power PnR

of the receiving coil of the near-ﬁeld RF energy harvesting system

can be expressed as:[38]

PnT =M

Lfr2(M

V1−V2)V1(7)

PnR =1

r2(M

V1−V2)V2(8)

where M,Lf,V1,V2,andr2are the mutual inductance between

the transmitting coil and the receiving coil, the inductance of the

transmitting coil, the voltage at the transmitting end, the voltage

at the receiving end, and the resistance at the receiving end, re-

spectively. The power PfR at the receiving end of the far-ﬁeld RF

energy harvesting system is:

PfR =PfTGTGR𝜆2

(4tR)2(9)

where PfT is the power of the transmitting antenna, GTand GR

are the gains of the transmitting and receiving antennas, respec-

tively, and Ris the distance from the transmitting antenna to the

receiving antenna.

A typical RF energy harvesting system consists of a receiving

antenna, an impedance matching circuit, a rectiﬁer, a booster,

and loads. Two common evaluation metrics for RF energy har-

vesting systems are conversion eﬃciency 𝜂RF and sensitivity

S(dBm). Conversion eﬃciency is deﬁned as the ratio of load

power Pload to receive antenna power PR, which is expressed

as:[199 ]

𝜂RF =Pload

(10)

The conversion eﬃciency depends on the eﬃciency of the indi-

vidual components. Sensitivity is deﬁned as the minimum input

power PR−min to drive the operation of the RF energy harvesting

system, which is expressed as:[200 ]

S(dBm)=10log10 (PR−min

1mW )(11)

RF energy harvesting is a promising alternative solution to re-

alize wireless power transfer, which is sustainable, cost-eﬀective,

and has long transmission distances.[201,202 ] However, RF energy

harvesting technology still needs to be optimized, such as reduc-

ing transmission loss, increasing output power, and optimizing

system size.[203,204 ] With the continuous advancement of tech-

nology, RF energy harvesters have been used to supply power

for wireless sensor nodes in smart agriculture, industrial mon-

itoring, and smart grids.[205,206 ] In addition, miniaturization and

light-weighting of RF energy harvesting systems make it possible

for self-powered wearable and implantable devices.[207,208 ]

4.4. Biochemical Energy Harvesting

Biofuel cells (BFCs) show good prospects for integrating tradi-

tional fuel cells and biological environments.[209 ] BFC was ﬁrst

proposed by Yahiro in 1964, which converts biochemical energy

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into electrical energy through an electrochemical reaction.[210 ] As

shown in Figure 5d, using enzymes or microorganisms as cata-

lysts, BFC converts biofuels (glucose, fructose, lactic acid, and

ethanol) into electricity through a redox reaction. Speciﬁcally, the

biofuel is oxidized at the anode of the BFC to generate electrons,

and the oxidant is reduced at the cathode. Human metabolites,

such as sweat, tears, and saliva, are rich in biofuels, which can

be used for bioenergy recovery and self-powered biosensing. The

wearable BFC can generate electricity in the milliwatt range, and

its output is proportional to the biofuel concentration. The ef-

ﬁciency of a BFC system is highly dependent on temperature,

pH, and oxygen levels. According to the diﬀerent catalysts, BFCs

can be roughly divided into microbial fuel cells (MFCs) and enzy-

matic fuel cells (EFCs).[211,212 ] Under anaerobic conditions, MFC

generates electrons through microbial degradation of biofuels

(such as sugar), accompanied by the production of hydrogen ions

and carbon dioxide, which can be expressed as:[23]

C12H22 O11 +13H2O→12CO2+48H++48e−(12)

In this process, the electrons are transferred to electrodes to

convert chemical energy into electrical energy. Since the trans-

fer process is relatively slow, the power density of the MFC is

low. At present, MEC has great attraction in purifying sewage

and degrading garbage. In contrast, EFCs have more potential

for wearable and implantable applications due to their superior

power density and compactness.[213 ] In the EFC system, enzymes

at the anode act as catalysts to catalyze redox reactions to generate

electrons. As a common example, alcohol dehydrogenase is used

to oxidize alcohol in EFC, and the reaction process is shown in

the following formulas:[214 ]

CH3CH2OH +NAD+Alcohol dehydrogenase

←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←←→CH3CH2O+NADH(13)

NADH +electrocatalyst(red)→NAD++electrocatalyst(ox)(14)

electrocatalyst(ox)→electrocatalyst(red)+e−(15)

Like an MFC, EFC electrons are transferred to the cathode

through an external circuit to generate current. There are many

types of enzymes as catalysts, among which glucose oxidase is

the most commonly used.[215 ]

One of the most prominent features of BFC compared to con-

ventional batteries is its environmental friendliness, fuel ﬂex-

ibility, mild temperature conditions, and ease of operation at

low temperatures.[216,217 ] Therefore, BFC is a promising power

source that is less expensive and easier to manage. However,

BFC still faces many challenges in practical applications, such

as improving operational stability, enhancing mechanical com-

pliance, and improving the interaction between electrodes and

biocatalysts.[218,219 ] With the development of BFC, it has many

possible applications, such as wastewater treatment, energy har-

vested by transportation, and wearable biofuel cells.[220 ] Non-

invasive BFCs provide feasible solutions for biochemical energy

recovery and biomarker monitoring, which will contribute to

the development of medical rehabilitation and national defense

security.[221,222]

4.5. Mechanical Energy Harvesting

4.5.1. Triboelectric Generator

The triboelectric eﬀect has been discovered for thousands of

years, and it is a kind of electriﬁcation eﬀect caused by contact.

When one material rubs against another, such as using a plastic

comb to comb their hair, theybecome charged. In 2012, Zhonglin

Wang ﬁrst proposed the triboelectric nanogenerator (TENG),

mainly used to harvest small-scale mechanical energy.[223] The

emergence of TENG provides a new solution for converting disor-

dered high-entropy mechanical energy into ordered low-entropy

electrical energy. Generally, TENG mainly has four basic work-

ing modes, namely vertical contact-separation mode,[224 ] lateral-

sliding mode,[225 ] single-electrode mode,[226 ] and freestanding

triboelectric-layer mode,[227 ] as shown in Figure 5e. The origin

of TENG is Maxwell’s displacement current theory, which can be

expressed as:[228,229 ]

JD=𝜕D

𝜕t=𝜀𝜕E

𝜕t+𝜕Ps

𝜕t(16)

where Dis the electric displacement ﬁeld, 𝜖is the vacuum per-

mittivity, Eis the electric ﬁeld, and Psis the polarization ﬁeld

generated by the surface charge. 𝜀𝜕i

𝜕irepresents the induced cur-

rent caused by the changing electric ﬁeld, which is the theoretical

basis of electromagnetic wave technology. 𝜕Ps

𝜕rrepresents the cur-

rent caused by the polarization ﬁeld generated by the electrostatic

charge on the surface, which is the basis and origin of the fun-

damental theory of TENG. Speciﬁcally, when two diﬀerent mate-

rials are in contact, their surfaces generate positive and negative

electrostatic charges due to the electrical action of the contact.

Then, when the two materials separate, the positive and negative

charges generated by contact electriﬁcation also separate, creat-

ing a potential diﬀerence between the upper and lower electrodes

of the material. A load is connected between the two electrodes,

and the potential diﬀerence drives electrons to generate a current

in the external circuit. The open circuit voltage between two elec-

trodes can be expressed as:[230 ]

Uoc =−

𝜎d

𝜀(17)

where 𝜎is the triboelectric charge density, and dis the gap dis-

tance between the two materials. In addition, the short-circuit

current can be expressed as:[231 ]

Isc =CT

𝜕VT

𝜕t+VT

𝜕CT

𝜕t(18)

where CTis the capacitance of the triboelectric system, and VTis

the triboelectric voltage generated on the two electrodes.

The invention of TENG is a milestone step in mechani-

cal energy generation and self-propelled systems. Since 2012,

TENG has developed rapidly, and its output power has been

increased from 2 μWto50W.

[232 ] TENG has the advantages

of a simple structure, and high energy eﬃciency, which has

been extensively developed for mechanical energy harvesting and

self-driven sensing.[233,234 ] In general, the three major applica-

tions of TENG are micro-nano-energy harvesting,[235 ] self-driven

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sensing,[236 ] and blue energy.[237] The TENG system has laid the

foundation for integrating nano-devices and large-scale energy

supply from micro-nano-scale distributed energy collection to

macro-high energy density power generation. It will play a huge

role in ﬁelds such as the IoTs,[238 ] healthcare,[239 ] artiﬁcial intelli-

gence (AI),[240 ] aerospace,[241 ] and environmental monitoring.[242 ]

4.5.2. Piezoelectric Energy Harvester

Piezoelectric energy harvesting (PEH) based on the piezoelec-

tric eﬀect is another popular mechanical energy harvesting tech-

nology. The Curie brothers ﬁrst discovered the piezoelectric ef-

fect in 1880.[243 ] The basic principle of the piezoelectric eﬀect

is shown in Figure 5f. The upper and lower surfaces of an in-

sulating piezoelectric material are covered with two electrodes,

and the piezoelectric material undergoes mechanical deforma-

tion under the action of an external force. Mechanical deforma-

tion leads to piezoelectric polarization charges at both ends of the

material, and the resulting potential diﬀerence drives the charge

ﬂow through the external circuit, thereby realizing the conversion

of mechanical energy into electrical energy.[ 244,245] In addition,

the piezoelectric eﬀect can be divided into direct and converse

piezoelectric eﬀects. The former represents the phenomenon of

induced potential generated by piezoelectric materials under me-

chanical stress, and the latter represents the phenomenon of me-

chanical strain generated by materials under an external electric

ﬁeld. In general, the piezoelectric eﬀect can be expressed by the

following piezoelectric constitutive equation:[246 ]

[𝛿

D]=[sEdt

d𝜀T][𝜎

E](19)

where 𝛿,s,d,𝜖,and𝜎represent the strain component, elas-

tic compliance, dielectric constant, piezoelectric coeﬃcient, and

stress component, respectively; Eand Dare the electric ﬁeld and

electric displacement, respectively; superscript t indicates trans-

pose.

Depending on the direction of applied stress and the polariza-

tion, piezoelectric materials can work in diﬀerent modes, which

can be mainly divided into 33 modes (transverse mode) and 31

modes (longitudinal mode).[247,248 ] In the 31 modes, 3 indicates

the direction of the piezoelectric material polarizing electric ﬁeld,

and 1 indicates the direction of the applied stress–strain. In gen-

eral, the piezoelectric coeﬃcient d33 is higher than d31. Piezoelec-

tric materials in the 31 mode are more strained in the 1 direction,

so the 31 mode is more common. The 31 mode usually appears in

PEH based on cantilever beams, and the 33 mode mostly appears

in PEH designed in the form of piezoelectric stacks.

The choice of piezoelectric materials determines the output

performance of PEH. Common piezoelectric materials include

piezoelectric ceramic transducers (PZT),[249 ] polyvinylidene ﬂuo-

ride (PVDF),[250 ] and ZnO.[251 ] Nanoscale generator based on the

piezoelectric eﬀect is a recent development. In 2006, Zhonglin

Wang proposed a piezoelectric nanogenerator (PENG) based

on zinc oxide nanowire arrays, promoting piezoelectric energy

harvesting technology.[252] PEH has received widespread atten-

tion due to its high energy density, simple structure, small

size, and easy installation.[253 ] PEH is already used to produce

medical and environmental sensors and actuators.[77,254 ] In ad-

dition, PEH has great potential to harvest mechanical energy

from human motion,[255 ] environmental vibration,[256 ] and vehi-

cle vibration.[257 ] All in all, PEH will be a promising technology

for IoT applications in the 5G era.

4.5.3. Electromagnetic Generator

In 1831, Faraday discovered the transformation relationship be-

tween magnetism and electricity, which is the phenomenon of

electromagnetic induction. As shown in Figure 5g, the conduc-

tor (magnet) of the closed circuit moves relative to the coil, which

causes a change in the magnetic ﬂux inside the coil, causing an

induced current in the coil. The resulting induced voltage can be

expressed as:[258 ]

E(t)=−

d𝜙B

dt (20)

where E(t) is the induced voltage and ϕBis the magnetic ﬂux.

When the magnet moves perpendicular to the coil, the open cir-

cuit voltage Voc of the coil can be expressed as:[259 ]

Voc =NBlc

dt(21)

where N,B,lcand xare the number of turns of the coil, the mag-

netic ﬁeld density, the eﬀective length of the coil cutting magnetic

ﬁeld, and the relative distance between the magnet and the coil,

respectively. From the above formula, the parameters that aﬀect

the output voltage are the rate of change of the magnetic ﬂux of

cutting the coil and the number of coil turns. The output power

P(t) of the external load is:

P(t)=E2(t)

Rc+Re

(22)

Rcand Reare the impedance of the coil and the impedance of the

external load, respectively. For the output power of external load,

it can reach the maximum as Re=Rc.

As a dynamic energy harvesting mechanism, the mechanical

structure greatly aﬀects the output performance of the electro-

magnetic generator (EMG). Generally, EMGs are divided into lin-

ear and rotary.[260,261] Linear EMG is often used to harvest vi-

bration energy,[262] and is usually integrated with piezoelectric

generators.[263 ] Rotating EMG is widely used in centralized and

large-scale power generation systems, such as large wind tur-

bines, ocean, and hydropower stations. In addition, rotating EMG

usually has a higher cutting magnetic induction line speed than

linear EMG, and thus has higher output performance. Therefore,

rotating EMG is more widely used in distributed energy harvest-

ing systems.[264 ]

Taking advantage of high power density, high energy conver-

sion eﬃciency, and high current, EMG covers all ﬁelds from

small distributed energy to large centralized energy, showing

great ability to promote the development of modern energy

technology.[265] It cannot be ignored that EMG has low out-

put voltage and unavoidable coil loss, so many hybrid power

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generation devices have been developed, such as piezoelectric-

electromagnetic hybrid generators[172 ] and electromechanical-

electromagnetic hybrid generators.[266 ]

4.5.4. Magnetostrictive Energy Harvester

The magnetostrictive energy harvester is a new type of energy

harvesting technology. Based on the Joule and Villary eﬀects, the

transformation between strain energy and magnetic energy of

magnetostrictive materials is realized. The Joule eﬀect indicates

that the size of magnetostrictive materials changes with changes

in external magnetic ﬁelds, also known as the magnetostric-

tive eﬀect.[267 ] The Villari eﬀect represents the phenomenon

in which a magnetostrictive material causes a change in the

magnetic ﬁeld when mechanically strained, also known as in-

verse magnetostriction.[268 ] As shown in Figure 5h, the Stoner–

Wohlfarth approximation can describe magneto-mechanical cou-

pling, in which the magnetically coupled material is assumed to

be a collection of magnetic domains. For small coaxial stress and

magnetic ﬁeld perturbations, the magneto-mechanical coupling

constitutive equation can be expressed as:[269 ]

ΔB=dΔT+𝜇HΔH(23)

ΔS=sHΔT+dΔH(24)

where ΔB,ΔT,ΔH,andΔSare the magnetic ﬂux density incre-

ment, the stress increment, the magnetic ﬁeld increment, and

the strain increment, respectively. d,μH,andsHare the piezomag-

netic constant, the magnetic permeability, and the elastic compli-

ance, respectively.

According to the strain state of the magnetostrictive material,

magnetostrictive energy harvesters can be divided into axial type

and bending type.[270 ] The axial type is mainly used to collect vi-

bration along the direction of the magnetostrictive material. In

contrast, the bend type can collect vibrations in any direction.

The commonly used materials for magnetostriction include fer-

romagnetic and ferromagnetic materials, mainly used for actu-

ators and motors.[271 ] Giant magnetostrictive materials such as

Fe─Ga alloys have been used in energy harvesting devices due

to their high energy conversion eﬃciency and environmental

durability.[272]

As a new mechanical energy harvesting technology type,

magnetostrictive energy harvesters have attracted widespread

attention due to their high power density and good environ-

mental adaptability. It performs excellently, especially in low-

frequency vibration energy harvesting systems.[273 ] At present,

magnetostrictive energy collection technology has been com-

bined with piezoelectric/electromagnetic technology to achieve

the conversion of kinetic energy, magnetic energy, and electri-

cal energy to enhance the eﬃciency of energy harvesters.[274 ]

Magnetostrictive-piezoelectric/electromagnetic-based hybrid en-

ergy harvesters show great potential in self-powered wireless sen-

sor networks.[275,276 ]

4.5.5. Electrostatic Energy Harvester

The structure of the electrostatic energy harvester (EEH) based on

the electrostatic eﬀect is similar to that of a variable capacitor. It

consists of two conductive plates with air or a dielectric between

them.[277 ] Unlike contacted triboelectric nanogenerators, which

require two materials to come into contact to generate electric-

ity, electrostatic energy harvesters harvest mechanical energy in

a non-contact manner. Usually, one plate is ﬁxed, and one plate is

externally stimulated to generate relative motion, which causes a

change in capacitance and converts mechanical energy into elec-

trical energy, as shown in Figure 5i.[278 ] For a capacitor with a

parallel plate, the capacitance Ccan be expressed as:[279 ]

C=Q

V=𝜀0𝜀rA

(25)

where Qand Vare the charge and the voltage on the plate, re-

spectively. 𝜖0,𝜖r,Aand dsare the permittivity of free space, the

relative permittivity of the dielectric material, the area of the ca-

pacitor plates, and the distance between the plates, respectively.

The voltage and capacitance on the capacitor aﬀect each other,

and the energy Estored on the capacitor is:[280 ]

E=1

2QV =1

2Q2∕C(26)

Electrostatic energy harvesters can be divided into electret-free

EEH,[281 ] and electret-based EEH.[282 ] Electret-free EEHs are pas-

sive devices that require the assistance of external active elec-

tronic circuits for charging and discharging. At the same time,

it requires energy cycling based on charge or voltage constraints

to convert mechanical energy to electrical energy. On the con-

trary, the electret-based EEH using pre-charged electret material

is similar to a charged capacitor and realizes the output of electric

energy without the assistance of an external power source.

Based on the advanced micro-electromechanical system

(MEMS) technology, EEH can be easily integrated with micro-

electronic circuits.[283 ] At the same time, it has the advantages of

high voltage output and low manufacturing cost. However, EEHs

require a separate power source or electriﬁed electrode material,

which increases the complexity of the energy harvester. Due to

its signiﬁcant advantages in miniaturization design, EEHs for

wearable devices and implantable medical devices have broad

prospects.[284,285 ]

Table 1 summarizes the latest research work based on diﬀer-

ent mechanical energy harvesting technologies. The innovation

points, input excitation, output response, power density, and ap-

plication objects of these research works are emphasized and

compared. Application-oriented, researchers use diﬀerent energy

harvesting strategies based on diﬀerent input excitations. This

allows the developed energy harvester to adapt to the target en-

vironment, thereby achieving a better energy harvesting eﬀect.

Based on energy harvesting technology, application-oriented self-

powered microelectronic devices are developed to meet the en-

ergy and monitoring needs in the IoTs era. These self-powered

microelectronic devices will play a key role in human wearable

applications, implantable applications, animal wearable applica-

tions, intelligent transportation, smart ocean, smart home smart

agriculture, smart industry, and natural environment to promote

the progress of the IoTs era.

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Tabl e 1 . Progress of mechanical energy harvesters based on diﬀerent technologies.

Energy harvesting

strategies

Description Input Output Power density Applications Year Ref.

Triboelectric Floating self-excited sliding TENG

for harvesting micromechanical

energy

300 rpm 34.68 mW 71.5 μCm

−2For self-powered

micro-grid

distribution and

environmental

monitoring

2021 [242]

Triboelectric and

Thermoelectric

Hybrid triboelectric and

thermoelectric energy

harvesters for human wearable

fabrics

0.5 Hz 39.24 W 8.25 mW m−2Charge the smartphone 2022 [190]

Triboelectric TENG for eﬃcient biomechanical

energy harvesting and musical

response

19 cm 2916 μW 148.6 mW m−2Self-powered sensors

for smart home

applications

2023 [286]

Triboelectric Hybrid nanogenerator-based

self-powered

double-authentication

microsystem for smart

identiﬁcation

50 Hz 23.5 V 51.2 μWcm

−2A self-powered DAM

realizes personal

identiﬁcation and

automatic unlocking

2021 [287]

Triboelectric Exo-shoe TENG 1 Hz 160 V ∖Wireless and

self-powered

monitoring of

environmental

information

2021 [288]

Triboelectric Vortex-induced vibration

triboelectric nanogenerator

2.78 m s−1392.72 μW 96.79 mW m−2Self-powered wireless

sensing system

2022 [289]

Triboelectric Torus structured TENG For water

wave energy harvesting

2 Hz 72.75 μW0.21Wm

−2Powering a

thermometer by the

Torus structured

TENG

2019 [290]

Triboelectric High-performance liquid-solid

tubular TENG for scavenging

water wave energy

1/3 Hz 150 V 228 mW m−3Self-power oﬀshore

device

2022 [291]

Triboelectric Frequency-modulated hybrid

nanogenerator for eﬃcient

water wave energy harvesting

500 g 9 mW 5.75 W m−3Powering wireless

sensors and sending

wireless signals

2022 [292]

Triboelectric TENG self-powered sensor for tire

pressure monitoring

100 rpm 22.3 mW 16.44 W m−2Self-powered sensor

monitoring networks

2018 [293]

Piezoelectric Hybrid acoustic, vibration, and

wind energy harvester using

piezoelectric transduction

∖1.9 mW 2318 μWcm

−3Structural health

monitoring of

bridges, tall buildings,

and railroad tracks.

2023 [294]

Piezoelectric Piezoelectric wind velocity sensor

with drag force

10 m s−17.5 μW3.3μWcm

−2Local wind speed

monitoring

2020 [295]

Piezoelectric Hybrid

piezoelectric-electromagnetic

wave energy harvester

2Hz,15cm 7V ∖Cross-sea bridge health

monitoring

2021 [296]

Piezoelectric Flexible aero-piezoelectric energy

harvester

6ms

−137.9 μW21μWcm

−2Structural,

environmental

monitoring

2022 [297]

Piezoelectric Origami dynamics-based soft

piezoelectric energy harvester

79 Hz 8.78V ∖Self-powered gait

biometric

identiﬁcation

2022 [298]

Piezoelectric Strongly coupled piezoelectric

energy harvesters

157 Hz 140 mW 317.5 mW cm−3g−2Self-powered machine

monitoring

2021 [299]

Piezoelectric A speed bump piezoelectric

energy harvester for an

automatic cellphone charging

system

30 km h−14086.08 mW 6.81 W m−2The self-controlled

charging system on

actual road.

2019 [300]

(Continued)

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Tabl e 1 . (Continued).

Energy harvesting

strategies

Description Input Output Power density Applications Year Ref.

Piezoelectric Wide-band piezoelectric energy

harvesters for self-powered

devices

132 Hz 321 mW ∖Powering wireless

network sensors

2020 [301]

Piezoelectric Wearable Piezoelectric Films

Based on

MWCNT-BaTiO3/PVDF

Composites

11 Hz 2.4 V 1.16 μWcm

−2Structural health

monitoring

2023 [302]

Piezoelectric Inverted piezoelectric ﬂag for

harvesting ambient wind energy

9ms

−120 mW 5.0 mW cm−3Structural,

environmental, and in

situ biological

monitoring

2017 [303]

Electromagnetic Vibration energy harvester with a

double frequency-up conversion

mechanism

0.2 Hz 75 μW∖Powering wireless

sensors for pipelines

in smart cities

2023 [304]

Electromagnetic Electromagnetic-triboelectric

energy harvester for human

motion energy exploitation

20 km h−115 V 7500 μWcm

−2Self-powered human

monitoring sensors

2023 [305]

Electromagnetic Pendulum-ﬂywheel vibrational

energy harvester

10 Hz 16.3 W ∖Self-powered sensor

nodes for health

condition monitoring

of machines or

structures

2020 [306]

Electromagnetic Electromagnetic energy harvesters

based on natural leaves

1700–1850 V

m−1

3.1 μA4.52mWm

−2Self-powered sensors

for environmental

monitoring

2022 [307]

Electromagnetic Low-frequency

electromagnetic-pendulum

energy harvester

1.5 Hz 14.76 mW 324.62 mW g−2Self-powered wireless

sensor system for

water monitoring

2022 [308]

Electromagnetic A wind energy harvesting system

for high-speed railway tunnels

11 m s−1107.76 mW ∖Self-powered

applications in

high-speed railway

tunnels

2019 [309]

Electromagnetic Electromagnetic type of hybrid

vibroacoustic energy harvester

130 dB, 0.3 g

s−2

741 μW9.2μWcm

−3Self-powered for

wireless sensor nodes

2023 [310]

Electromagnetic Mini-generator that harvests

energy from human motion

7kmh

−12034 mW 18.32 mW cm−3Wearable electronic

devices

2021 [311]

Electromagnetic Electromagnetic vibration energy

harvester based on ring

magnets with Halbach

conﬁguration

61.7 Hz 3.61 mW 29.08 mW cm−3g2∖2022 [312]

Electromagnetic Hybrid wave vibration energy

harvester actuated by a rotating

wobble ball

1.4 Hz 21.95 mW 3.914 ×10−6mW

mm−3

Island power supply and

marine climate

monitoring

2023 [313]

Electrostatic Dual modules cantilever-based

electrostatic energy harvester

with stoppers

52 Hz, 0.23 g

s−2

0.45 mW 4.6 mW m−3g−2∖2023 [314]

Electrostatic Micro electrostatic energy

harvester

3 Pa, 0.09 g

s−2

4.95 μW3mWcm

−3g−2System integration of

sensors and inherited

circuits

2018 [283]

Electrostatic Hybrid piezoelectric and

electrostatic energy harvester

for scavenging arterial

pulsations

4 mm 87.29 mV 25 nW mm−1Powering implantable

and wearable

biomedical devices

2023 [315]

(Continued)

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Tabl e 1 . (Continued).

Energy harvesting

strategies

Description Input Output Power density Applications Year Ref.

Electrostatic Electrostatic Induced

Nanogenerator Circulation

Network

1.5 Hz, 1.44

−2

1.70 mW 2.16 W m−3Self-powered sensing

and remote marine

environmental

monitoring

2021 [316]

Electrostatic Hybrid vibration energy harvester

with integrated piezoelectric

and electrostatic devices

0.25 g s−21112.198 μW∖Power supply for

low-power wireless

sensor nodes

2023 [317]

Magnetostriction Spherical Magnetoelastic

Generator

5 Hz 4.6 mW 15.1 mW m−2Physiological

information

monitoring

2023 [318]

Magnetostriction Magnetostrictive iron-gallium

alloy vibration energy harvester

75 Hz 25 mW 7.4 mW/(cm3g−1) Supplying power for an

electronic meter and

electric fan

2020 [319]

Magnetostriction Detection of virus-like particles

using magnetostrictive

vibration energy harvesting

116 Hz 0.414 mW 12.2 mW cm−3Detection of virus-like

particles

2022 [320]

Magnetostriction Magneto-Mechano-Electric

Harvester

1 mT 37.5 μW2.2mWcm

−3Powering wireless

communications and

IoT sensors

2020 [321]

Magnetostriction Magnetoelectric coupled

magneto-mechano-electric

energy generator

500 μT 5.32 mW 2.2 mW cm−3Sustainable power

supply for sensors

and wireless

communication

systems

2020 [275]

5. Typical Applications of Self-Powered

Microelectronics

The distributed microenergy system based on energy harvesting

has great potential in solving the energy problem of distributed

IoT sensor nodes. Currently, customized self-powered devices for

applications are being widely developed. In this section, energy

harvesting-based human wearable electronics, animal monitor-

ing devices, and environmental monitoring sensors will be re-

viewed and discussed in detail

5.1. Self-Powered Wearable Devices: Above Shoulder

Self-powered wearable devices can be worn directly on the body or

integrated into human accessories to achieve speciﬁc functions.

Self-powered wearable devices can not only serve as independent

power sources but also as signal-sensing sources. Even some self-

powered wearable devices can achieve self-sustainability through

a combination of software and hardware. The miniaturization,

diversiﬁcation, intellectualization, and systematization of wear-

able devices provide a reliable guarantee for applications such

as bioenergy utilization, motion monitoring, physiological sig-

nal sensing, and human-computer interaction. Recently, a lot

of smart human wearable devices have been developed, such

as smart glasses,[92] hearing aids,[93] and masks,[94] as shown in

Figure 7. The development of these devices opens new avenues

for monitoring physiological states, enabling human-computer

interaction, and providing intelligent assistance

The functions of smart glasses with integrated self-powered

sensing are becoming increasingly diverse, such as visual percep-

tion and eye movement sensing, which are beneﬁcial for moni-

toring driver fatigue and helping disabled people walk.[331,332 ] In

addition, smart glasses are used to monitor chewing and eat-

ing behaviors.[333 ] As shown in Figure 7a, Zhang et al.[322 ] de-

signed smart glasses with integrated EMG electrodes to moni-

tor chewing behavior. The EMG electrodes are located at the ear

bend and temple end positions to monitor temporalis muscles’

activity. Experimental results show that the detection accuracy

of 44 eating events is above 95%. Smart glasses integrated with

eye-tracking sensors can precisely capture tiny movements of

the eyes, which can help realize human-machine interaction sys-

tems. Anaya et al.[323 ] proposed a TENG-based self-powered eye-

tracking sensor for human-machine interaction (Figure 7b). The

sensor is on the glasses and captures the movement of the orbic-

ularis oculi muscle to accurately detect voluntary and involuntary

eye blinking. In addition, it has great potential in remote car con-

trol, driver fatigue monitoring, and assistance for the disabled.

Inspired by the perception function of octopuses, Guo et al.[324]

proposed a wearable device that senses and visualizes stimuli, as

shown in Figure 7c. Based on the proposed dual-function inter-

active device, a wearable smart glasses system is constructed to

monitor information such as temporal pulse and chewing. When

the physiological information is abnormal, the system changes

the color of the glasses to remind the user. The smart glasses

system has the functions of signal acquisition, processing, trans-

mission, display, reﬂecting its integration and practicability.

Self-powered hearing aids can provide great voice informa-

tion assistance for the hearing-impaired, so they have received

extensive attention.[334,335 ] Speech is an important sensory infor-

mation that includes speech content, character emotions, and

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Figure 7. Self-powered wearable microelectronic devices: above shoulder. a) Smart glasses that monitor chewing behavior Reproduced with

identity information. Acoustic sensors based on self-powered

technology can eﬀectively capture speech information for voice

recognition and communication. In recent years, TENG-based

self-powered acoustic sensors have attracted much attention. As

showninFigure7d,Sunetal.

[325 ] proposed a human–robot in-

terface using a dual-function acoustic transducer. The acoustic

transducer is manufactured based on TENG and used to iden-

tify identity information, emotional state, and speciﬁc content

in speech. The recognition accuracy rate of the human-machine

interface for 30 speech categories is as high as 96.63%, show-

ing great potential in AI communication and robot intelligence

applications. In addition, a TENG-based multifunctional acous-

tic sensor is proposed, which has high-frequency resolution and

sensitivity and can sense 20 Hz–20 000 Hz acoustic waves.[336]

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The sensor’s sense-transform-response integration provides a vi-

able option for commercial applications such as music record-

ing and wireless video communication. Yang et al.[326 ] proposed a

tympanic triboelectric acoustic sensor based on ﬂexible nanoﬁber

materials, as shown in Figure 7e. The sensor has acoustic detec-

tion with high sensitivity and wide detection range, and it can

achieve a speech recognition accuracy rate of 92.64% based on

a dense convolutional network. Relying on this sensor, sound in-

formation is converted into text in time, which is not only of great

help to the hearing-impaired but also has broad prospects in the

development of intelligent systems based on speech recognition.

Acoustic sensors based on TENG have been widely developed,

and sensors based on piezoelectric materials have also shown ex-

cellent performance.[337 ] AsshowninFigure7f,Hanetal.

[327 ] de-

signed an acoustic sensor using ﬂexible piezoelectric materials,

which exhibited high sensitivity and multi-resonant frequency

bands. The acoustic sensor uses Gaussian mixture model-

based algorithms to perform deep learning on multi-channel

speech information, achieving a speaker recognition rate of

97.5%.

Masks play a role in ﬁltering air and isolating bacteria and

viruses in medical treatment, factories, and daily life. In particu-

lar, since the outbreak of COVID-19, face masks are one of the

most eﬀective means of stopping the spread of the virus. The

smart mask based on self-powered technology not only has the

function of air ﬁltration,[338 ] but also has the functions of respi-

ratory monitoring and lip language decoding.[330,339 ] Particulate

matter pollutants in the air pose a huge threat to human health.

Therefore, to eﬀectively ﬁlter particulate matter, Zhang et al.[340]

proposed a self-powered air ﬁlter based on ionic liquid-polymer

composites. This air ﬁlter exhibits high removal eﬃciencies of

99.59% for PM2.5 and 99.75% for PM10, respectively. Although

the air ﬁltration function of the mask is very powerful, its short

service life is a major drawback. In order to prolong the service

life of the mask, Peng et al.[328] proposed a self-powered elec-

trostatic mask driven by breathing, which can eﬀectively isolate

air pollutants for a long time, as shown in Figure 7g. The pro-

posed mask has an eﬀective service life of 60 hours and a ﬁltra-

tion eﬃciency of over 95.8% for 0.3-μm particles. Wearing a mask

for a long time may have adverse eﬀects caused by carbon diox-

ide rebreathing. Therefore, Escobedo et al.[53] proposed a smart

mask for carbon dioxide monitoring, which is based on an opti-

cal sensor with near-ﬁeld communication-based sensing tags to

achieve gas detection. In recent years, smart masks with respi-

ratory monitoring functions have received extensive attention in

healthcare and clinical applications.[341 ] Xue et al.[342 ] proposed

a smart mask using pyroelectric nanogenerators, which harvests

human breathing energy and simultaneously monitors human

breathing and ambient temperature. In order to realize the multi-

functionality of masks, Liu et al.[329 ] designed a smart mask with

self-disinfection, reuse, and respiratory monitoring functions,

as shown in Figure 7h. The proposed smart mask is made of

Ag micro-mesh ﬁlms, which can accurately distinguish diﬀerent

breathing states. At the same time, the developed TENG-based

self-powered breathing alarm system sends out an alarm when

the user has diﬃculty breathing. The mask is in close contact with

the lips, so it is feasible to use smart masks to capture lip move-

ment. In order to eﬀectively capture lip movements, Lu et al.[330 ]

proposed a lip language decoding system with a triboelectric sen-

sor and a machine-learning neural network model (Figure 7i).

The system has a recognition accuracy of 94.5% for 20-word lip

movements.

5.2. Self-Powered Wearable Devices: From Shoulder to Waist

From the shoulder to the waist of the human body, many wear-

able devices have also been developed, such as backpacks,[95]

watches,[96] wristbands,[97] and gloves,[98] as shown in Figure 8.

The ﬁrst three wearable devices mainly harvest human body

kinetic energy, which is used to power low-power electron-

ics. Gloves are mainly used to capture ﬁnger movements and

develop machine learning-based human-machine interaction

systems.

During the process of human walking, the center of mass oscil-

lates periodically, and this process contains huge mechanical ki-

netic energy. Wearable energy-harvesting backpacks can harvest

watt-level energy from human motion and power micro-power

electronics.[343 ] At present, a large number of energy-harvesting

backpacks have been carried out, and they mostly use EMG,[344]

TENG,[345 ] and hydraulic systems[346 ] for energy recovery. The en-

ergy harvesting backpack mainly harvests the energy of the vi-

bration of the center of mass, so a spring-mass-damper system

can be constructed to analyze the energy harvesting process. As

showninFigure8a,Xieetal.

[84] designed a tubular energy har-

vester embedded in a backpack to capture inertial kinetic energy.

In the spring-mass-damper system, the mass of the backpack acts

as a seismic mass, and its electromagnetic generator converts ki-

netic energy into electrical energy. The proposed backpack ex-

hibits excellent energy harvesting performance with an output

power of ≈5 W at a walking speed of 7.5 km h−1. The backpack

based on linear energy harvesters has the problem of power drop

caused by the mismatch of the resonant excitation frequency.

Therefore, in order to solve this problem, many researchers focus

on exploring nonlinear technology and frequency-tuning tech-

nology. Hou et al.[347 ] studied a bistable energy harvesting back-

pack, introducing a nonlinear system to improve energy harvest-

ing performance, as shown in Figure 8b. Compared with conven-

tional backpacks, the proposed backpack exhibits an improved

frequency bandwidth from 1 Hz to 1.65 Hz, and the output power

is enhanced from 2.34 W to 3.32 W when the walking speed is

5.6 km h−1.Mietal.

[348 ] designed a vibration energy harvester

with half-wave mechanical rectiﬁcation to improve the perfor-

mance of backpacks. This energy harvester converts bidirectional

vibrations into unidirectional rotation of EMG with an average

power range of 3.13-6.30 W at a speed of 3.3 km h−1. In the

case of energy-harvesting backpacks harvesting human kinetic

energy, it is also necessary to consider how to reduce the load

of the backpack. Xie et al.[349 ] utilized the frequency tuning tech-

nique to increase the output performance of the backpack while

relieving part of the acceleration load of the backpack. In addi-

tion, Martin et al.[350 ] designed a new type of energy harvesting

backpack, which can eﬀectively modulate the oscillation ampli-

tude and phase of the carrying mass while harvesting kinetic

energy. Yang et al.[ 351] proposed a TENG-based power backpack,

which has the advantages of labor-saving, shock absorption, and

power generation, as shown in Figure 8c. The backpack gener-

ates enough power to light up a low-power electronic watch and

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Figure 8. Self-powered wearable microelectronic devices: from shoulder to waist. a) Backpack based on a tube-like harvester. Reproduced with

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210 LEDs, which is expected to become a reliable power source

for wearable electronic products.

Smartwatches for health monitoring are popular in daily life,

but limited battery life and pollution produced by discarded bat-

teries limit their application. Human wrist vibrations are rich in

mechanical kinetic energy, so developing smartwatches to har-

vest wrist vibration energy is a signiﬁcant solution to the power

of human wearable electronics.[360,361 ] Cai et al.[ 362] proposed a

wrist-worn inertial energy harvester, which introduced a pair of

repulsive magnets to reduce the potential energy well depth of

the system, thereby achieving higher power output. Compared

with the traditional inertial energy harvester, the power of the

proposed energy harvester is increased by 425% under the ex-

citation of 0.7 Hz. Inspired by the structure of the woodpecker’s

head, Wang et al.[352] designed a piezoelectric array-based double-

layer ribbon energy harvester to power low-power electronics,

as shown in Figure 8d. The energy harvester has two working

modes: sports mode and impact mode, which has strong envi-

ronmental adaptability. The prototype has a maximum output of

15.41 mW, enough to power a watch or screen continuously. Ding

et al.[353 ] designed an electromagnetic-triboelectric hybrid energy

harvester, which harvests kinetic energy and supplies power to

electronic watches (Figure 8e). The coordinated operation of the

electromagnetic unit and the triboelectric unit has a better output

performance than that of a single energy harvesting unit. In ad-

dition, Zhao et al.[64] designed a self-powered electronic watch for

monitoring human sweat glucose levels, as shown in Figure 8f.

The proposed smartwatch is powered by a ﬂexible photovoltaic

cell to drive the operation of the electrochemical glucose sensor.

In order to improve the battery life of wearable electronic de-

vices, many smart bracelets with built-in generators have been

developed. These wristband generators can be integrated with

wearable devices to harvest environmental energy (such as hu-

man kinetic energy,[363] human thermal energy,[364] and solar

energy,[365] etc.) to build a self-powered system for health mon-

itoring. Wristband energy harvesters are mostly driven by mag-

netic beads, which eﬀectively convert inertial kinetic energy into

electrical energy. As shown in Figure 8g, Shi et al.[354 ] proposed a

wristband piezoelectric-electromagnetic hybrid energy harvester

driven by magnetic beads to harvest energy from arm swings. The

movement of the human body drives the rolling of the magnetic

beads, and the magnetic beads pass through the coil and drive the

piezoelectric beam to vibrate, realizing the conversion of kinetic

energy into electrical energy. The arm swings for 40 seconds, and

the electric energy generated by the energy harvester can drive the

hygrometer to work for 9.5 minutes. Maharjan et al.[355 ] proposed

a wearable hybrid electromagnetic-triboelectric nanogenerator to

capture low-frequency wrist motion (Figure 8h). The surface of

the magnetic ball has a micro-nano structure, and the contact

with the inside of the hollow tube generates an electric current.

The combination of the two charging methods of electromag-

netic induction and electrostatic induction signiﬁcantly improves

the output performance of the generator. In order to further im-

prove the output performance of the energy harvester, Maharjan

et al.[266 ] also demonstrated a novel curve-shaped wristband hy-

brid generator. The authors study the characteristic trajectories

under diﬀerent swing behaviors as a basis for the design of the

curve shape of the hybrid generator. The heat emitted by the hu-

man body is considered a huge energy source, and thus wearable

thermoelectric generators are considered as a promising energy

harvesting device. Kim et al.[356 ] proposed self-powered electro-

cardiography based on a wearable thermoelectric generator, as

shown in Figure 8i. The output power density of the wearable

thermoelectric generator exceeds 38 μWcm

−2in the ﬁrst 10 min-

utes, which is enough to drive the operation of electrocardiogra-

phy. In addition, wrist-worn microelectronic devices with health

monitoring functions, such as wearable sweat analysis devices,

show widespread social demand.[366 ] Qinetal.

[367 ] proposed a

wrist-worn self-powered sweat sensor based on a cellulose-based

conductive hydrogel. The sensor has high ﬂexibility, stability and

sensitivity, and eﬀectively solves the problems of insuﬃcient ma-

terial healing and unstable power supply in visual sweat compo-

nent analysis.

In the era of the IoT and AI, the human-machine interface

is an eﬀective means to achieve immersive communication be-

tween humans and machines. Fingers are one of the very dex-

terous parts of the human body, capable of performing and ex-

pressing a large number of complex gestures, and are suitable as

a carrier of human-machine interaction.[368 ] The sensing inter-

face for capturing ﬁnger motion is mainly divided into a single

ﬁnger-bending sensor and an integrated sensing glove.[369,370 ] In

recent years, many smart gloves have been developed to ﬁnely

capture ﬁnger movements and cooperate with machine learn-

ing to achieve more interactive functions.[371,372 ] As shown in

Figure 8j, Sun et al.[357] proposed a tactile perception system

with haptic-feedback rings for portable human-computer inter-

action. The integrated ring consists of triboelectric and pyroelec-

tric sensors, enabling tactile and temperature sensing, as well as

vibration and thermal tactile feedback. Based on the proposed

integration loop, a gesture recognition system supporting ma-

chine learning is developed, and the recognition accuracy rate

for 14 gestures is 99.821%. Smart gloves based on multi-modal

tactile perception systems can face more complex and sophis-

ticated human-machine interaction applications. Zhu et al.[373]

propose a modular soft glove with multimodal sensing and feed-

back functions, which can eﬀectively detect static and dynamic

Wiley-Blackwell.

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contact, vibration, strain, and pneumatic actuation. In addition,

Zhu et al.[358 ] also designed a smart glove with tactile feedback

for virtual reality applications, which consists of triboelectric ﬁn-

ger sensors, palm sensors, and piezoelectric tactile stimulators,

as shown in Figure 8k. The glove provides new possibilities for

human-computer interaction applications and can be used in

robot control, sports rehabilitation, and medical industries. In

addition to advanced robot control and human-machine interac-

tion, sign language gesture recognition is of great help to facil-

itate communication between sign language users and the out-

side world. Wen et al.[374] designed a sign language recognition

and communication system based on triboelectric smart gloves,

which can not only recognize single words but also recognize en-

tire sentences. The system achieves 91.3% and 95% recognition

accuracy for words and sentences in a non-segmented frame-

work, demonstrating strong sign language recognition capabil-

ities. Besides, a ﬂexible smart glove for detecting organophos-

phorus chemical threats was also reported.[375 ] An organophos-

phate hydrolase-based biosensor system on the index ﬁnger of

the glove enables rapid on-site detection of organophosphate

nerve-agent compounds. The biosafety testing glove could play

a huge role in defense and food safety applications. The above

human-computer interactions based on smart gloves are rela-

tively indirect and have weak visualization eﬀects. In order to

achieve more direct and visual human-computer interaction, Lu

et al.[359 ] proposed a visual-tactile sensing glove based on TENG,

which achieves direct touch recognition and feedback (Figure 8l).

The glove can easily convert touch stimulation into a visually vis-

ible light signal (9.8 cd m−2), achieving visual feedback of grasp-

ing intensity and status, showing great potential for advanced

human-computer interaction.

5.3. Self-Powered Wearable Devices: Below the Waist

The movement of the lower limbs of the human body contains

enormous mechanical kinetic energy, which can reach tens of

watts. Therefore, a large number of rigid exoskeleton energy har-

vesters have been developed to harvest the kinetic energy of knee

joints,[99] ankle joints,[376] hip joints,[ 377] and shoe soles,[74] as

shown in Figure 9. In addition, the capture and monitoring of

lower limb movement have also attracted widespread attention.

Smart shoes and socks have been developed to achieve this pur-

pose of capturing and monitoring lower limb movement.[378,379 ]

When humans move, there is an inﬂow and outﬂow of energy

between muscles and joints. The mechanical energy of the lower

limbs (knees, ankles, and buttocks) accounts for the vast major-

ity of the energy generated by the human body. Collecting me-

chanical energy from lower limb movements is one of the eﬀec-

tive solutions to the power supply problem of wearable electronic

devices. Therefore, many rigid energy harvesters have been de-

veloped to harvest the energy of human walking to provide elec-

trical energy for wearable devices.[386 ] Fan e t al. [387 ] proposed a

lightweight biomechanical energy harvester, which has the ad-

vantages of lightweight, high power density, and low metabolic

cost. The electromagnetic energy harvester is designed based on

the cable pulley mechanism, which harvests the motion of the

knee joint in a full cycle and provides an eﬀective solution for

solving the energy problem of low-power electronic devices. Dur-

ing a gait cycle, the muscles perform both positive and negative

work at the same time. The full-cycle energy harvester harvests

both positive and negative work simultaneously. However, the

negative energy harvester only works when the muscles perform

negative work, which can help the joints to decelerate, so it is an-

other hot spot in the research of lower limb energy harvesting.[388 ]

As shown in Figure 9a, Donelan et al.[24] designed a knee joint

energy harvester based on electromagnetic eﬀects to harvest the

negative work of human walking. The device has an average out-

put of 5 W and the cost of energy harvesting is less than one-

eighth of that for conventional human power generation. This

negative energy harvester can power portable medical devices

and is a milestone in joint energy harvesting research. Humans

need to consume a lot of energy when walking, so a lot of re-

search focuses on using exoskeleton devices to provide assis-

tance for human walking to reduce the energy consumption of

walking.[389,390 ] Slade et al.[391 ] designed a portable ankle exoskele-

ton to provide assistance for human walking. The device helps

reduce metabolic energy expenditure, and the assistance reduces

energy consumption by 23 ±8% when users walk at a speed of

1.5 m·s−1. Lower limb health monitoring is usually achieved by

obtaining physiological information such as the user’s posture,

speed, and strength. It plays a huge role in the health monitoring

of the elderly, medical care, and sports guidance.[392] Luo et al.[ 380]

proposed a wearable brace for rehabilitation assessment of pa-

tients with total knee arthritis, as shown in Figure 9b. The bracket

is composed of a force transducer for isometric muscle strength

measurement and a TENG angle sensor of the knee joint. Clin-

ical experiments have proved that the bracket is beneﬁcial to re-

habilitation enhancement. Furthermore, Gao et al.[393] designed

an intelligent lower limb system with motion capture and energy

harvesting for motion rehabilitation applications. The system uti-

lizes a sliding piezoelectric generator for energy harvesting and

a ratchet-based triboelectric nanogenerator (R-TENG) for lower

limb motion sensing. Furthermore, this paper demonstrates the

promise of R-TENG in multiple application scenarios such as

rehabilitation monitoring, VR gaming, and motion monitoring.

Kong et al.[17] proposed a self-powered sensing lower limb system

with deep learning capabilities for smart healthcare (Figure 9c).

The system features motion capture and negative energy harvest-

ing. In addition, the system can achieve an identity recognition

accuracy of 99.68% and a motion detection accuracy of 99.96%.

The energy generated by foot movement during human walk-

ing can reach 2–20 W, so converting the mechanical energy of

human walking into electrical energy to power portable elec-

tronic devices is a promising solution.[394 ] Many researchers

have developed energy harvesters embedded in shoes to har-

vest energy from foot movements, which can be classiﬁed

into electromagnetic,[381 ] piezoelectric,[395 ] triboelectric,[288 ] and

magnetostrictive.[81] In the process of human walking, the pres-

sure on the soles of the feet changes periodically, which is a

reusable energy source. Jeong et al.[396] designed a piezoelec-

tric energy harvester to power LED shoes. The pressure of hu-

man walking acts on the generator to generate electricity, which

can generate an output power of 800 μW at a resistive matching

point of 400 kΩ. In addition to using the pressure on the soles

of the feet, the bending deformation of the feet can also be used

to generate electricity, and it also avoids the limitation of scarce

space on the soles. Wang et al.[381] proposed an electromagnetic

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Figure 9. Self-powered wearable microelectronic devices: below the waist. a) Negative energy harvester based on electromagnetic eﬀect. Reproduced

Nature.

energy harvester based on shoe sole bending to power portable

devices such as navigation and gait monitoring, as shown in

Figure 9d. The design converts the bending of the foot into a

unidirectional rotation of a generator with an average output of

≈10 mW, enough to power micropower sensors. Due to the low-

frequency nature of human foot motion, most energy harvesters

have low output eﬃciency. Therefore, Tao et al.[ 397] proposed a

triboelectric rotational energy harvester with a mechanical gear

clutch transmission system to convert ultra-low frequency hu-

man motion into high-speed and long-lasting rotation to improve

energy conversion eﬃciency. In addition, the design achieves a

constant DC output through the phase coupling eﬀect, which can

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generate a maximum output current of 10.1 μA and an average

output power of 3.95 mW. In addition to harvesting plantar en-

ergy, sensing foot posture is crucial to reﬂect the state of motion

and health. Yang et al.[382 ] designed a TENG-based in-shoe sen-

sor pad to monitor the real-time stress distribution on the top

of the foot for guiding the training of athletes and the custom

design of shoes (Figure 9e). The detection range of the sensor

reaches 7.27 MPa, and it can realize the functions of step count-

ing and human-machine interaction, which has a great eﬀect on

promoting smart sports. Furthermore, Lin et al.[383] proposed a

multifunctional gait monitoring smart insole that eﬃciently con-

verts mechanical triggers/shocks into electrical outputs via elas-

tic TENG (Figure 9f). The smart insole can accurately monitor

and distinguish various gait patterns, including jumping, strid-

ing, walking, and running, for gait analysis and rehabilitation as-

sessment. In addition, the insole can also monitor falls, which is

very helpful for the safety monitoring of patients and the elderly.

The smart shoes discussed above all have good self-powering and

self-sensing properties. However, it is worth noting that a lot of

sweat occurs during walking. This will expose the shoe to a rela-

tively high humidity environment, which will aﬀect the perfor-

mance of the wearable sensor. In order to solve this problem,

researchers have focused on developing new materials to give

the sensor good water and moisture resistance, thereby improv-

ing device sensitivity and reliability.[398] Liu et al.[ 399] developed a

moisture-proof sensing insole based on nanocellulosic triboelec-

tric materials with micro-mountain arrays, which can eﬀectively

sense gait and motion status. The sensor has excellent hydropho-

bicity and moisture resistance, allowing it to maintain a full-scale

output retention rate above 82.4% at 98% relative humidity.

Gait is a rich sensory information of the human body, which

contains information such as health status and personal iden-

tity. A normal gait allows people to carry out activities of life with

ease, but gait disorders disrupt these normal activities. There-

fore, monitoring gait patterns is very important for healthcare,

sports instruction, identiﬁcation, etc. Compared to smart shoes

and insoles, socks are more ﬂexible and comfortable.[400 ] In ad-

dition, socks are in direct contact with the feet and are more

widely applicable to indoor scenes, so socks are one of the best

choices for gait analysis. Hossain et al.[401 ] large-scale fabrication

of core-shell triboelectric braided ﬁbers and power textiles for

energy harvesting and plantar pressure monitoring proposed a

self-powered sock to sense footsteps, which is based on a single-

electrode mode triboelectric sensor that converts plantar pres-

sure into an electrical signal. In addition, Li et al.[384 ] proposed a

large-scale preparation method of core-shell triboelectric braided

ﬁbers with stable structure and strong tensile strength to solve

the problems existing in the large-scale manufacturing of ﬂex-

ible wearable devices. Combining this method with traditional

socks, a smart sock was developed to detect plantar pressure dis-

tribution, as shown in Figure 9g. The sock has 16 single-sensor

units that can easily detect the mapping of foot pressure in diﬀer-

ent body postures. Jeerapan et al.[402] design a biofuel cell-based

self-powered sensor with highly stretchable properties that can

sense changes in human metabolites. The early development of

smart socks focused on the perception of single sensory informa-

tion, laying the foundation for the development of an intelligent

wearable system with multiple sensory information perception.

AsshowninFigure9h,Zhuetal.

[385 ] developed a self-powered

sock based on a hybrid piezoelectric and triboelectric mecha-

nism for energy harvesting and multi-physiological signal sens-

ing (gait, contact force, sweat level, etc.). The PZT module pro-

vides gait information, and the TENG module senses sweat level

and impact force. This multi-information-perception smart sock

shows great potential in smart homes, motion monitoring, and

smart healthcare. Traditional information-perception socks can

only obtain shallow features from raw data, and cannot further

extract deeper information. Wearable electronic products based

on AI technology have stronger analysis and prediction capabili-

ties and have shown great potential in image processing, speech

recognition, and human activity recognition. Besides, the fur-

ther developed human-machine interface enables wearable prod-

ucts to have wider applications. Zhang et al.[100 ] developed a deep

learning-enabled triboelectric smart sock for gait analysis and VR

applications (Figure 9i). Based on the optimized deep learning

model, the triple-sensor sock has achieved 93.54% identiﬁcation

accuracy for 13 users and 96.67% detection accuracy for 5 diﬀer-

ent human activities.

5.4. Self-Powered Implantable Microelectronic Devices for Smart

Healthcare

Smart healthcare combines modern information technology with

medical services, which is of great signiﬁcance to improving

the eﬃciency and quality of medical services, reducing medical

costs, and improving patient satisfaction and health status.[403 ]

In recent years, a large number of implantable biomedical de-

vices have been developed to promote the continuous progress

of smart medicine. Implantable devices are used to monitor

the health status of the body, assist in the treatment of dis-

eases, and realize biometric identiﬁcation by implanting elec-

tronic devices into the human body.[404] However, the size, qual-

ity, and power life of implantable devices are huge challenges.

Relying on self-powered technology, harvesting energy from

human activities and the physiological environment to drive

the operation of miniaturized implantable devices is a feasible

solution.[405 ] Common self-powered implantable devices include

cardiac pacemakers,[406 ] cardiovascular monitors,[407 ] nerve and

muscle stimulators,[408 ] drug delivery systems,[409 ] etc., as shown

in Figure 10.

A pacemaker is an implanted medical device used to treat

heart conditions such as arrhythmias. It is connected to the

heart via electrodes and controls the beating of the heart through

electrical stimulation when needed.[91] However, pacemakers re-

quire regular checks and battery replacements, resulting in sig-

niﬁcant replacement costs and risks. Self-powered cardiac pace-

makers based on piezoelectric and triboelectric eﬀects provide

a low-cost, reliable, long-running solution for cardiac moni-

toring and therapy.[410] Piezoelectric ceramic-based transducers

have high sensitivity and fast response, and are easy to real-

ize miniaturized design, so they can be integrated into cardiac

pacemakers.[411 ] As shown in Figure 10a, Shi et al.[412 ] proposed

a MEMS-based broadband piezoelectric ultrasonic energy har-

vester for self-powered cardiac pacemakers. The energy harvester

is a PZT diaphragm array with a wide working bandwidth. Ad-

justing the frequency of the device reduces the standing wave ef-

fect at any given distance, which will beneﬁt the output stability

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Figure 10. Self-powered implantable microelectronic devices for smart healthcare. a) A MEMS-based broadband piezoelectric ultrasonic energy harvester

b) An energy harvesting strategy that does not directly contact the heart to prolong the lifespan of cardiac pacemakers. Reproduced with permission.[413]

e) A triboelectric pressure sensor based on bioabsorbable materials for monitoring abnormal vascular occlusive events. Reproduced with permission.[416]

implantable biodegradable PENG for the development of ultrasound-driven wireless electrical stimulation. Reproduced with permission.[418 ] Copyright

self-powered system consisting of stacked TENG and a multiple-channel epimysial electrode to directly stimulate muscles. Reproduced under the terms

of the energy harvester. At present, almost all implantable cardiac

energy harvesters are in direct contact with the epicardium or

pericardium, which poses potential risks to patients. Therefore,

Dong et al.[413 ] developed an energy harvesting strategy that does

not directly contact the heart to prolong the lifespan of cardiac

pacemakers (Figure 10b). This strategy achieves energy harvest-

ing by integrating a self-winding helically conﬁgured piezoelec-

tric ﬁlm on a pacemaker lead. It is proved by experiments that

10 ×10 helical piezoelectric arrays are all wrapped on the

lead wires, which can prolong the life of the pacemaker by

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1.5 years. The proposed strategy presents a demonstration of in

vivo biomedical energy harvesting. TENG has also received at-

tention in the study of self-powered cardiac pacemakers. Ouyang

et al.[414 ] proposed an implantable TENG-based symbiotic car-

diac pacemaker for energy harvesting, storage, and cardiac pac-

ing (Figure 10c). The implantable TENG has an open circuit volt-

age of 65.2 V and can harvest energy of 0.495 μJ per cardiac mo-

tion cycle, which is higher than the threshold energy of 0.377 μJ

for endocardial pacing. The pacemaker has successfully achieved

cardiac pacing in a large animal model and can correct sinus ar-

rhythmia and other conditions. The development of this symbi-

otic pacemaker provides a reference for the development of in

vivo symbiotic bioelectronics.

Cardiovascular diseases such as arrhythmia, high blood pres-

sure, and arteriosclerosis can reduce or interrupt blood ﬂow in

the cardiovascular system, thereby aﬀecting the functions of var-

ious organs in the body. Develop an implantable self-powered

cardiovascular monitor for monitoring the health status of the

heart and vascular system, which can help doctors diagnose and

treat cardiovascular diseases, as well as monitor changes in pa-

tient conditions.[421 ] Among them, blood pressure monitoring

is a necessary link for hypertensive patients to understand their

own health status. As shown in Figure 10d, Cheng et al.[415 ] pro-

posed a self-powered implantable blood pressure monitor based

on piezoelectric ﬁlm to monitor high systolic blood pressure

of the aorta at all times. The piezoelectric ﬁlm is wrapped in

the aorta, and its output voltage has a linear relationship with

blood pressure. Therefore, the monitor can accurately monitor

blood pressure with a sensitivity of 173 mV mmHg−1.Inad-

dition, an implantable, self-powered, and visualized blood pres-

sure monitoring system has been established and successfully

operated, which can monitor hypertension status in real-time

and send out alarms, showing great prospects in the ﬁeld of im-

plantable medical monitoring. Vaso-occlusion is another cause

of cardiovascular disease, so the monitoring of vaso-occlusion is

also very important. Ouyang et al.[416 ] proposed a triboelectric

pressure sensor based on bioabsorbable materials for monitor-

ing abnormal vascular occlusive events (Figure 10e). The sensor

eﬃciently converts ambient pressure into electrical signals and

successfully identiﬁes vaso-occlusive events in large animals. The

sensor has excellent sensitivity (11 mV mmHg−1) and linearity

(R2=99.3%) and has excellent durability (450 000 cycles). The

sensor has a lifespan of 5 days and a degradation and absorption

time of 84 days, making it useful for cardiovascular postoperative

care. Heart failure is caused by insuﬃcient pumping ability of

the heart, and endocardial pressure is an important parameter to

evaluate the pumping ability of the heart. Liu et al.[417 ] developed

a TENG-based ﬂexible self-powered endocardial pressure sensor,

as shown in Figure 10f. Experiments were performed using a

porcine model, and the sensor showed good responsiveness in

both low and high-pressure environments. In addition, the sen-

sor has excellent linearity (R2=99.7%) and sensitivity (1.195 mV

mmHg−1). In the experiment, cardiac arrhythmias such as ven-

tricular ﬁbrillation and premature beats were also successfully

detected by the sensor, showing its broad prospects in monitor-

ing and diagnosing cardiovascular diseases.

Electrical stimulation is a method of rehabilitation therapy

used to promote the repair of damaged tissues such as nerves

and muscles. The self-powered implantable electrical stimula-

tion strategies based on energy harvesting technology can be

mainly divided into nerve stimulation strategy and muscle stim-

ulation strategy.[422,423] Neurostimulation strategies stimulate the

neurophysiological signals of the nervous system through elec-

trical action to manipulate the respective body functions. PENG

and TENG have been integrated with neural interfaces for

forming neurostimulation strategies.[424 ] Wu et al.[418] prepared

an implantable biodegradable PENG for the development of

ultrasound-driven wireless electrical stimulation (Figure 10g).

Ultrasound acts as an external wireless energy source to excite

the PENG, which delivers adjustable electrical stimulation to a

biodegradable conductive nerve guide. The PENG can be used

as an implantable neurostimulator, which generates alternating

electrical stimulation to promote nerve regeneration and mon-

itor nerve repair. Furthermore, Li et al.[419 ] proposed a stacked

TENG-based neural interface for direct neural stimulation, as

shown in Figure 10h. This neural interface serves as a univer-

sal electrode for selective stimulation and recording of the sci-

atic nerve. In addition, this neural interface can directly stimu-

late the sciatic and common peroneal nerves to modulate and

control the tibial anterior muscles. This work combines self-

powered technology and neural interface, providing new ideas for

battery-free neuromodulation strategies. Electrical muscle stim-

ulation uses electrical signals to stimulate diseased muscles and

is a treatment for muscle function recovery. Wang et al.[420 ] pro-

posed a self-powered system consisting of stacked TENG and a

multiple-channel epimysial electrode to directly stimulate mus-

cles (Figure 10i). This work successfully veriﬁed the feasibility

of TENG to directly stimulate muscles with good stimulation

eﬃciency and stability. The successful realization of this work

laid the foundation for the development of an implantable self-

powered muscle electrical stimulation system.

The development of drug delivery systems is a major advance-

ment in smart medicine. Traditional pulse drug delivery sys-

tems mainly rely on commercial power supplies, which greatly

limits the promotion and application of drug delivery systems.

The drug delivery system combined with self-powered technol-

ogy does not require an external power supply, greatly reduc-

ing cost and weight while expanding the application scope of

the system.[409 ] The electrical stimulation drug delivery system

combines a self-powered sensor and a microchip to activate the

electrosensitive drug carrier through an electric ﬁeld and re-

lease the drug at the target point.[425 ] Ouyang et al.[426 ] pro-

posed a self-powered transdermal drug delivery system based

on TENG. The system consists of a TENG and a power man-

agement circuit, which cooperate with each other to release

drugs on demand. Experiments show that the system has an

adjustable drug release rate between 0.05 and 0.25 μgcm

−1.

In addition, Zhao et al.[427 ] developed an intelligent drug deliv-

ery system based on implantable TENG and red blood cells for

In Situ Hepatocellular Carcinoma Therapy. Implantation experi-

ments on rabbits demonstrated the excellent therapeutic eﬀects

of this system. Microneedle is a new type of physical penetration-

promoting technology, which consists of multiple micron-sized

tiny needle tips in an array.[428] Microneedles can be directed

through the stratum corneum to create micron-sized mechan-

ical channels and place drugs directly on the epidermis or up-

per dermis to exert pharmacological responses. The microneedle

drug delivery system has the advantages of a stable transdermal

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absorption rate, reducing or eliminating pain, and convenient

drug administration.[429 ] Yang et al.[430 ] developed a microneedle-

based self-powered transdermal electrical stimulation system by

integrating TENG and microneedle patches to improve epider-

mal growth factor pharmacodynamics. In addition, the team also

developed a self-powered controllable transdermal drug delivery

system based on piezoelectric nanogenerators.[431 ] The system re-

leases 8.5 ng of dexamethasone when electrically stimulated and

is used to treat psoriasis-like skin disease. The disease treatment

eﬀect of this system is better than traditional treatment methods,

providing a promising method for intelligent medical treatment.

Self-powered microneedle drug-carrying systems are developing

rapidly, but in order to achieve better medical eﬀects, precise con-

trol of the dosage is a major diﬃculty in the development of this

ﬁeld.

5.5. Self-Powered Microelectronics on Animals

With global warming and the deterioration of the ecological en-

vironment, the protection of animals is particularly important,

especially the rare animals. Portable sensors are usually used

to monitor the behavior, physiological information, and location

of the animals. Traditional battery-powered monitoring sensors

have limited life, diﬃculty in replacement, and potential envi-

ronmental pollution. Energy harvesting from the environment

(animal kinetic energy, solar energy, etc.) is considered to be an

eﬃcient alternative solution to power monitoring sensors. Cur-

rently, many self-powered animal wearable devices have been de-

veloped to monitor their health and activity habits, which can be

categorized as terrestrial animal wearable devices, aerial animal

wearable devices, and aquatic animal wearable devices, as shown

in Figure 11.

Self-powered wearable electronics used for terrestrial organ-

isms oﬀer new ideas for monitoring animal health and loca-

tion information. Tracking and telemetry devices are fundamen-

tal tools for studying the behavior of animals related to their liv-

ing environment. The data collected by these devices is of great

signiﬁcance for animal protection, optimizing ecosystems, and

studying disease models. Many energies exist in the living en-

vironment of animals and can be collected and used to provide

power for tracking and telemetry devices.[110,432 ] As shown in

Figure 11a, Badr et al.[433 ] proposed a low-frequency piezoelec-

tric energy harvester to harvest animal motion to power teleme-

try and radio equipment. The device can get an output power of

37.5 μW when the mouse is running. In addition, Hart et al.[434 ]

proposed a 180-gram solar device to power a GPS tracking device

of terrestrial animals. The proposed solar device can maintain a

high and stable voltage during long-term animal migration ex-

periments. In addition to powering tracking devices, research on

self-powered sensors to monitor animal health has also been ex-

tensively studied. Kong et al.[435 ] proposed a kinetic energy har-

vester (KEH) based on a motion enhancement mechanism for

self-powered applications in smart ranch. The proposed motion

enhancement mechanism utilizes the bistable swing character-

istic to enhance weak excitation, of which the maximum voltage

growth rate is up to 103.7%. The KEH can produce an average

output power of 7 mW, which is suﬃcient to power an IoT sensor

node. Wildlife monitoring is of great signiﬁcance for investigat-

ing the status and changes of wild animal populations, develop-

ing wildlife management strategies, and assessing the value of

wild animals. As shown in Figure 11b, Zhang et al.[109] designed

a vibration energy harvester, that can convert the random motion

of wild animals into electricity through an eccentric rotor for self-

powered animal monitoring application. It is estimated that the

energy harvester installed on the sika deer can generate energy of

212.08 J per day, which can be used for powering the monitoring

tags for ≈15 days. In addition, as human companions, pets are

increasingly receiving attention to their health status. More and

more pet wearable devices are being used for pet health and lo-

cation monitoring. Self-powered pet wearable electronic devices

based on animal energy harvesting are promising for application.

Chen et al.[436 ] proposed a TENG-based pet belt to realize a self-

powered human-pet interaction system (Figure 11c). When the

pet belt is stretched and retracted, electricity is generated to power

the LED light strip around the pet’s neck. Additionally, the belt

has been shown to power wearable electronics such as acoustic

mosquito repellents and exercise wristbands.

The monitoring of aerial animals, especially birds, has at-

tracted widespread attention. Migration is a survival instinct re-

sponse of birds to adapt to the natural environment. Tracking and

monitoring birds during their migration can help researchers un-

derstand the ecological patterns of migration time, routes, and

population relationships, providing scientiﬁc basis for protecting

rare and endangered birds. Due to the simple mechanism and

high output voltage, energy harvesters based on the piezoelectric

eﬀect are widely used to harvest energy from birds.[107] As shown

in Figure 11d, Shafer et al.[437 ] proposed a custom piezoelectric

vibratory energy harvester to harvest energy from the ﬂapping

motion of birds to power wildlife tags during the migratory sea-

son. The author ﬁrst tested two types of birds in a ﬂight tunnel

and studied their ﬂight dynamics, in order to generate resonance

between the energy harvester and the bird to improve energy har-

vesting eﬃciency. Meanwhile, Shafer et al.[438 ] also developed a

system that can simultaneously harvest energy and measure the

ﬂight acceleration of birds (Figure 11e). The system is attached to

the bird and consists of three subsystems: a piezoelectric energy

harvesting device, a data recording system, and a beam locking

system. In addition, Anthony et al.[441 ] proposed a novel sensor

platform for monitoring migratory birds, which has a great im-

pact on ecological research. The platform consists of a rich set

of sensors, a multi-modal radio, and power control circuitry for

sustainable information delivery during migration. In addition

to harvesting energy from the ﬂight of birds, researchers also

have carried out research to harvest energy from the ﬂight of in-

sects. Micro Air Vehicle (MAV) is a small insect-sized ﬂying robot

that utilizes network communication between multiple MAVs to

perform search and rescue operations, hazardous environment

monitoring, and explosive detection functions. Aktakka et al.[108]

developed a bioenergy harvester based on bicrystalline piezoelec-

tric beams to convert the mechanical vibrations of insects into

electrical energy, as shown in Figure 11f. Two initial generator

prototypes were developed which are able to generate 11.5 and

7.5 μW during tethered ﬂight.

The rapid development of wireless sensor networks makes it

possible to track aquatic animals automatically and continuously.

Sonar detection and radio telemetry are eﬀective means of mon-

itoring ﬁsh movements and their environment. Transmitters

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Figure 11. Self-powered microelectronic devices on animals. a) Low-frequency piezoelectric energy harvester powers positioning electronics. Reproduced

ican Society of Mechanical Engineers. f) Insect energy harvester based on bicrystalline piezoelectric beams. Reproduced with permission.[ 108] Copy-

integrating self-powered technology are self-sustaining and have

the potential to monitor animals throughout their life cycle.

Fish movement has huge energy, which can be obtained directly

from the vibration of the ﬁsh body, or indirectly from the ﬂuid

ﬂow around the ﬁsh body. Many self-powered ﬁsh tags have

been developed, which can be divided into implantable tags

and external tags.[442 ] Implantable electronic devices are already

widely used to monitor the health of animals and track their

location. Li et al.[112 ] developed an implantable self-powered

acoustic wave transmitter based on ﬂexible piezoelectric beams

that can harvest energy from the swimming motion of aquatic

animals. The proposed transmitter is ﬂexible and lightweight,

which will not inﬂuence the movement of the host animal. In

2022, Li et al.[111 ] again developed an implantable and lightweight

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biomechanical energy harvester using macro ﬁber composite

piezoelectric beams to harvest energy from animal body bending

motions as a power source for integrated microelectronics

(Figure 11g). Compared with PZT-5A, macro ﬁber composite

piezoelectric beam has better material fatigue resistance. An

underwater acoustic transmitter was successfully implanted

in juvenile beluga sturgeon, and the transmitter continuously

emitted signals for up to 5 weeks. Research has shown that using

biomimetic technology can improve the eﬃciency of energy col-

lectors to adapt to complex and ever-changing environments.[443 ]

Inspired by the symbiotic relationship between the remora ﬁsh

and sharks, Qian et al.[439 ] developed a self-powered animal

telemetry tag driven by a biomimetic bistable piezoelectric en-

ergy harvester, as shown in Figure 11h. The telemetry tag can be

externally placed on the dorsal ﬁn of ﬁsh to harvest hydrokinetic

energy to monitor ﬁsh habitat, population, and underwater

environment. Underwater experiments show that the proposed

energy harvester can eﬃciently convert ﬁsh swings into electrical

energy. As shown in Figure 11i, Wang et al.[440] developed a mul-

tifunctional ﬁsh wearable data-snooping platform based on an

air sac triboelectric nanogenerator with an antibacterial coating

to study ﬁsh kinematics. The air sac triboelectric nanogenerator

can generate a peak output voltage of 150 V and a peak output

power of 0.74 mW. In addition, the detailed parameters of ﬁsh

movement, including swing angle and swing frequency, can be

obtained through the voltage of air sac triboelectric nanogener-

ator. Therefore, the developed platform may greatly facilitate the

study of ﬁsh behavior and its neural basis.

5.6. Self-Powered Microelectronics in Intelligent Transportation

The development of transportation, whether it is land transporta-

tion, water transportation, or aerospace development, has eﬀec-

tively promoted the progress of society and economic develop-

ment. Especially, intelligent transportation systems bring safety

and convenience to human life.[444 ] As the basis of intelligent

transportation systems, sensors are used to collect real-time sig-

nals from automobiles, trains, sea vehicles, air vehicles, roads,

tracks, etc., which are of great signiﬁcance to ensure the safe

operation of the transportation system and improve transporta-

tion eﬃciency.[445] Advanced self-powered technology provides

these sensors with stable, reliable, and renewable power.[446,447]

Figure 12 shows the typical applications of self-powered microp-

ower sensors in intelligent transportation, which can be divided

into 6 categories, including road vehicles, roadside, rail vehicles,

trackside, oceanic vehicles, and aerial vehicles.

Road vehicles are the core units in the intelligent transporta-

tion system, so the hardware monitoring of the vehicle itself is

particularly important to ensure traﬃc safety. However, some

parts of the vehicle cannot be monitored due to power and hard-

ware architecture limitations, as well as complex power line man-

agement. The micro-power smart device integrated with self-

power supply technology can collect vehicle environment energy

such as kinetic energy,[448] and solar energy,[449] and simultane-

ously can monitor the status of tires,[450 ] steering wheel,[451 ] lu-

bricating oil,[452 ] and other components of vehicle. Regenerative

shock absorbers have attracted attention because they can harvest

energy to extend the cruising range of electric vehicles. As shown

in Figure 12a, Salman et al.[453] developed an energy regenera-

tive shock absorber applied to the hub motor of an electric vehi-

cle to convert the irregular vibration of the vehicle into the regu-

lar rotation of the motor. Vibration experiments showed that the

three-phase electromagnetic generator of the regenerative shock

absorber produced an output power of more than 380W with

62% eﬃciency. In the vehicle system, the sensors are the most

important elements to monitor the driving and safety status of

the vehicle. In particular, vehicle acceleration sensors have been

used to monitor vehicle states such as collisions, anti-lock brakes,

traction, and electronic steering.[454 ] Lu et al.[455 ] proposed a self-

powered acceleration sensor based on TENG to monitor the run-

ning and collision of the car in real-time. The acceleration sensor

is based on the arrangement of triangular electrodes and interdig-

ital electrodes, which can simultaneously monitor the value and

direction of acceleration. Like cars, bicycles are also indispens-

able as travel tools. The popularity of shared bicycles in China

has made people pay more attention to the safety of bicycle rid-

ing. In addition, there is a large amount of kinetic energy in the

process of bicycle running, such as cushion vibration,[456] and

wheel rotation.[457 ] Zhou et al.[458 ] developed a dual-mode rota-

tional triboelectric nanogenerator to harvest energy from bicy-

cle rotational braking (Figure 12b). This generator can charge a

300 μF capacitor to drive the speedometer operation.

Roads provide support for the movement of vehicles and

pedestrians, which directly aﬀects traﬃc safety. Roads are ex-

posed to the external environment and load movement, so there

are many renewable energy sources such as solar energy, geother-

mal energy, and mechanical energy in the road environment.

In addition, tens of thousands of sensors are used in the con-

struction of smart roads, which require a large amount of dis-

tributed energy as support. In recent years, researchers have

developed plenty of road self-powered sensor systems to pro-

mote the development of smart roads, which can be divided

into four categories, including wind and solar energy harvesting-

based type,[242 ] vehicle kinetic energy harvesting-based type,[468]

pedestrian kinetic energy harvesting-based type,[304 ] and speed

bump vibration energy harvesting-based type.[469 ] As shown in

Figure 12c, Qi et al.[40] developed a wind-solar hybrid power gen-

eration system based on a foldable umbrella mechanism, which

harvests solar energy and wind energy generated by vehicles to

provide power for highway electrical equipment. Highway bridge

is an eﬀective way for pedestrians and cars to cross physical barri-

ers, and bridge safety is also crucial to driving safety. Cao et al.[470]

proposed a piezoelectric-electromagnetic hybrid wind energy har-

vesting system for wind energy harvesting on canyon bridges to

power low-power sensors for bridge health monitoring. In addi-

tion to harvesting wind and solar energy, the kinetic energy gen-

erated by vehicles is an excellent renewable energy source. As

shown in Figure 12d, Jeon et al.[459] proposed a lever-type piezo-

electric energy harvester to harvest kinetic energy from the road

surface to be used as a power source for electric vehicle charg-

ing stations. The harvesting module produces 60.3 mW under 1

mm displacement, showing potential as a power source for elec-

tric vehicles. With the rapid development of smart transporta-

tion, vehicle speed needs to be monitored to reduce the accident

rate.[471 ] Cao et al.[ 472] designed a TENG-based self-powered over-

speed wake-up alarm system. This system provides an eﬃcient

and low-cost method for vehicle speed monitoring in unattended

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Figure 12. Self-powered microelectronic devices for intelligent transportation. a) Energy regenerative shock absorber for electric vehicle hub motor.

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traﬃc environments. In addition, the monitoring of other traf-

ﬁc violations is also necessary. Yun et al.[473] design a paint-based

TENG to build an intelligent traﬃc intrusion detection system.

The proposed system successfully detects traﬃc violations by hu-

mans or vehicles, which will contribute to the advancement of

traﬃc safety systems.

Rail transit, especially high-speed railways, has developed

rapidly in recent years. The operation safety of the rail transit

system is very important, so it is imperative to develop monitor-

ing devices for the railway environment based on self-powered

technology. Rail vehicles, such as high-speed rail, freight trains,

and urban express trains, are huge in size and have many com-

ponents, which brings challenges to safety monitoring.[474,475 ] Vi-

bration caused by rail vehicles is very common, which will in-

crease the risk of track wear and train derailment, thereby threat-

ening driving safety. Therefore, real-time monitoring of the key

components of the train is very necessary, such as monitoring

to carriage,[67] bogie,[476] and wheelset.[ 477] Fang et al.[478 ] devel-

oped a regenerative vibration energy harvesting system to harvest

the kinetic energy of the bogie to power freight train monitor-

ing sensors. Based on the design of the inertial pendulum and

motion conversion module, the system converts train vibration

into unidirectional rotation and can reach a peak output power of

1.04 W. The bogie contains huge kinetic energy, and the vibration

of the bogie can reﬂect the running state of the vehicle.[479 ] Fur-

ther, Fang et al.[460 ] proposed a triboelectric nanosensor based on

roller bearings to detect the running state (steady state and in-

stability) of freight trains, as shown in Figure 12e. Combining

the preprocessing module and the LSTM deep learning module,

the eﬀective detection of the train running status can be realized,

and the detection accuracy rate reaches 96.6%. As an important

and easily worn part of the bogie, wheels have attracted much

attention in monitoring their health and stability. As shown in

Figure 12f, Jin et al.[461] developed a TENG that collects the ki-

netic energy of train wheels for wheel safety monitoring. The de-

signed free-ﬁxed TENG has no negative impact on the wheel and

can generate a maximum power of 15.68 mW. In addition, the

TENG can be used to monitor the rotation speed and tempera-

ture of the wheel in real-time, which provides a new idea for the

development of intelligent transportation.

The exploration of self-powered technology on the railway side

is also a research hotspot. The safe operation of rail transit is

inseparable from the assistance of trackside electronics, such as

signal lights, and railway health monitoring sensors.[480 ] Rail vi-

bration and wind energy caused by running trains can be used

as power sources for trackside electronic devices.[481,482 ] Due to

the uneven surface roughness of the track, the running train can

cause the vertical vibration of the track, with amplitudes rang-

ing from 1 to 12 mm and frequencies ranging from 1 Hz to

4Hz.

[483 ] The vibration energy harvester based on the electro-

magnetic generator can eﬀectively harvest the vibration energy

of the rail track to power the trackside electronics. Pan et al.[484]

developed an electromagnetic vibration energy harvester based

on a compact ball screw and a mechanical rectiﬁer, which can

generate an average power of 2.24 W at a speed of 30 km h−1.

Due to the obvious nonlinear and width characteristics of rail

track vibration, the acquisition eﬃciency of linear and narrow

bandwidth vibration harvesters is low. Therefore, Dong et al.[485]

proposed an enhanced rail track vibration piezoelectric harvester

(PEH) whose dual-mass conﬁguration can signiﬁcantly enhance

the harvesting performance. The output voltage of the proposed

PEH under time-domain pulse excitation is 6 times that of the

normal PEH. Track vibration is a satisfactory renewable energy

source, but it will have a huge impact on the safe operation of

trains. Rail corrugation is a serious rail defect that may cause

noise and vibration on the ground and nearby buildings during

running of trains, as well as aﬀect the safe operation of trains.

In order to realize the online monitoring of rail corrugation, Sun

et al.[462 ] proposed a rail corrugation monitoring system based

on a triple-repellent electromagnetic energy harvester, as shown

in Figure 12g. Based on the measured railway track spectrum,

the system has a wide energy acquisition bandwidth, and can ef-

fectively identify rail corrugations through induced voltage. The

abundance of wind energy generated during rail vehicles running

is another considerable renewable energy source for powering

trackside electronics.[486 ] As shown in Figure 12h, Pan et al.[463]

developed a renewable energy harvesting wind barrier for railway

self-powered applications. The proposed wind barrier is based on

the design of coaxial counter-rotation to improve the acquisition

performance and can achieve an average power output of 0.8 W.

In addition, the wind barrier can eﬀectively reduce the inﬂuence

of crosswinds on the train and improve the safety of train opera-

tions.

Another important means of transportation are marine vehi-

cles such as speedboats and yachts. In addition, marine vehi-

cles are a tool for exploring ocean energy, which is equipped

with a large number of sensors and electronic devices. Maritime

vehicles are in the energy-rich environment of the ocean, so

wave energy acquisition technology based on maritime trans-

portation has broad application prospects.[487 ] Li et al.[488 ] de-

veloped a piezoelectric generator to harvest energy from ma-

rine vehicle suspension systems, which consisted of six indi-

vidual piezoelectric stack units. The piezoelectric generator has

proved to be of great help in constructing self-powered sensor

networks for marine vehicles through laboratory and oﬀshore ex-

periments. As shown in Figure 12i, Zhang et al.[464 ] developed an

2020, Elsevier. d) Lever-type piezoelectric energy harvester for harvesting kinetic energy from the road surface. Reproduced with permission.[ 459] Copy-

right 2021, Elsevier. e) Triboelectric nanosensor based on roller bearings to detect the running state of freight trains. Reproduced with permission.[460]

American Association for the Advancement of Science.

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electromagnetic-triboelectric hybrid nanogenerator to eﬃciently

harvest wave energy. A shipping platform is developed based on

the designed generator to improve the stability and economy of

energy harvesting. Through experiments, the hybrid nanogen-

erator can output a power of 358.5 W·m−3. Smart ships based

on the IoT and self-powered technology have developed rapidly,

which is of great signiﬁcance to navigation safety, monitoring of

personnel on board, and monitoring of the hull.[90] Ships are usu-

ally in harsh sea conditions, so it is very necessary to monitor the

motion attitude of the ship. Wang et al.[489] proposed a tilt sen-

sor based on annular liquid-solid interfacing TENG to monitor

the attitude of the ship. The foundation of ship safety is person-

nel safety, so Wang et al.[490 ] proposed a triboelectric smart ﬂoor

mat based on deep learning. The smart ﬂoor mat has person-

nel and status identiﬁcation, as well as positioning and counting

functions, which can realize comprehensive monitoring of crew

members and cargo. Ships have been in harsh marine environ-

ments with high salinity and high corrosive characteristics for a

long time, and the application of anti-corrosion technology is an

eﬀective way to prolong the service life of marine equipment.[491 ]

Wang et al.[465] proposed a liquid–solid TENG to evade the ma-

rine anticorrosion of ships (Figure 12j). The proposed TENG has

good triboelectriﬁcation performance and weak ion adsorption

eﬀect, which can reduce the friction coeﬃcient of seawater by

43.8%, which will signiﬁcantly reduce the navigation resistance

of ships.

Energy and sensing are even more integral in aircraft and

aerospace to ensure the success of ﬂight and space exploration

missions. The introduction of self-power technology can greatly

improve the energy saving, reliability, and intelligence of the

system.[492 ] During high-speed ﬂight, an aircraft usually encoun-

ters strong airﬂow, which causes vibration of the fuselage and var-

ious components. In addition, the landing gear also has a huge

vibration energy when the aircraft is landing. Du et al.[493 ] pro-

posed a method based on a 2-DOF resonant system with energy

harvesting and shock absorption. The method could be used in

the landing gear of an aircraft to act as a buﬀer while recovering

energy. Furthermore, Tao et al.[466 ] proposed a cellular-inspired

TENG for, unmanned aerial vehicle (UAV) deformable wing en-

ergy harvesting, as shown in Figure 12k. The generator’s honey-

comb structure has multiple power generation units, which can

reach a high output performance of 1207 V and 12.4 mW. Further,

the proposed TENG is installed in the deformable wing of a small

UAV to realize the conversion of ﬂapping wing energy into elec-

trical energy. As the core component of the aircraft, the real-time

health monitoring of the jet engine is very important to ensure

ﬂight safety. Wang et al.[494 ] developed a self-powered jet engine

monitoring system based on piezoelectric generators, paving a

new way for jet engine monitoring systems. In Aerospace, self-

powered sensors are introduced to ensure the smooth execution

of space exploration missions.[495 ] Houetal.

[241 ] developed a scal-

able self-attaching/assembling robotic cluster system based on

triboelectric sensors. The sensing system can realize the percep-

tion and monitoring of the working status of on-orbit compo-

nents, so as to reduce the potential risks in the construction of

large spacecraft. In space exploration, radiation is a serious pol-

lution problem that can threaten human health. Ye et al.[ 496] de-

veloped a piezoelectric nanogenerator based on composite for

energy harvesting and radiation protection. The proposed piezo-

electric nanogenerator exhibits 9% neutron radiation shielding

capability, showing great potential to protect human beings in

the space environment. Furthermore, Shi et al.[467] developed a

self-powered electro-tactile system for a virtual haptic experience

based on a TENG array with spherical electrodes, as shown in

Figure 12l. Integrating this electro-tactile system into a spacesuit,

the direct contact of the spherical electrodes with human skin

provides users with an enhanced sense of touch.

5.7. Self-Powered Microelectronics in Smart Ocean

The ocean is a huge treasure trove of renewable energy, mainly

including tidal energy, tidal current energy, ocean current en-

ergy, and wave energy. The development of a smart ocean is in-

separable from the utilization of self-powered and self-sensing

devices. Currently, a large number of ocean energy harvesters

have been developed.[497] In particular, wave energy is the easiest

to harvest, most energy harvesters are designed to harvest wave

energy.[498] In addition, most sea areas are far away from cities,

and the application of marine self-sensing devices is of great sig-

niﬁcance for monitoring the status of remote sea areas.[499 ] In

Figure 13, self-powered devices in the ocean are mainly divided

into surface self-powered devices and underwater self-powered

devices. According to diﬀerent structural designs, sea surface

self-powered devices can be divided into: spherical structures,[500 ]

multi-layer structures,[501 ] pendulum structures,[70] and oscillat-

ing bodies.[502 ] Underwater self-powered devices can be divided

into underwater vehicles and self-powered devices using ocean

current energy.[503,504]

In this section, self-powered devices with solid-solid contacts

are mainly discussed. Most of these devices are packaged to re-

duce the impact of seawater. A self-powered device with a spher-

ical structure is one of the typical structures for harvesting wave

energy.[514] The spherical structure has the advantages of simple

structure, light weight, good ﬂexibility, low resistance, and om-

nidirectional collection of wave energy, so it has received a lot of

attention.[515 ] In the marine environment, the motion of waves

has low frequency and irregular characteristics, which poses chal-

lenges to the design of energy harvesters. As shown in Figure 13a,

Qi et al.[296 ] proposed a piezoelectric-electromagnetic hybrid gen-

erator with a spherical package structure, which is used to col-

lect wave energy to power the monitoring sensors of cross-sea

bridges. The hybrid generator consists of a piezoelectric mod-

ule, an electromagnetic module, and an energy storage module.

The motion of the water wave drives the magnetic core to pro-

duce sliding, and then cuts the magnetic lines of ﬂux to gen-

erate current, and on the other hand, drives the piezoelectric

sheet to deform to generate electricity. The collected energy is

rectiﬁed and stored in the energy storage module to power the

bridge health monitoring sensors. To improve the energy con-

version eﬃciency, Cheng et al.[516] developed a spherical TENG

with a soft-contact structure for eﬃcient wave energy harvesting.

The spherical TENG is shelled with acrylic hollow spheres and

rolled ﬂexible silica gel as a soft core, which improves the max-

imum output charge by 10 times compared with the traditional

hard-contact TENG. This work provides a new method for col-

lecting low-frequency wave motion in multiple directions. Fur-

thermore, Gao et al.[505 ] proposed a gyroscope-structured TENG

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for harvesting multidirectional wave energy (Figure 13b). This so-

lution adopts the design of internal and external generator sets,

which increases the power generation area and achieves better

performance. Under the multi-directional excitation with an ac-

celeration of 6 m s−2, the inner and outer generator sets reached

730 and 160 V respectively. In large tank experiments, this gener-

ator was suﬃcient to light LEDs and thermometers. In addition,

the generator also has excellent underwater durability, showing

the potential to develop large-scale ocean energy.

The performance of self-powered equipment with a spheri-

cal structure is superior, but there are disadvantages such as

low space utilization rate and insuﬃcient movement of internal

moving body. Self-powered devices with a multi-layer structure

have reasonable space planning, and the space utilization rate

is higher.[517] At the same time, the multi-layer and sub-area de-

sign can make the internal moving body move along the track ef-

fectively to achieve better energy harvesting eﬃciency.[518] Wang

et al.[506 ] proposed a TENG based on bionic butterﬂy wings for

multi-directional wave energy harvesting, as shown in Figure 13c.

The design of ﬁve pairs of blades can eﬀectively absorb the impact

of low-frequency water waves, thus expanding the working band-

width of the generator. With excitation as low as 1.25 Hz, the gen-

erator can produce an output voltage of 400 V, enough to light 240

LEDs and a thermometer. In addition, the generator exhibited ex-

cellent durability in the 45-day durability experiment, which has

a great role in promoting the development of smart oceans. Wu

et al.[519 ] developed a magnetic sphere-based hybrid generator

for wave energy harvesting. The generator is a spherical struc-

ture, which is divided into four areas: power management cir-

cuit, EMG module, TENG module, and magnetic ball. The water

wave drives the movement of the magnetic ball, and the magnetic

ball drives the TENG module and the EMG module to work, re-

alizing the conversion from wave energy to electrical energy. In

addition, Liu et al.[507 ] developed a nodding duck structure multi-

track TENG to harvest low-frequency wave motion, as shown in

Figure 13d. There are three layers of multi-rail TENG inside the

generator, and the electrodes and dielectric ﬁlms of each layer are

the same, which can greatly improve space utilization. The de-

sign of the multi-track structure is to guide the nylon ball along

a ﬁxed track to eﬀectively contact the dielectric layer. The maxi-

mum instantaneous power density of a single generator is 4 W

m−3, enough to light 320 LED lights. By connecting more genera-

tors in parallel, a network for harvesting large-scale ocean energy

can be formed. This idea provides a reference for large-scale de-

velopment of ocean energy. Currently, most wave energy collec-

tion is achieved by TENGs, and the erosion of water molecules

in humid environments is the main challenge limiting the per-

formance of TENGs. Speciﬁcally, in a humid environment, water

molecules accumulate on the triboelectric interface to form a wa-

ter ﬁlm, which hinders charge transfer or causes charge dissipa-

tion, thereby aﬀecting the triboelectric performance.[520 ] There-

fore, developing advanced triboelectric materials to improve their

hydrophobicity and environmental adaptability is a promising

approach. Cellulose nanoﬁbers have attracted widespread atten-

tion due to their widespread availability, lightweight, and excel-

lent performance in humid environments.[521] Recently, Zhang

et al.[522 ] proposed a superhydrophobic cellulose triboelectric ma-

terial for wave energy harvesting, which has excellent super-

hydrophobicity (water contact angle: 154.7°). Based on this ad-

vanced material, a multi-layer network structure TENG was de-

veloped, showing excellent output performance and stability.

The pendulum structure is a common structure that utilizes

a swinging mass for energy conversion and storage. The struc-

ture has a high sensitivity to external stimuli, and these stim-

uli are converted into continuous swings and drive energy con-

version modules to convert mechanical energy into electrical

energy.[523] In order to improve energy conversion eﬃciency,

many studies focus on improving the pendulum structure,

such as up-conversion pendulums,[524 ] bistable pendulums,[306 ]

spring-assisted pendulums,[525 ] double-mass pendulums,[526 ]

and chaotic pendulum.[527 ] The pendulum structure is very ef-

fective in the ﬁeld of collecting low-frequency wave energy. As

shown in Figure 13e, Li et al.[308 ] proposed an electromagnetic

pendulum energy harvester to realize low-frequency wave energy

harvesting to build a self-powered wireless water quality sens-

ing system. It is veriﬁed by theoretical analysis that no matter

whether the energy harvester is in horizontal vibration or swing

motion, the pendulum can generate periodic swings. In addition,

the energy harvester operates at a frequency as low as 1.5 Hz and

can achieve an RMS power of 14.76 mW, which is suﬃcient to

drive a low-power water quality wireless sensor. The development

of this self-powered system lays the foundation for an unattended

marine monitoring environment. Furthermore, Xu et al.[71] de-

veloped a pendulum-based hierarchical energy-harvesting TENG

for self-powered ocean wave monitoring (Figure 13f). When the

wave is small, the dual generator sets are in the primary trans-

mission state, and generator 2 does not work. When the waves

are big enough, the dual generator set is in the secondary trans-

mission state, and the two generators work together. Experiments

show that the energy generated by the double generator set is 2.3

times that of the single generator set. This work provides a ref-

erence for energy harvesting and monitoring in variable marine

environments.

Point absorber is another wave energy harvesting solution,

which is composed of an oscillating buoy and a power take-

oﬀ (PTO), which realizes the conversion from wave energy to

vier. k) A compact electromagnetic transducer for harvesting energy from ocean currents to power underwater robots. Reproduced with permission.[512]

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electrical energy.[502] The oscillating body ﬂoats on the water sur-

face and oscillates under the excitation of waves, thus driving the

PTO to work. The PTO directly driven by the mechanical struc-

ture can eﬀectively convert the linear oscillation into the rota-

tional motion of the generator. In recent years, in order to im-

prove power generation eﬃciency, research on point absorbers

has focused on: designing high-eﬃciency PTO systems,[15] and

optimizing buoy shapes.[528 ] Zhao et al.[508 ] proposed a wave en-

ergy point absorber based on a triboelectric-electromagnetic hy-

brid generator, as shown in Figure 13g. The point absorber con-

sists of an oscillating ﬂoating body, a transmission mechanism,

and a hybrid generator. The waves drive the ﬂoating body to os-

cillate, which is transmitted to the generator through the trans-

mission mechanism to generate electrical energy. In the actual

wave tank experiment, when the wave height is 16 cm and the

frequency is 0.8 Hz, TENG and EMG generate peak open-circuit

voltages exceeding 2600 and 2.5 V, respectively. To improve power

absorption, Li et al.[529 ] focused on the study of highly eﬃcient

PTOs. This work proposes a compact PTO utilizing a ball screw

mechanism and a mechanical motion rectiﬁer to improve the en-

ergy conversion rate. Bench test results show that the proposed

compact PTO has better freewheeling motion than the tradi-

tional PTO, and the highest energy conversion eﬃciency reaches

81.2%. Also, Ahmed et al.[509 ] optimized the oscillating ﬂoating

body to improve the performance of the wave energy converter

(Figure 13h). The researchers’ simulations and theoretical deriva-

tions indicate that the buoy with the most expansive bulbous bot-

tom of 1.6 m height has the highest power and eﬃciency. Com-

pared with the non-spherical cylindrical hemispherical buoy, the

response amplitude operator and power absorption of the pro-

posed innovative spherical buoy increase by up to 16.8% and

21.5%.

The development of underwater equipment for ocean explo-

ration has received widespread attention. Autonomous underwa-

ter vehicles, underwater robots, and other underwater equipment

play a huge role in ocean exploration, submarine search and res-

cue, and marine environment monitoring.[530 ] These devices are

usually equipped with a large number of sensors to perform spe-

ciﬁc tasks. However, the power supply problem of sensors and

insuﬃcient perception ability have been a huge problem. Un-

derwater equipment with dual capabilities of self-powering and

self-sensing can be of great use in this ﬁeld.[503 ] Li et al.[510 ] de-

veloped an extended-range wave-powered autonomous underwa-

ter vehicle for building an underwater wireless sensor network

(Figure 13i). Under the excitations of diﬀerent amplitudes and

frequencies, the maximum mechanical eﬃciency of the proposed

underwater vehicle is 81.56%. In ﬁeld experiments, the maxi-

mum power of this design is 67.74 W, which has the potential

to power underwater wireless sensor networks. Autonomous un-

derwater vehicles have many advanced capabilities but still lack

the tactile perception comparable to marine animals. In deep-

sea environments, tactile perception plays a huge role in situ-

ations where visual detection is diﬃcult. Therefore, smart and

precise tactile sensors are crucial for accurate ocean exploration

missions.[531 ] Inspired by the whisker structure of marine ani-

mals, Liu et al.[511 ] proposed a bionic whisker sensor based on

TENG to assist underwater robots to perceive the environment,

as shown in Figure 13j. The sensor consists of a carbon ﬁber rod,

an epoxy resin matrix, and four TENG sensing units. When the

carbon ﬁber rod on the sensor comes into contact with the outside

world, it will drive the octagonal prism to impact TENG sensing

unit, thereby converting the mechanical excitation into an elec-

trical signal. By analyzing the generated electrical signal, the di-

rection, displacement, and frequency of the external load can be

judged. In the underwater environment experiment, the under-

water robot equipped with the tactile sensor can detect the under-

water environment and actively avoid obstacles, demonstrating

the potential of underwater environment perception.

Ocean Current refers to the regular horizontal ﬂow of seawa-

ter along a certain direction with a relatively stable speed, which

is a non-periodic movement.[532 ] Ocean currents are divided into

surface ocean currents and deep currents according to underwa-

ter depth. The former is usually aﬀected by factors such as wind

force and earth rotation, while the latter is usually aﬀected by fac-

tors such as seawater density diﬀerences and gravity. Ocean cur-

rent energy is a renewable energy source with great potential for

development. Ocean current energy collectors do not occupy the

water’s surface area when working underwater.[ 533] A turbine, a

device that harnesses the energy of ocean currents to generate

electricity, has made good progress.[534] Li et al.[ 512] proposed a

compact electromagnetic transducer for harvesting energy from

ocean currents to power underwater robots (Figure 13k). The de-

vice uses turbines to convert ocean currents into rotational mo-

tion, which is ampliﬁed by a gear train. The electromagnetic gen-

erator module adopts an alternating magnet arrangement to in-

crease the magnetic ﬂux density to increase the power output.

Under the water ﬂow speed of 0.64 m s−1, the maximum aver-

age output power of the transducer is ≈0.51 W, and the energy

conversion eﬃciency is 30.91%. Furthermore, the transducer can

charge the lithium battery embedded in the underwater robot to

75% within 75 s, demonstrating its capability for self-powered

applications. Flow-induced vibration harvesters are also suitable

for harvesting ocean current energy. Inspired by the waving ﬂag,

Wang et al.[513] proposed an underwater ﬂag-shaped TENG to har-

vest ocean current energy, as shown in Figure 13l. The generator

has good water resistance, a low starting speed, and a wide work-

ing range. By adjusting its bending stiﬀness, the critical start-up

speed of this generator is as low as 0.133 m s−1, showing a signiﬁ-

cant advantage in low-speed ocean current collection. Circulating

tank experiments show that the peak output power of the six gen-

erator units is 52.3 μW when the water ﬂow velocity is 0.461 m

s−1. This work provides a simpler and more cost-eﬀective ap-

proach for underwater self-powered applications in low-velocity

ocean currents.

5.8. Self-Powered Microelectronics in Smart Home

In the era of 5G and the IoT, smart homes are developing rapidly

as the core of smart cities, as shown in Figure 14. In order

to achieve smart homes, various smart devices (mainly divided

into energy collectors and environmental monitoring devices)

have been extensively developed. There are various renewable en-

ergy sources available around the house, such as solar energy,

wind energy, rainwater energy, magnetic ﬁeld energy, and me-

chanical energy, which can be used to build a sustainable home

system.[535 ] In addition, various sensors and self-sensing sys-

tems are applied to household equipment such as doors, ﬂoors,

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Figure 14. Self-powered microelectronic devices for smart home. a) A hybrid generator with solar cells and TENG installed on the roof of the house.

switches, windows, beds, and toilets, to achieve diversiﬁed func-

tions such as home automation, environmental monitoring, and

health management.[536 ] In order to promote the development of

smart home systems, AI has been introduced into the home sys-

tem, realizing advanced functions such as personalized monitor-

ing, identity recognition, and human-computer interaction.[537 ]

The household appliances and various sensors in the house

consume a large amount of electricity. The development of en-

ergy harvesters provides a low-cost and energy-saving solution

to the power supply of these electronic devices.[538 ] In the home

environment, solar energy and wind energy are the main renew-

able energy sources, which are abundant and easy to obtain.[539 ]

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Zhang et al.[540 ] developed a ﬂexible ribbon array TENG installed

on the roof for collecting natural wind from any direction, propos-

ing an innovative solution for self-powered home applications.

In order to achieve simultaneous collection of wind and solar en-

ergy, Wang et al.[541 ] proposed a hybrid generator with solar cells

and TENG, installed on the roof of the house (Figure 14a). Un-

der the same device area, the maximum output power of solar

cells is ≈8 mW, while TENG can reach up to 26 mW. When the

impedance of the two power generation units is matched, the hy-

brid generator can achieve the optimal output performance. In

addition, raindrops also have great value in energy harvesting for

smart home applications. As shown in Figure 14b, Li et al.[542]

developed a generator array installed on the roof for large-scale

collection of raindrop energy. The power density of the droplet-

based electricity generator reached 765 W m−2, which could light

up 100 LEDs simultaneously. In addition to raindrop energy, tap

water can also be used for self-powering applications. Zhong

et al.[543 ] designed an electromagnetic-triboelectric hybrid nano-

generator for ﬂuid energy harvesting and self-powered ﬂow rate

monitoring, which will promote the application of smart homes.

Compared to clean energy such as solar and wind power, mag-

netic energy has received less attention.[544 ] Maharjan et al.[545 ]

designed a magnetic ﬁeld energy harvester that harvests time-

varying magnetic ﬁelds around indoor wires (Figure 14c). The

energy harvested by the magnetic ﬁeld energy harvester is sup-

plied to the wireless sensor network through an energy man-

agement circuit, and this process has been successfully demon-

strated through experiments. In addition, a high-performance

magneto-mechano-triboelectric nanogenerator has been devel-

oped, which can achieve a maximum peak power of 21.8 mW.[546 ]

Based on this generator, a self-powered indoor IoT position-

ing system has been developed and successfully operated. In-

home environments, the harvesting of mechanical energy is

also a hot spot of people’s attention.[547] Graham et al.[ 548] de-

veloped a TENG for smart homes, which has the functions of

mechanical energy harvesting and storage, as well as motion

sensing.

The implementation of smart homes cannot be achieved with-

out various types of smart electronics. The access control system

is the ﬁrst line of defense for home security.[554] Liu et al.[ 555] de-

veloped a triboelectric sensor based on a ferroﬂuid-liquid-solid

interface for the design of security home locks. This combination

lock provides users with a high level of protection by detecting the

pressure level of the keys. Qiu et al.[115 ] designed a self-powered

control panel based on TENG, which can generate a 3-digit bi-

nary code, as shown in Figure 14d. An intelligent home access

control system is developed based on the control panel, which

is powered by a hybrid energy harvester (TENG and solar cells).

Furthermore, to improve the sensitivity and reliability of sensing,

Xie et al.[556 ] a natural wood triboelectric sensor with high sensi-

tivity for smart home systems. To protect personal privacy and se-

curity, a self-powered intelligent door lock system has been built

for identity recognition and home security.

Smart ﬂoor is one of the most frequently interacted interfaces,

which can obtain rich sensory information from human walk-

ing to realize functions such as automatic control, activity mon-

itoring, identiﬁcation, and human-machine interaction.[557 ] Hao

et al.[558 ] proposed a self-powered ﬂoor based on natural wood

TENG. When the experimenter steps on the ﬂoor, the TENG acts

as a power source to power the LEDs and also acts as a sen-

sor to track the experimenter’s movement. In order to make the

smart ﬂoor have more advanced and diversiﬁed functions, deep

learning can be integrated into the ﬂoor monitoring system.[559]

As shown in Figure 14e, Shi et al.[549] developed an Artiﬁcial

intelligence of things (AIoT) enabled ﬂoor monitoring system,

which integrates triboelectric encoding pads and deep learning

to achieve advanced sensing functions, including location aware-

ness and identiﬁcation. The triboelectric pad employs two en-

coded electrodes, enabling 16 unique quaternary encoding con-

ﬁgurations. Based on a 4×4 ﬂoor mat array, the system can realize

position sensing and trajectory tracking. In addition, by introduc-

ing 1D-CNN model, the identity recognition accuracy of the intel-

ligent ﬂoor monitoring system for 20 users has reached 85.67%.

Furthermore, a virtual reality (VR) scene with dual functions of

location tracking and identity recognition was constructed, which

proves the enormous potential of this intelligent ﬂoor system in

smart home applications.

Smart switches are developed to replace traditional switches

to achieve convenient and automatic control of home system

equipment.[560 ] Voltage threshold comparison is a commonly

used signal processing method, which can be used to realize

the control of household equipment by smart switches. Shrestha

et al.[561 ] designed a TENG-based self-charging supercapacitor

power cell, and built a smart switch for home appliance control.

When the voltage of the supercapacitor power cell reaches the

threshold voltage, the microcontroller sends a signal to control

the household appliances. In addition, Li et al.[562 ] designed a tri-

boelectric sensing ﬁber, which also utilizes the method of volt-

age threshold comparison for smart home applications. When

the peak voltage generated by the hand touching the triboelectric

sensing ﬁber is greater than a threshold, the corresponding elec-

trical appliance is turned on. To improve the sensing sensitivity

and pressure response range, Zhang et al.[550 ] developed a hybrid

sensor through the combination of piezoresistive and triboelec-

tric layers (Figure 14f). The sensor has an excellent self-powered

ability, so the author built a self-powered smart home system,

that can realize functions such as fall detection, home appliance

control, and access control management.

Self-powered smart windows are another research hotspot in

smart life.[563 ] Ye et al.[ 564] develop a self-powered smart win-

dow that integrates an electrochromic device with a transpar-

ent TENG. The smart window can achieve a light transmittance

change of up to 32.4%, which will promote the development of

energy-eﬃcient buildings. Electrochromic windows usually suf-

fer from long switching times and light leakage, whereas liq-

uid crystal rotations have the advantage of fast response. There-

fore,Wangetal.

[551 ] developed a smart window integrating

TENG and polymer network liquid crystal (PNLC), as shown in

Figure 14g. PNLC is usually transparent and becomes opaque

after tribocharging. The maximum change rates of light trans-

mittance and haze ratio of the proposed smart window are 91%

and 78%, respectively, providing new solutions for radiation con-

trol and privacy protection. Zheng et al.[565 ] designed a TENG-

driven polymer dispersed liquid crystal (PDLC) ﬁlm for smart

window applications. Under the action of TENG, PDLC ﬁlms

can be transformed from opaque to transparent, which can be

used for radiation control, heat insulation, and personal privacy

protection.

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Sleep is a natural and recurring physiological state, and the

quality of sleep plays a vital role in human health. Smart bedding

(pillows,[566 ] sheets,[567 ] etc.) is being developed extensively to en-

able sleep monitoring, early disease diagnosis, and fall warning.

AsshowninFigure14h,Lietal.

[552 ] developed a smart bed sheet

based on a TENG array for real-time and self-powered sleep mon-

itoring. The smart bed sheet is composed of 9 ×11 TENG array

units, and a single TENG unit is made of conductive ﬁbers and

elastic materials with a wave structure. The developed smart bed

sheet has pressure sensing and detection capabilities, and a sleep

monitoring system and early warning system are built based on

the smart bed sheet. In addition, the sheets are washable and suit-

able for mass production, representing a great advance in clinical

medicine for sleep monitoring. Kou et al.[568 ] designed a smart

pillow based on a ﬂexible and breathable TENG array to moni-

tor the user’s head motion. A pressure sensor array integrating

TENG and a ﬂexible printed circuit can realize touch sensing and

motion trajectory monitoring. Additionally, a self-powered drop

alarm is demonstrated, opening up a novel solution for clinical

care.

Among other aspects of smart homes, the development of

tables and toilets has also attracted attention. He et al.[569 ] devel-

oped a desktop interactive system based on a triboelectric vibra-

tion sensor for the control of diﬀerent applications. The desk-

top is divided into several control areas, and the control of diﬀer-

ent household appliances can be realized through the processing

and identiﬁcation of triboelectric signals. Smart toilets provide

another viable platform for human health monitoring. Zhang

et al.[553 ] proposed an AI toilet based on a triboelectric pressure

sensor array, which provides a low-cost and simple method for

user health monitoring and privacy security (Figure 14i). Ten tri-

boelectric pressure sensors are integrated into the smart toilet

cover to accurately capture user characteristic information. In ad-

dition, based on deep learning analysis, the accuracy rate of iden-

tiﬁcation of 6 users reached 97.14%, showing excellent privacy

protection capabilities. The smart toilet also integrates a camera

sensor and analyzes the user’s urine and feces based on deep

learning, which provides valuable information for health moni-

toring.

5.9. Self-Powered Microelectronics in Smart Agriculture

In recent years, smart agriculture based on IoTs technology has

developed very rapidly. Smart agriculture combines traditional

agriculture with IoT technology to achieve real-time monitoring

of farm environment and plant growth status[570 ]. Smart agri-

culture uses a large number of agricultural environment and

plant protection monitoring sensors to obtain the temperature,

humidity, light intensity, soil moisture, and plant growth status

information in the farm, so as to achieve intelligent manage-

ment of the farm and improve agricultural production eﬃciency.

A large number of self-powered monitoring devices have been

developed for smart agriculture, which can be mainly classiﬁed

into: energy harvesting-based agricultural environment moni-

toring sensors,[116 ] and energy harvesting-based plant wearable

devices,[571 ] as shown in Figure 15.

There are abundant environmental energy sources (wind,

solar, and hydro) in the farm environment, which can

serve as power sources for farm environmental sensors and

electronics.[572 ] Among all kinds of mechanical energy, natural

wind energy has the advantages of abundance, wide distribution,

sustainability, and easy access, which is a satisfactory energy

source for agricultural environmental sensors.[573 ] Men et al.[574 ]

proposed a Cotton-assisted TENG to collect environmental

wind energy to promote the development of self-powered en-

vironmental monitoring for smart agriculture. Cotton is used

as the friction-positive layer, which eﬀectively improves power

generation eﬃciency and durability. In addition, Han et al.[575 ]

developed a TENG based on rabbit fur soft contact to harvest

wind energy for smart agriculture, as shown in Figure 15a. The

soft rabbit fur has good triboelectriﬁcation performance and

can prolong the service life of the generator. The researchers

successfully demonstrated the application of the designed

TENG in mosquito trapping and soil temperature and humid-

ity monitoring, pointing out the way for the development of

smart agriculture. The information collected by agricultural

sensors needs to be transmitted to end users, and then the

transmission distance is too short to meet the needs of the

farm environment. Gu et al.[576] proposed a long-distance self-

powered multi-channel wireless agricultural sensing system

based on TENG of corn husk composite ﬁlm. The system can

simultaneously collect four diﬀerent types of information, in-

cluding ambient temperature and humidity, sunlight intensity,

and soil moisture, with a maximum transmission distance

of 1.7 kilometers, which fully meets the needs of the farm.

TENG has high voltage and high energy conversion eﬃciency,

and EMG has the characteristics of a large current and stable

output. Combining the two can improve the performance of

self-powered equipment.[577 ] As shown in Figure 15b, Zhang

et al.[578 ] proposed a self-powered sensing system for smart

agriculture based on an electromagnetic-triboelectric hybrid

generator. EMG collects wind energy and accurately detects wind

speed, and three-layer TENG acts as a wind direction sensor

to detect wind directions in 8 directions. The developed smart

agricultural self-powered sensor system integrates the functions

of wireless transmission and multi-information (wind speed,

wind direction, ambient temperature, and humidity) sensing,

with great application potential.

In a farm environment, solar energy is one of the most

widely distributed clean energy sources, and it has a high en-

ergy density.[586] In recent years, photovoltaic agriculture, which

combines large-scale photovoltaic power generation and agricul-

tural activities, has been developed rapidly.[587] In addition, small

photovoltaic self-powered devices are also being developed for

smart agriculture. Since solar energy collection is closely related

to weather conditions, it is less eﬃcient at night or on cloudy

days. Therefore, researchers want to combine photovoltaic cells

and other energy-harvesting devices to enhance environmen-

tal adaptability and improve power generation eﬃciency. Roh

et al.[579 ] proposed a hybrid energy harvesting module to con-

vert the energy of wind, sunlight, and rain into electricity for

a variety of weather conditions (Figure 15c). The hybrid energy

harvesting module consists of wind TENG, rain TENG, and so-

lar cells, which can detect wind, raindrops, and sunshine condi-

tions to create a good growth environment for plants. Addition-

ally, Wang et al.[588] developed a hybrid energy harvesting device

that harvests wind and solar energy to drive smart agricultural

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Figure 15. Self-powered microelectronic devices for smart agriculture. a) TENG based on rabbit fur soft contact for smart agriculture. Reproduced with

applications. Based on the hybrid energy harvesting device, the

researchers developed a self-powered wireless multi-point tem-

perature and humidity monitoring system and a wireless passive

infrared monitoring system, which provide a guarantee for the

health and safety of smart agriculture. As shown in Figure 15d,

Ye et al.[ 580] developed a highly transparent raindrop TENG array

panel with integrated solar panels to synergistically harvest solar

energy and raindrop energy. Comparative experiments show that

the average power density of the raindrop TENG array panel is

40.80 mW∙m−2when the droplet frequency is 50 mL per minute,

which is higher than the power density of 37.03 mW when the

solar cell is at 500 Lux. In addition, the researchers developed a

self-powered wireless light intensity monitoring system based on

an integrated system for all-weather real-time monitoring of envi-

ronmental sunlight intensity, which will pave the way for the de-

velopment of smart agriculture and meteorological monitoring.

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In a farmland environment, water ﬂow energy in irrigation

canals or rivers is another large-scale renewable energy source

that can be used for self-powered applications.[589 ] However,

water ﬂow energy has low speed and irregular characteristics,

which brings great challenges to eﬃciently recover this part of

energy.[87] Therefore, Ye et al.[581 ] developed a high-performance

TENG based on agricultural waste, which realized the energy har-

vesting of low-frequency and low-speed water ﬂow in agricultural

environments (Figure 15e). Plant ﬁbers from agricultural wastes

exhibited excellent performance (lower wear and better durabil-

ity), and the power density of TENG based on plant ﬁber brushes

and PVC ﬁlm nanomodiﬁcation was increased by ≈64 times. In

addition, this TENG successfully powers wireless plant sensors

and develops automatic irrigation systems to help realize the in-

telligentization and informatization of agriculture. Inspired by

the eddy current eﬀect of ﬁsh ﬁns, Zhang et al.[590 ] developed a

soft-bionic-ﬁn structure triboelectric-electromagnetic generator.

Speciﬁcally, the vortex eﬀect-driven soft body swings to make the

TENG oscillate, and drives the EMG through the swing-rotation

mechanism to realize water ﬂow energy harvesting. The TENG

and EMG attain an output voltage of 203 and 7.7 V, respectively,

underﬂow velocities of 0.96 m s−1. Rainfall is a very common phe-

nomenon in agricultural environments. Especially in areas with

high annual rainfall, raindrop energy may be the preferred en-

ergy source for self-powered devices.[591 ] However, raindrop en-

ergy has the characteristics of wide distribution, low frequency,

and insuﬃcient driving force, so it is necessary to design eﬃ-

cient energy harvesters. As shown in Figure 15f, Zhang et al.[582 ]

developed a self-powered smart greenhouse based on TENG that

harvests raindrop energy. A ﬂuorinated superhydrophobic green-

house ﬁlm is used as negative triboelectric layer material, and the

TENG structure is integrated into the greenhouse to harvest rain-

drop energy on a large scale. Based on the proposed TENG, a self-

powered temperature and humidity monitoring system is con-

structed for greenhouses, which is of great signiﬁcance to guide

agricultural production.

In the agricultural environment, plants and crops are the core

components, and all sensing and monitoring are for the healthy

growth of plants. It is important to pay attention to the growth

conditions and health of individual plants for more intelligent

and high-quality agricultural production.[592 ] Wearable devices

have long been studied and applied in humans and animals. At

present, the concept of wearable devices has been extended to

plants, such as humidity sensors, temperature sensors, and light

intensity sensors, to monitor the health status of individual plants

in real-time.[593 ] As shown in Figure 15g, Nassar et al.[583] uti-

lized ﬂexible and biocompatible materials to develop a low-power

and lightweight plant wearable device. The proposed plant wear-

able device integrates temperature, humidity, and strain sensors,

which can be closely attached to the leaves of plants to remotely

and continuously monitor local humidity and temperature lev-

els as well as quantitatively monitor plant growth. Furthermore,

Zhao et al.[594 ] proposed a multifunctional stretchable leaf sensor

with sensing functions such as temperature, hydration, illumi-

nance, and strain. The sensor ﬁts the blade perfectly, applying

only a contact pressure of no more than 170 μN to the blade. The

signal transmission distance of the wireless sensing platform de-

veloped based on this sensor exceeds 100 meters, demonstrat-

ing the potential of developing large-scale plant wearable sensing

networks. Besides, as shown in Figure 15h, Li et al.[584] demon-

strated epidermal plant sensors for gas sensing. A graphite sen-

sor array based on a single-walled carbon nanotube was trans-

ferred and laminated directly on the surface of a leaf for the detec-

tion of dimethyl methyl phosphonate vapor. A single plant sensor

is very capable of monitoring plant growth conditions, but most

of the plant sensors developed are active sensors. Based on self-

powered technology, developing self-sustainable sensing systems

is an inevitable trend in smart agriculture.[595 ] Hsu et al.[596 ] devel-

oped a plant-wearable hydrogel-based smart agricultural system

to monitor plant growth status and promote plant growth. The

multifunctional hydrogel consists of sensors to monitor plant

growth rate and environment, TENG to harvest acoustic energy,

rainfall, and wind energy, and capacitors for energy storage. The

stored energy continuously powers the LEDs that promote plant

growth. In addition, Lan et al.[597 ] developed a self-powered sus-

tainable agricultural system based on plant-wearable waterproof

and breathable TENG. With carbon nanotubes as electrodes, the

TENG exhibits a high output power density of 330.6 μW∙cm−2,

high electrostatic adhesion, gas permeability, and hydrophobic-

ity. In addition, a sustainable agricultural system based on the

proposed TENG is constructed to monitor the plant growth and

send the growth information to the mobile phone via Bluetooth.

As shown in Figure 15i, Luo et al.[585] developed a living plant leaf-

based TENG for self-powered smart agricultural sensing. With a

maximum average power density of 90.67 mW∙m−2, the TENG

can be used as a self-powered humidity sensor (with a sensitiv-

ity of 3.0 V/% RH). In addition, TENG has demonstrated high

wind speed warning capabilities in greenhouses, which has con-

tributed to the construction of smart agriculture.

5.10. Self-Powered Microelectronics in Smart Industry

The era of Industry 4.0 (the fourth industrial revolution) repre-

sents a new era of digital, networked, and intelligent production.

It covers advanced technologies such as IoTs, AI, big data, cloud

computing, and machine learning, aiming to improve produc-

tion eﬃciency, reduce costs, and optimize production processes.

In the smart industry, self-powered sensing devices play an im-

portant role, which is concentrated in the ﬁelds of energy re-

covery, intelligent manipulators, bearing monitoring, wire mon-

itoring, machine safety status monitoring, and the self-powered

electrochemical industry. These self-powered devices will help in-

crease production eﬃciency, reduce costs, and improve product

quality and ﬂexibility while reducing dependence on humans.

This section mainly reviews several prominent applications of

self-powered micropower devices in the smart industry, as shown

in Figure 16.

With the development of modern industry, the industrial pro-

duction process consumes more and more energy.[612] In the

past, industrial waste heat could not be directly utilized and

would eventually be discharged into the environment, resulting

in energy waste and environmental pollution. In recent years,

waste heat power generation technology has gradually emerged

as an eﬀective method for recycling industrial waste heat.[613 ]

Yun e t a l.[ 598] proposed a hybrid energy harvesting system for

harvesting industrial waste heat, as shown in Figure 16a. The

system converts industrial heat energy into mechanical energy

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Figure 16. Self-driven micropower devices for smart industry. a) A hybrid energy harvesting system for harvesting industrial waste heat. Reproduced with

enhanced soft manipulator based on an embedded multifunctional perception system for robotic industrial automation. Reproduced under the terms

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through a Stirling engine, and its working process is realized

based on the Stirling cycle (heat, expansion, cool, contraction).

The hybrid electromagnetic-triboelectric generator module con-

verts mechanical energy into electrical energy, which can achieve

an electrical energy output of 23.65 μJ. The proposed Stirling

engine-based energy recovery system will play a huge role in in-

dustrial heat recovery applications. In addition to industrial waste

heat recovery, wind energy has attracted much attention in in-

dustrial self-powered applications. Zhang et al.[599 ] proposed a

turbine TENG, which is installed at the roof vent to collect ir-

regular wind energy (Figure 16b). The generator can generate a

voltage of 178.2 V at a wind speed of ≈y7ms

−1and success-

fully lights up 120 LEDs. Using the proposed turbine genera-

tor, a self-powered industrial monitoring system with tempera-

ture sensing and wireless early warning is developed, which pro-

vides a new approach for industrial safety monitoring. Mechan-

ical energy, including vibrational and rotational energy, is ubiq-

uitous in modern factories. Speciﬁcally, in logistics transporta-

tion, the rotation of the roller can be used for energy recovery.

Ra et al.[600 ] proposed a self-powered smart conveyor roller sys-

tem based on a triboelectric-electromagnetic hybrid generator

(Figure 16c). The system consists of TENG, a microprogrammed

control unit (MCU), and EMG. The TENG senses transported

products, including information such as material, size, weight,

and moving speed. The MCU collects triboelectric signals and

transmits them wirelessly to the terminal. The EMG collects the

rotational energy of the roller to provide enough power for the

MCU. The proposed self-powered intelligent conveyor roller sys-

tem is a near-zero energy system integrating sensing, analysis,

and transmission, which is expected to become the cornerstone

of the intelligent logistics industry.

Robots and robotic arms are important components of modern

industrial systems, which are of great signiﬁcance in improving

production eﬃciency, intelligence level, and product reliability.

Recently, many studies have focused on developing self-powered

sensors for robots, especially self-powered robotic systems in-

tegrating AIoT.[614,615 ] Self-powered sensors provide an energy-

eﬃcient, simple, and reliable strategy for robots to sense the ex-

ternal environment.[616 ] In particular, angle sensing plays an im-

portant role in robotics and machine control. Therefore, Wang

et al.[601 ] proposed a high-sensitivity triboelectric self-powered an-

gle sensor suitable for manipulators, as shown in Figure 16d. The

working principle of the angle sensor is due to the diﬀerence in

electrode overlap between two TENG modules, thereby generat-

ing an angle-sensing signal. Three angle sensors are integrated

into the palletizing robot arm, and the robot arm accurately writes

the word “Nano”, demonstrating its high-precision angle sensing

capability. In recent years, research on soft robots (soft manipu-

lators) based on ﬂexible sensors has attracted great interest.[617 ]

Soft robots have the advantages of high sensitivity, strong com-

pliance, lightness, and more freedom, and can eﬃciently com-

plete safe and smart grasping tasks.[618 ] Xie et al.[619 ] proposed a

soft manipulator based on a self-powered multifunctional sensor

that can precisely sense ﬁnger curvature and stiﬀness. The maxi-

mum sensitivity of the soft manipulator to curvature and stiﬀness

is 0.55 mV m−1and 0.09 mV N−1, respectively. The sensor suc-

cessfully sensed and recorded the ﬁnger curvature and stiﬀness

information of the manipulator during the process of picking up

and placing objects. In order to realize the interaction between

manipulators and humans, more advanced and intelligent sen-

sors are needed. Therefore, Jin et al.[602 ] proposed a soft gripper

based on triboelectric tactile sensors and length triboelectric sen-

sors for AIoT-based digital twin applications (Figure 16e). Tribo-

electric tactile sensors can detect sliding, contact position, and

contact area of external stimuli, and length triboelectric sensors

are used to detect bending motions. With the help of deep learn-

ing, the smart soft gripper integrated with multi-functional sen-

sors can perceive various objects with an accuracy rate of 97.1%.

The digital twin unmanned warehouse system based on the soft

grip was successfully demonstrated, which laid the foundation

for the unmanned development of smart factories. Furthermore,

Sun et al.[ 603] developed an enhanced soft manipulator based on

an embedded multifunctional perception system for robotic in-

dustrial automation, as shown in Figure 16f. The developed sens-

ing system consists of tactile TENG, length TENG, and PVDF py-

roelectric temperature sensor. Based on deep learning analysis,

the fusion of tactile TENG and length TENG achieved an accu-

racy rate of 97.143% for 28 objects. Pyroelectric sensors are used

to sense the temperature distribution of objects. This work pro-

vides a low-cost, simple, and highly compatible self-powered in-

teractive system for smart industrial automation applications.

A bearing is a mechanical element used to reduce friction

and support rotational motion and is an indispensable core ele-

ment of a modern factory. Converting the rotational energy of the

bearing into electrical energy can achieve self-monitoring of the

bearing.[620 ] Zhang et al.[604 ] developed an EMG based on a circu-

lar Halbach magnet array to collect the rotational kinetic energy

of the bearing to provide electrical energy to the monitoring unit

(Figure 16g). When the bearing speed is 1000 rpm, the EMG can

generate 4.59 V voltage and 131.1 mW maximum average output

power. Due to the special structure of the bearing to support ro-

tational motion, smart bearings are mostly developed as rotation

and speed sensors.[621 ] As shown in Figure 16h, Han et al.[605]

proposed a triboelectric rolling ball bearing with dual functions

of self-power and self-sensing. The rolling contact between the

glass ball and the copper electrode on the outer ring generates

a triboelectric signal. The self-induction bearing uses RMS volt-

age and current frequency as the evaluation index of the speed

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sensor, and it also has the ability to self-induction of two ab-

normal states. This work demonstrates a multifunctional smart

bearing with great potential in modern smart factories. The run-

ning status of rolling bearings directly aﬀects the working per-

formance of mechanical equipment, so the monitoring of bear-

ing running status is an important goal.[622 ] In order to realize

self-powered fault diagnosis of rolling bearings, a self-powered

rolling bearing is proposed.[623 ] Relying on deep learning data

analysis, the self-powered rolling bearing has an accuracy rate

of more than 92% for the identiﬁcation of four bearing motion

states (healthy state and three fault states). Slipping is one of

the common failure modes of bearings, which seriously aﬀects

the healthy operation of mechanical equipment. Therefore, Xie

et al.[606 ] developed a non-contact bearing sensor for monitoring

the speed and slip rate of the bearing, as shown in Figure 16i.

It has been veriﬁed by experiments that the bearing sensor has

an ultra-long service life and an ultra-wide working speed range

of 10–5000 rpm. The sensor can monitor bearing speed at low

speeds and bearing slippage at high speeds and light loads. This

work provides a reference for bearing health monitoring and will

contribute to the progress of the smart industry.

Transmission lines are important carriers of power transmis-

sion, located in the arteries and veins of the power system. With

the development of smart grids, the demand for power line mon-

itoring is constantly increasing. The power supply of monitor-

ing equipment has always been a major issue, and the appli-

cation of self-powered technology has eﬀectively alleviated this

diﬃcult situation. Wind-induced vibration energy,[624 ] magnetic

energy,[625] andwindenergy

[626 ] can all be used as energy sources

for self-powered wire monitoring equipment. For vibration en-

ergy harvesting, Tang et al.[ 607] developed an electromagnetic en-

ergy harvester that collects omnidirectional vibrations of wires,

as shown in Figure 16j. Utilizes ﬂexible rope, one-way bearings,

and coil springs to convert the wireless omnidirectional vibration

of the wire into the unidirectional rotation of a three-phase DC

motor. The maximum output voltage and output power of this

omnidirectional energy harvester are 10 V and 41.6 mW, respec-

tively, which are enough to power the monitoring equipment for

more than 1440 s. Wind-induced vibration is an eﬀective energy

source for self-powered equipment, but it also increases the risk

of line breaks, aﬀecting the safety of the power system.[627 ] There-

fore, Hu et al.[628] developed a vibration-driven TENG (V-TENG)

for vibration suppression and condition monitoring of transmis-

sion lines. This work successfully demonstrated a V-TENG-based

wireless self-powered tilt alarm system and temperature and hu-

midity data transmission system. Through simulation experi-

ments, it is proved that V-TENG can reduce the vibration am-

plitude of 13 cm wire to ≈5 cm under the excitation of 8 Hz res-

onance frequency, which also means that V-TENG can eﬀectively

suppress the vibration of wires. There is an abundant and persis-

tent stray magnetic ﬁeld around power lines, which is a useful

energy source for self-powered monitoring equipment.[629 ] Yuan

et al.[173 ] proposed a hybrid magnetic energy harvester, which re-

alized the eﬀective conversion of magnetic energy-mechanical

energy-electrical energy (Figure 16k). The magnet is aﬀected by

the alternating magnetic ﬁeld to cause the ﬂexible pendulum to

swing, thereby driving the hybrid mechanical energy collection

module to work. The TENG and EMG modules were connected

in parallel to charge a 4 μF capacitor to 78.55 V within 100 s. In ad-

dition, a self-powered wireless temperature alarm system based

on a hybrid magnetic energy harvester was developed to mon-

itor ﬁre hazards caused by overheating. Overhead power lines

are located in a wind-rich environment for a long time, so it is

necessary to monitor the wind conditions. Tang et al.[608 ] pro-

posed a self-powered wind sensor based on TENG to monitor the

breeze vibration of wires, as shown in Figure 16l. The sensor can

monitor 1.7–6.7 m s−1wind speed and direction. Furthermore, to

demonstrate the feasibility of self-powered wind sensors, a wind

monitoring system for transmission lines is designed, providing

a new strategy for smart grid wind monitoring.

In mechanical equipment, sensors are indispensable tools for

monitoring the operating status of equipment. Various indus-

trial sensors are used to detect, measure, and monitor changes

in physical and chemical quantities in industrial processes, and

transmit the acquired data to the control system for analysis and

processing.[630 ] With the help of self-power and self-sensing tech-

nology, the developed industrial sensors mainly include vibra-

tion sensors,[155 ] speed sensors,[631 ] mechanical wear monitor-

ing sensors,[632 ] and impact monitoring sensors.[633 ] Mechani-

cal equipment will generate vibration during operation, which

usually aﬀects the safety and stability of the equipment. There-

fore, vibration monitoring of mechanical equipment is very

necessary.[634] Lin et al.[ 635] proposed a self-powered vibration

sensing system in which EMG harvests vibration energy and

TENG is used for vibration sensing. The electric current of the

TENG is used to sense vibration acceleration changes with a

maximum vibration sensing resolution of 23.4 nA·m−1·s2.In

addition, as shown in Figure 16m, Lin et al.[609] developed a

self-powered autonomous vibration wake-up system. The sys-

tem’s TENG acts as an accelerometer with a sensitivity of 14.6

V/ ( m s −2). Via MEMS switches, the system monitors acceleration

thresholds to signal an alarm, oﬀering a solution for self-powered

vibration monitoring in modern factories. Among all kinds of

mechanical motion, rotary motion is one of the most basic forms

of mechanical equipment motion, and it is a research hotspot in

the ﬁeld of self-powered sensing.[636 ] Zhang et al.[610] proposed a

triboelectric rotational motion sensor to monitor the speed and

angle of rotational motion, as shown in Figure 16n. The experi-

mental results show that the sensor can realize the speed mea-

surement between 10–1000 rpm, and the error rate is less than

0.8%. In addition, the sensor can achieve 360°bidirectional angle

measurement with a resolution of 1.5°. This work demonstrates

an industrial-grade speed and angle sensor that will greatly ad-

vance the development of smart factories. Mechanical equipment

will inevitably wear out under long-term high-intensity opera-

tion. Wear can reduce equipment performance, reduce equip-

ment life, and increase safety hazards. Therefore, the monitoring

of mechanical wear is very important. Kim et al.[611] proposed a

self-powered mechanical wear monitoring system for brake pads,

as shown in Figure 16o. The proposed system inserts a geomet-

ric gradient layer into the brake pads, and the magnitude of the

generated electrical signal can reﬂect the degree of wear of the

brake pads. Therefore, this system is a self-sustaining wear mon-

itoring system that can eﬀectively diagnose the wear condition of

machinery.

The self-powered electrochemical industry is a major branch

of smart industry and plays an important role in energy, materi-

als, life sciences, and other ﬁelds. Self-powered electrochemistry

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has a wide range of applications, including the electrolysis indus-

try, wastewater treatment, metal anti-corrosion, etc. Self-powered

electrolysis uses electric current to pass through an electrolyte

solution to separate bonded elements and compounds.[637 ] Self-

powered water electrolysis is one method of producing hydro-

gen, which uses self-powered generators such as TENGs to split

water into oxygen and hydrogen. This method often uses TENG

to collect wave energy and apply it to seawater desalination.[638 ]

Feng et al.[639] proposed a self-driven electrochemical system that

harvests wave energy for hydrogen production from seawater

decomposition. Under ideal conditions, the hydrogen produc-

tion rate of this system is 814.8 μL·m−2·d−1, providing a poten-

tial solution to environmental problems. Wastewater treatment

is an important link in industrial production, especially in the

paper industry.[640] Wastewater is rich in chemical substances

such as heavy metal ions and organic pollutants, and it also

has huge mechanical energy.[641] Self-powered electrochemical

wastewater treatment is one of the eﬀective methods of indus-

trial wastewater treatment. The treatment includes the removal

and recovery of heavy metals, explanation of organic pollutants,

sterilization and disinfection, etc.[642 ] In addition, potential en-

ergy generated during wastewater treatment, such as water wave

energy, wind energy, and acoustic energy, can be harvested us-

ing self-powered technology.[643] Liu et al.[ 644] demonstrated a

self-powered wastewater treatment system based on water-driven

TENG, which eﬀectively improved the removal eﬃciency of 4-

chlorophenol. The output voltage of this water-driven TENG can

reach 22 V, which increases the removal rate of 4-chlorophenol by

10% in 120 min. In addition, Cai et al.[645] proposed self-powered

sterilization of cellulose ﬁbers based on liquid-solid TENG. The

TENG converts the liquid energy of the cellulose suspension

into electrical energy and then converts it into pulsed direct cur-

rent for sterilizing cellulose ﬁbers. Experiments have shown that

this method has excellent sterilization eﬀects on microorganisms

such as E. coli and A. niger. Therefore, this method provides new

ideas for liquid energy recovery and pulp sterilization in the paper

industry. Metal corrosion is very common in industrial produc-

tion, causing huge losses and safety hazards. Cathodic protection

is a commonly used anti-corrosion measure. Its principle is to

apply an external current to the surface of corroded metal struc-

tures to inhibit the electron migration process of metal corrosion,

thereby avoiding or weakening the occurrence of corrosion.[646 ]

Xu et al.[647] developed a highly elastic and pressure-resistant

sponge TENG for harvesting mechanical energy, using stainless

steel for corrosion protection. The sponge TENG is used for ca-

thodic protection, allowing the metal material electrode to en-

ter a thermodynamically stable state, thereby achieving the anti-

corrosion eﬀect.

5.11. Self-Powered Microelectronics in Natural Environment

Monitoring

The natural environment includes ecosystems such as forests,

grasslands, and wetlands, which are closely related to the devel-

opment and progress of human society. The protection and mon-

itoring of the natural environment is receiving increasing global

attention. Monitoring the natural environment will help protect

the ecological environment, prevent natural disasters, and pro-

mote the healthy development of the natural environment. The

monitoring of the natural environment cannot be separated from

wide-area low-power wireless sensors. The rise of self-powered

technology will replace traditional chemical batteries to power

wireless monitoring sensors, in order to avoid issues such as elec-

trochemical pollution and frequent battery replacement. These

self-powered monitoring devices can be categorized as: wind

monitoring devices,[648 ] rain monitoring devices,[649 ] and natural

disaster monitoring devices,[650 ] as shown in Figure 17.

As a renewable clean energy, wind energy can be eﬀec-

tively collected by energy harvesting devices. Monitoring wind

speed and direction is crucial for natural disaster prevention,

weather forecasting, air quality, and wind power generation ca-

pacity prediction.[659 ] Traditional wind speed sensors have the

drawbacks of complex structure and high cost, and TENG-

based self-powered wind speed sensors provide a feasible al-

ternative solution.[660 ] Wang et al.[661] proposed a triboelectric–

electromagnetic hybrid nanogenerator as a self-powered wind

speed sensor. The TENG module uses a soft and elastic contact

method to reduce the starting torque so that it can detect wind

speeds as low as 3.5 m s−1. Furthermore, He et al.[651] developed

a dual-mode TENG for wind energy harvesting and wind speed

detection, as shown in Figure 17a. The AC-TENG module is used

to collect energy, and the DC-TENG module realizes wind speed

detection and strong wind warning. Experiments show that the

correlation coeﬃcient between wind speed and voltage frequency

is as high as 0.999, showing excellent wind speed monitoring ac-

curacy. In order to improve the range of wind speed monitoring,

Ye et al.[ 662] proposed a broadband triboelectric-electromagnetic

hybrid nanogenerator with a wind speed response range of 1.55

to 15 m s−1, which provides a new idea for wind speed sensing.

Not only wind speed, but wind direction monitoring also plays a

key role in ﬁelds such as weather forecasting and environmen-

tal monitoring.[663 ] Jin et al.[664 ] developed an omnidirectional

wind energy harvester. The design of the self-suspending shell

can make it possible to collect wind energy uniformly from any

direction. In addition, the device can be used as a self-powered

wind speed and direction sensor, which uses the voltage distribu-

tion signals on the eight electrodes to predict the wind direction,

and the maximum RMS voltage to judge the wind speed. Zhao

et al.[652 ] proposed a biomimetic TENG for wind energy harvest-

ing (Figure 17b). The special structure of the generator can obtain

16 output voltage signals, and 8 wind directions can be judged

through electrical signal analysis. In addition to the commonly

used method of judging wind direction by triboelectric voltage

signal analysis, photoelectric wind direction detection technology

has also attracted people’s attention. Xe et al.[653] proposed a wind

vector detection system based on triboelectric and photoelectric

sensors, as shown in Figure 17c. The current frequency of the

angle-shaped triboelectric sensor has a good linear relationship

with the wind speed and a wide wind speed sensing range be-

tween 2.9 and 24.0 m s−1is realized. The wind direction sensor

based on photoelectric detection can accurately identify the wind

speed in 8 directions and successfully demonstrate the wind vec-

tor detection system developed on the LabVIEW platform.

In the natural environment, monitoring rainfall and river wa-

ter levels is also very important for preventing drought and ﬂood

disasters and meteorological records.[665 ] Rain gauge is a com-

mon tool for rainfall detection, but the traditional tipping-bucket

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Figure 17. Self-powered microelectronic devices for natural environment monitoring. a) A dual-mode TENG for wind energy harvesting and wind

Elsevier. e) A raindrop-TENG array for raindrop energy harvesting and rainfall sensing. Reproduced under the terms of the CC–BY license. [655] Copy-

right 2022, the authors, published by Springer Nature. f) An electromagnetic/triboelectric hybrid generator for river ﬂow velocity detection. Repro-

rain gauge has problems such as low resolution, poor measure-

ment accuracy, and insuﬃcient durability. He et al.[ 654] devel-

oped a TENG-based self-powered rain gauge with excellent rain-

fall detection performance and rainwater harvesting capability,

as shown in Figure 17d. The triboelectric signal frequency of the

proposed self-powered rain gauge has a linear relationship with

the rainfall intensity, which can detect the rainfall intensity from

0to288mmd

−1in real time. In addition, the minimum rainfall

resolution of the device is 5.5 μm, and it has excellent anti-wet

interference ability, which provides a solution for real-time rain-

fall monitoring in extreme weather environments. The TENG

based on the liquid-solid interface can directly convert rainfall

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information into electrical signals without other complicated

mechanical structures, which has certain advantages in rainfall

monitoring. Xu et al.[655] developed a raindrop-TENG array for

raindrop energy harvesting and rainfall sensing, as shown in

Figure 17e. Under the rainfall intensity of 71 mm min−1, the open

circuit voltage and maximum output power of the generator ar-

ray are 1800 V and 325 μW, respectively. In addition, the voltage of

the generator array has a strong linear relationship with the rain-

fall intensity, and the sensitivity is 0.239 V/(mm min−1), showing

good sensing performance. This work successfully demonstrates

an autonomous rainfall monitoring and wireless transmission

system, opening the way for weather monitoring, IoT, etc. In ad-

dition to the detection of rainfall intensity, acid rain detection is

also very necessary in production and life. Liu et al.[666 ] developed

a self-powered acid rain sensor, which was implemented by a

composite ﬁlm TENG. Both the voltage and current of the device

exhibit a good linear relationship between pH values, and it has

excellent pH sensitivity. This work provides a feasible strategy for

acid rain detection without a power supply. Heavy rainfall often

leads to surges in river ﬂow, so an electromagnetic/triboelectric

hybrid generator for river ﬂow velocity detection was developed,

as shown in Figure 17f.[118 ] The generator uses the frequency of

triboelectric signals to determine the ﬂow velocity of a river. In

addition, this work also developed a wireless sensor system for

measuring water ﬂow velocity, which is of great signiﬁcance for

environmental monitoring and disaster warning.

Natural disasters are catastrophic events caused by natural

forces that can cause great damage to humans, animals, and

the environment. At present, many self-powered natural disas-

ter monitoring sensors have been developed, such as ﬁre moni-

toring sensors,[667 ] earthquake monitoring sensors,[668 ] and land-

slide monitoring sensors,[669 ] which will provide scientiﬁc basis

for disaster prevention and rescue. The occurrence of forest ﬁres

can cause great harm to humans and nature, and self-powered

wireless ﬁre sensors are eﬀective for ﬁre monitoring.[670 ] Peng

et al.[671 ] developed a multilayer cylindrical TENG to harvest tree

branch kinetic energy to power commercial ﬁre monitoring sen-

sors. This work demonstrates a self-powered forest ﬁre moni-

toring system integrating TENG, micro-supercapacitors, and ﬁre

sensors. Liu et al. [656 ] proposed a self-powered forest ﬁre alarm

system based on TENG and thermal sensors (Figure 17g). When

there is an open ﬂame, the resistance of the thermal sensor is sig-

niﬁcantly reduced, so that the TENG output voltage changes and

the LED is turned on to achieve the purpose of alarm. As shown

in Figure 17h, Zhang et al.[657 ] proposed a TENG based on the

ﬂow-induced vibration eﬀect to collect multi-directional breeze

to build a self-powered ﬁre detection system. The TENG can be

used as a wind direction sensor to detect wind in 6 directions,

and can also harvest energy to power the smoke concentration

detection system. The system not only enables ﬁre detection but

also predicts the speed and direction of ﬁre spread. Earthquake

is a highly destructive natural disaster. Using self-powered seis-

mic sensors to monitor and analyze seismic activity can help re-

duce environmental damage, economic losses, casualties, etc.[672 ]

Yang et al.[673 ] proposed a hybrid TENG to harvest low-frequency

vibrational energy, as well as serve as a self-powered vibration

sensor. Using the linear relationship between the peak number

of triboelectric signals and vibration amplitude, a self-powered vi-

bration amplitude sensing system for bridge vibration and earth-

quake detection was developed. Furthermore, Kim et al.[658] de-

veloped a levitating oscillator-based TENG for monitoring earth-

quake hazards (Figure 17i). Due to the use of suspension design,

TENG has frictionless characteristics. In addition, experiments

have shown that TENG has the advantages of high sensitivity,

high output, and long sustained output time. Applying force ex-

citation to TENG-based seismic sensors, the monitoring software

program successfully detected seismic vibrations, providing new

ideas for seismic monitoring in remote areas.

6. Conclusion, Challenges and Prospects

AI and IoT are driving the rapid development of microelectronic

devices based on self-powered technology, which profoundly af-

fects the development of the world. This paper comprehensively

reviews recent advances, challenges, and future directions in

the self-powered microelectronic world. The general research

progress of human body wearable devices, animal wearable de-

vices, and environmental monitoring sensors is summarized. Be-

sides, this paper provides a detailed summary of the characteris-

tics of available environmental energy sources for self-powered

microelectronics, and the basic principles and characteristics of

energy harvesting technology. From an application-oriented per-

spective, this paper comprehensively summarizes the progress

of self-powered microelectronics in multidisciplinary applica-

tion scenarios such as human wearable devices (glasses, hearing

aids, masks, backpacks, watches, wristbands, gloves, exoskeleton

systems, shoes, and socks), animal wearable devices (land, ﬂy-

ing, and aquatic), and environmental monitoring sensors (intel-

ligent transportation, smart ocean, smart home, smart agricul-

ture, smart industry, and natural environment monitoring). Fi-

nally, research gaps and future advanced research directions in

this ﬁeld have been proposed in response to the shortcomings of

self-powered microelectronic devices.

Although signiﬁcant progress has been made in the research

and application of self-powered microelectronic devices, they still

face signiﬁcant challenges to achieve more widespread applica-

tions. Most self-powered microelectronics today operate as a sin-

gle node. However, single nodes have great shortcomings in en-

ergy harvesting, signal sensing, and system integration, making

it diﬃcult to deal with unknown challenges. Continuously im-

proving the performance of the AI-assisted multi-node network-

ing system can meet the needs of the current era. In addition, ma-

terials are the basis of devices, and the development of advanced

materials can continuously promote the progress of self-powered

sensing systems. Looking forward to the future, further in-depth

research is needed in the following areas, as shown in Figure 18.

1) Single-node self-powered microelectronics have two main

functions: energy harvesting and signal sensing. The energy har-

vesting module realizes the conversion of environmental energy

into electrical energy through an energy conversion mechanism.

Currently, the module needs to continuously improve energy har-

vesting eﬃciency and power to cope with the ever-increasing

power demand. The constant change of the external environment

requires improving the stability of energy harvesting. At the same

time, long-term durability needs to be continuously improved

to ensure that single-node devices have excellent long-term sta-

ble operation performance. Due to the intermittent and unstable

environmental excitations, eﬃcient energy management circuits

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Figure 18. Future prospects of the self-powered microelectronic world.

are required to improve energy utilization. Especially for minia-

turized electronic products, more ﬂexible and eﬃcient manage-

ment circuits are needed. The energy storage unit is very critical

for storing the collected electric energy, and it is very important

to improve the energy storage eﬃciency and solve the impedance

mismatch problem between the energy harvesting module and

the energy storage unit.

2) The signal sensing unit of the single-node self-powered mi-

croelectronics has the ability of self-sensing, which can realize

the response to the excitation signal of the external environment.

First of all, it is necessary to continuously improve the sensitiv-

ity of the sensor and reduce the response time to cope with the

rapid external excitation. At the same time, the response range

and working bandwidth need to be increased to enhance the en-

vironmental adaptability of the sensing module. In addition, in

a long-term working environment, the stability and durability of

sensing need to be improved. The durability of the sensor can

be improved by surface treatment, such as using wear-resistant

materials.

3) Materials are the basis of devices, and the development

of self-powered sensing nodes is inseparable from the advance-

ment of advanced materials. Advanced materials represented

by cellulose triboelectric materials are developing rapidly, but

they still face many diﬃculties.[674 ] In order to improve self-

power eﬃciency and power, physical surface modiﬁcation meth-

ods can be used, such as etching processes and patterning pro-

cesses. In addition, the self-power supply performance can also

be improved through chemical surface modiﬁcation methods

such as plasma treatment and neutral beam irradiation. In ad-

dition to indicating modiﬁcation, modiﬁcation of materials is

also very important. The development of composite materials

such as ﬂexible/stretchable composites based on material mod-

iﬁcation can signiﬁcantly improve the performance of gener-

ators. It is crucial to develop application-oriented functional

materials.[675 ] High-humidity environments require the develop-

ment of hydrophobic materials, and highly corrosive environ-

ments require anti-corrosion materials. In addition, the applica-

tion scope of the material needs to be expanded so that it can

maintain high stability, sensitivity, and output power in various

extreme environments.[676,677 ]

4) The self-powered sensing system integrating energy har-

vesting and signal sensing ﬁrst needs to ensure the energy bal-

ance between the power generation capacity and the power de-

mand of the signal sensing module. It is necessary to ensure

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oversupply to achieve self-powered sensing of single-node de-

vices. Besides, improving the system’s integration level is neces-

sary to make it a highly integrated system. In addition, the econ-

omy and environmental friendliness of the system are also very

important. Costs and beneﬁts in practical applications must be

considered to improve economic performance. It is necessary to

use degradable and environmentally friendly materials to reduce

the impact of self-powered devices on the environment during

operation.

5) A multi-node system can be formed by networking multi-

ple self-powered micro-power nodes through IoT technology. It

has high performance, reliability, and scalability compared to a

single-node system. However, multi-node systems also face many

challenges. Due to the large power requirements and impedance

mismatch of wireless signal transmission modules, more intelli-

gent network energy management can reduce signal transmis-

sion consumption and improve network performance and ef-

ﬁciency. As the amount of information transmitted increases,

multi-node networks need higher bandwidth and lower latency.

In order to adapt to diﬀerent application requirements and net-

work environments, more ﬂexible network architecture and de-

ployment methods are needed to achieve optimal network perfor-

mance and coverage. In addition, multi-node networks should in-

troduce better privacy protection mechanisms to improve system

security for the increasing network attacks and data leakage.

6) With the continuous advancement of technology, AI has

made breakthroughs. AI-assisted self-powered microelectronics

have also been extensively developed and applied in multiple

ﬁelds. In the future, it is necessary to continuously optimize al-

gorithms to improve the running speed and computational eﬃ-

ciency of the system, to cope with the surge in random excita-

tion signals and data volume. Additionally, AI must move toward

multimodal techniques to process signals involving multiple in-

put modalities. At present, in self-powered sensor monitoring, it

is necessary to intervene and regulate the input data artiﬁcially.

Autonomous learning does not require human intervention, and

machines can learn autonomously from data, further improving

the system’s autonomous decision-making capabilities. In the fu-

ture, AI will be further combined with self-powered sensing tech-

nology and applied in more ﬁelds, such as medical treatment,

manufacturing, transportation, agriculture, and the ocean.

In summary, self-powered microelectronics are a key technol-

ogy for energy development and signal utilization in the IoT era.

Although various challenges still exist, with the assistance of AI

technology and advanced materials, self-powered microelectron-

ics technology will be better studied, explored, and developed to-

ward intelligence, integration, multifunctional, and miniaturiza-

tion. As self-powered microelectronics technology becomes in-

creasingly mature, many ﬁelds will become more intelligent and

low-carbon, including smart homes, smart cities, smart trans-

portation, smart agriculture, smart manufacturing, smart ocean,

etc.

Acknowledgements

This work was supported by the Special Posts of Guizhou University (No.

[2023] 27), the 2023 General Undergraduate University Scientiﬁc Research

Project of Guizhou Provincial Department of Education (Guizhou Edu-

cational Technology [2022] 107) project, the Innovation team of Guizhou

Province CXTD2022-009 project, the Swedish Knowledge Foundation (KK-

Stiftelsen) “FREE” project, the Swedish Research Council “Synergies of

distributed multienergy systems for eﬃcient integration of large shares of

renewable energies” project.

Conﬂict of Interest

The authors declare no conﬂict of interest.

Keywords

energy harvesting, environmental monitoring, microelectronics, self-

sensing technology, wearable devices

Received: August 15, 2023

Revised: October 9, 2023

Published online:

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Lingfei Qi is now working at Guizhou University,in China. Dr. Qi got his PhD degree from Southwest

Jiaotong University and served as a guest PhD at Mälardalen University for two years. Dr.Qi focuses on

energy harvesting and conversion technologies, including environmental vibration energy harvesting,

wind energy harvesting, wave energy harvesting, triboelectric generators, etc. Dr.Qi has published

over 30 peer-reviewed journal papers and owns more than 30 patents. His work aims to harvest ambi-

ent clean/wasted energy and enable self-power and self-sensing of distributed low-power microelec-

tronics. Dr.Qi is a distinguished professor and academic subject leader at Guizhou University.

2302699 (58 of 59)

www.advancedsciencenews.com www.advenergymat.de

Lingji Kong received his B.S. in mechanical engineering from Southwest Jiaotong University in 2021.

Now he is a PhD candidate at Southwest Jiaotong University.His research interests mainly focus on

wearable self-powered sensing technology,microelectronics technology, and artiﬁcial intelligence

IoT technology.Currently, he has published over 10 peer-reviewed journal papers. His work aims to

harvest human body energy to achieve self-sustainable human intelligent sensor networks.

Zhang Zutao is a professor at Southwest Jiaotong University,vice president of Chengdu Institute of

Technology, and one of the top 2% of scientists in the world in 2023. His research focuses on renew-

able and intelligent vehicles, energy harvesting and self-sensing technology,and assistive vehicle

safety technology.Prof. Zhang hosted 3 National Natural Science Foundation of China projects. As

the ﬁrst/corresponding author in Advanced Energy Materials, Nano Energy,Renewable & Sustainable

Energy Reviews, Small Methods, Applied Energy,IEEE Transaction on Intelligent Transportation Sys-

tems, Mechanical Systems and Signal Processing, and other journals published more than 130 journal

papers.

Jinyue Yan is an esteemed academician of the European Academy of Sciences and Arts, currently serv-

ing as a chair professor at the Hong Kong Polytechnic University. With a PhD from the Royal Insti-

tute of Technology (KTH), he has held chair professor positions at Luleå University of Technology,

Mälardalen University,and KTH. Prof. Yan’s research focuses on renewable energy, advanced energy

systems, climate change mitigation, and environmental policies. He has an impressive publication

record of over 400 papers in renowned journals and holds more than 10 patents. Having supervised

≈200 post-doctoral researchers and 50 doctoral candidates.

2302699 (59 of 59)

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