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Review
Advancements in Energy Harvesting: Piezoelectric, Triboelectric, Pyroelectric,
and Magnetoelectric Technologies for Self-powered Sensor Systems
Biswajit Mahanty (Mahanty B), Dong-Weon Lee (Lee DW)
DOI : https://doi.org/10.57062/ijpem-st.2024.00080

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Int. J. Precis. Eng. Manuf.-Smart Tech. > Volume 2(2); 2024 > Article


Mahanty and Lee: Advancements in Energy Harvesting: Piezoelectric,
Triboelectric, Pyroelectric, and Magnetoelectric Technologies for Self-powered
Sensor Systems

Review



International Journal of Precision Engineering and Manufacturing-Smart
Technology 2024;2(2):151-167.

Published online: July 1, 2024

DOI: https://doi.org/10.57062/ijpem-st.2024.00080


ADVANCEMENTS IN ENERGY HARVESTING: PIEZOELECTRIC, TRIBOELECTRIC, PYROELECTRIC,
AND MAGNETOELECTRIC TECHNOLOGIES FOR SELF-POWERED SENSOR SYSTEMS

Biswajit Mahanty1 · Dong-Weon Lee1.2.3

1MEMS and Nanotechnology Laboratory, School of Mechanical Engineering, School of
Mechanical Engineering, Chonnam National University, 77 Yongbong-ro, Buk-gu,
Gwangju 61186, Republic of Korea

2Advanced Medical Device Research Center for Cardiovascular Disease, Chonnam
National University, 77 Yongbong-ro, Buk-gu, Gwangju 61186, Republic of Korea

3Center for Next-generation Sensor Research and Development, Chonnam National
University, 77 Yongbong-ro, Buk-gu, Gwangju 61186, Republic of Korea

Dong-Weon Lee, mems@jnu.ac.kr



Received May 27, 2024       Revised June 19, 2024       Accepted June 19, 2024

© Korean Society for Precision Engineering 2024




ABSTRACT

In the era of Internet of Things (IoT) advancements, millions of sensors and
electronic devices are interconnected through the internet. A reliable power
source is required for their continuous operation. Self-powered sensor systems
have emerged as promising solutions for various applications including wearable
devices and environmental monitoring, benefiting both society and the
environment. These systems can maintain themselves by eliminating the need for
external power sources or frequent battery replacements and converting discarded
energy sources around them into electrical energy. Among various energy
harvesting technologies, piezoelectric, triboelectric, pyroelectric, and
magnetoelectric mechanisms have garnered significant attention due to their
ability to convert mechanical, frictional, thermal, and magnetic energy into
electrical power, respectively. This review aims to provide a comprehensive
overview of recent advances in these technologies for self-powered sensor
systems, catering to a wide audience. It explores fundamental principles of
their-energy harvesting mechanisms, highlighting their strengths, limitations,
and potential applications. In addition, this review discusses challenges
related to the development of nanogenerator-based self-powered sensor systems
and presents new opportunities for their advancement.



Keywords: Energy harvester · Self-powered sensor · Wearable device ·
Piezoelectric nanogenerator · Triboelectric nanogenerator

Go to :


LIST OF SYMBOLS

IOT

Internet of Things

PENG

Piezoelectric Nanogenerator

TENG

Triboelectric Nanogenerator

PyNG

Pyroelectric Nanogenerator

ME

Magnetoelectric


1 INTRODUCTION

Over the past few years, the Internet of Things (IoT) has permeated various
sectors, including advanced agriculture through smart farming, innovative
residential spaces via smart homes, automated industries with smart sensor
technology, personal healthcare systems with wearable sensors, and even
commonplace household items [1]. IoT network technology ensures that a wide
range of sensors and electronics are continuously connected and operational
24/7. The uninterrupted and reliable operation of the smart sensors, which are
key component of these systems, requires a continuous supply of electrical
power. Traditionally, the use of various types of small batteries to power these
devices has been effective to some extent. However, the widespread deployment of
wireless sensors presents challenges such as the need for regular charging and
the increased cost associated with battery replacement. Moreover, these
batteries often contain chemicals that are not only toxic but also pose serious
environmental and health risks [2]. Therefore, there is growing interest in
recycling various discarded energy sources and developing self-powered
electronics that use sustainable energy. Additionally, relevant innovations can
provide environmentally friendly alternatives, reducing reliance on potentially
harmful battery technologies and paving the way for more sustainable and secure
implementation of IoT systems across different domains. Achieving sustainability
in power sources for electronic devices involves harnessing ambient
environmental energy such as vibrational or mechanical energy, thermal energy,
and electromagnetic waves, and converting it into useful electrical energy. This
promising technology is gaining traction through several innovative harvesting
devices. Notably, piezoelectric nanogenerators (PENGs) and triboelectric
nanogenerators (TENGs) are at the forefront of converting environmental
mechanical or vibrational energy into electrical energy. On the other hand,
pyroelectric nanogenerators (PyNGs) utilize the heat energy from human body
warmth, vehicle exhausts, convection, and solar radiation, converting it into
electrical energy through the pyroelectric effect [3–8]. Additionally, the
magnetoelectric (ME) energy harvesters also play a crucial role by converting
magnetic energy into electrical energy and vice versa [9,10]. In general, people
are generally exposed to 50/60 Hz electromagnetic fields, which can be used as
an energy source in their daily lives [10,11]. At the heart of the technology
required to exploit discarded electromagnetic fields in this field is the
development of superior ferroelectric materials based on ceramics, polymers, and
magnetostrictive alloys. However, the development of new materials with superior
properties is a challenging and time-consuming process. Among many examples,
piezoelectric effects, one of the fastest techniques to enter the market, occur
when an external force is applied to piezoelectric materials, causing the
charges to move within the material and creating an electric dipole. This
movement results in a voltage potential from the change in distance between the
charges at the dipole’s ends. For PyNGs, the pyroelectric materials capitalize
on time-dependent temperature changes (dT/dt) to generate electrical signals
[9]. In magnetoelectric effects, the strain from the magnetic field is
transferred to the piezoelectric layer, inducing electric polarization through
the piezoelectric effect [12]. TENGs work on the principle of static electricity
generated through contact electrification, where touching materials exchange
charges, leading to one material becoming positively charged and the other
negatively charged [1,7,8]. These devices typically utilize materials such as
Fluorinated Ethylene Propylene (FEP), Silicone, and Polytetrafluoroethylene
(PTFE) to achieve negative charging, and Polyamides (PA), Indium Tin Oxide
(ITO), and Zinc Oxide (ZnO) for positive charges [1,13]. Each of these energy
harvesters offers distinct advantages and challenges, and they are increasingly
employed in energy harvesting and sensing technologies, as detailed in the
provided tables. However, most nanogenerator technologies developed to date to
build smart systems or environments still have problems in terms of device size,
low voltage or current, and long-term reliability.

TABLE 1

Comparison of piezoelectric, triboelectric, pyroelectric, and magnetoelectric
nanogenerators

Piezoelectric Triboelectric Pyroelectric Electromagnetic Advantages

 * High output voltage

 * High electric capacitor

 * Simple use

 * Robustness

 * Large T° range

 * Very high output voltage

 * Harvesting on low frequencies

 * Simple implementation and integration

 * Coupling coefficient easy to adjust

 * High output voltage

 * Possibility to harvest on quick change of temperature as a function of time

 * High output current

 * Robustness

 * Long lifetime proven

Disadvantages

 * The conversion properties of the micro-generator is intimately related to
   those of the piezoelectric element

 * Needs a polarization source.

 * Complex power circuit management

 * Mechanical guiding

 * Low capacitor (sensible to parasitic capacitor)

 * No information about time life

 * Insufficient knowledge on temperature resistance

 * The conversion properties of the micro-generator are intimately related to
   the one of the pyroelectric elements.

 * Insufficient knowledge on temperature resistance

 * Difficulty of harvesting on spatial gradients, needs a spatial-to-temporal
   conversion using thermal machine

 * Low output voltage, problem of electronic management

 * Bulky

 * Requirement of precision machining

 * Insufficient knowledge on temperature resistance

 * Low efficiency in low frequencies and small sizes

 * Problem of electromagnetic compatibility



This comprehensive review offers insights into recent advancements in energy
harvesting, emphasizing four types of energy harvesters: Piezoelectric
Nanogenerators (PENGs), Triboelectric Nanogenerators (TENGs), Pyroelectric
Nanogenerators (PyNGs), and Magnetoelectric (ME) energy harvesters. It
thoroughly explores the materials involved, their practical applications in
powering self-sufficient sensors, the inherent challenges they face, and the
future prospects of these technologies. This paper aims to deepen the
understanding of nanogenerators for those intrigued by the dynamic field of
energy harvesting, providing both a foundational overview and a detailed
examination of the current state and potential advancements in these critical
technologies.
Go to :



2 CLASSIFICATION OF ENERGY HARVESTERS


2.1 PIEZOELECTRIC ENERGY HARVESTERS

2.1.1 MECHANISM OF PIEZOELECTRIC EFFECTS

Mechanical energy harvesting is facilitated through the use of Piezoelectric
Nanogenerators (PENGs). For a better understanding of piezoelectric effects, the
working mechanism for the PENG is described in Fig. 1(a). The piezoelectric
layer, when polarized, contains dipoles arranged in a specific direction, which
enhances its piezoelectric performance. Initially, when the material is in a
stress-free state (Fig. 1(a-I)), charges accumulate on the surface to maintain
electrical balance. When compressive stress is applied (Fig. 1(a-II)), the
polarization decreases, causing the surface charges to move and generate an
electric current. Conversely, removing stress or applying tensile stress (Fig.
1(a-III)) increases the polarization, leading to a current flow in the opposite
direction to restore balance [14].

FIG. 1

(I) (a) Working mechanism of PENGs [4] (Adapted from Ref. 4 with permission),
(b) Schematic of capacitor charging process with an equivalent circuit diagram
and several capacitor charging performances, [18] (Adapted from Ref. 18 with
permission, Copyright 2022, Wiley), (c) Schematic of the all-fiber PPNG
comprising of (i) a large area PVDF–MWCNT nanofiber mat (8 × 7 cm). (ii) FESEM
images of the PVDF–MWCNT nanofiber and (iii) micro-fiber based conducting
electrode. (d) The excellent flexibility and conformability of PVDF–MWCNT
electrospun nanofibers is shown by wrapping them on a human finger. Energy
harvesting characterization of nanogenerators. (e) Pressure dependent output
open circuit voltage (Voc) of the PPGN, [3] (Adapted from Ref. 3 with
permission, Copyright 2022, RSC), (f) Schematic of the electrospinning setup
where a needle is connected to the positive terminal of the high-voltage supply
and the plate collector is grounded. (g) Digital photograph of the electrospun
nanofiber mat. (h) Open-circuit output voltage of C-PNG under a compressive
pressure of 22 kPa [19] (Adapted from Ref. 19 with permission), (II) The concept
of hetero-layer structure PENG (HT-PENG). (a) The schematic of layer-by-layer
hetero-structure PENG with interspace metal sheet. b) Cross-sectional SEM image
of the HT-PENG. (c) open circuit voltage (Voc) and (d) short-circuit current
(Isc) of the HT-PENGs. (e) The Voc and (f) Isc of the optimized 6 layers HT-PENG
[6] (Adapted from Ref. 6 with permission)



2.1.2 PIEZOELECTRIC MATERIALS AND ITS PROGRESS

Ferroelectric materials are promising for energy harvesting through
piezoelectricity. Various materials, including ceramics, polymers, and
piezoelectret polymers, are used in PENG fabrication. The piezoelectric ceramics
exhibit micro/nanostructures of wurtzite and perovskite. Examples of
piezoelectric ceramics with wurtzite micro/nanostructures include ZnO NW, CdS,
ZnS, and group III nitrides (InN, GaN, AlN). Examples of piezoelectric ceramics
with perovskite micro/nanostructures include PZT, PMN-PT, BaTiO3, ZnSnO3, and K,
NaNbO3. The performance of piezoelectric ceramics is superior due to their high
piezoelectric coupling coefficient (d33), but they are brittle in nature and
some contain lead, which is highly toxic to the environment. Therefore, their
use in flexible sensors or certain biomedical applications is limited. In
contrast, the ferroelectric polymer such as synthetic (e.g. PVDF and its
copolymers) and natural (e.g. silk, cellulose, and collagen) are have gained
intense interest in energy harvesting and sensor applications due to their
exceptional mechanical flexibility, ease of fabrication, environment friendly,
and biocompatibility [6,15]. In addition to that, ferroelectret polymers, like
cellular PP foams, possess piezoelectret properties as a result of charge
accumulation within their voids. To achieve high piezoelectric performance while
preserving excellent device flexibility, a specific number of piezoelectric
ceramics is incorporated into the polymer matrix [9,15]. The mechanism of charge
generation in ferroelectret polymers differs from that of ferroelectric polymers
[16,17]. Extensive research has been conducted to enhance the performance of
piezoelectric nanogenerators (PENGs), focusing on parameters such as open
circuit output voltage, short circuit current, power density, and energy
conversion efficiency [2,6,15,16]. For example, Ghosh et al. proposed platinum
(Pt) nanoparticles incorporated P(VDF-HFP) composite film for flexible
ferroelectretic nanogenerator (FTNG) [18]. The as prepared FTNG generated an 18
V open circuit voltage with an energy conversion efficiency of 0.2%. The
schematic of the capacitor charging process with an equivalent circuit diagram
and several capacitor charging performances is illustrated in Fig. 1(I-b).
Mahanty et al. proposed an all-fiber pyro-and piezoelectric nanogenerator (PPNG)
by incorporating MWCNT into PVDF nanofiber [3]. The schematic of the fabricated
device is shown in Fig. 1(I-c) with excellent flexibility in Fig. 1(I-d). The
fabricated PPNG demonstrated improved performance with an open-circuit voltage
of approximately 35 V, an instantaneous power density of around 34 μW·cm−2, and
an energy conversion efficiency of 19.3%. The pressure dependent output voltage
of PPNG is shown in Fig. 1(I-e). The fabricated device was able to detect human
physiological signals wirelessly through a mobile device, enabling remote
healthcare monitoring. Furthermore, Roy et al. adopted a scalable approach by
incorporating a [Cd(II)-μ-I4] two-dimensional (2D) metal-organic framework (MOF)
bridged by naphthylamine into PVDF composite nanofibers mat [19]. The schematic
of electrospinning setup and fabricated nanofiber mat is shown in Figs. 1 II-f
and 1II-g respectively. The fabricate device generated high electrical output
(open circuit output voltage ~22 V (Fig. 1(I-h)), and power density ~24 μW·cm−2)
under periodic imparting. The composite nanofibers showed a superior
electroactive β-phase content of 98% with a high piezoelectric coefficient of 41
pC N−1. However, all these devices are composed of a single layer as the
piezoelectric active layer. In order to improve the performance of the PENG
layer-by-layer structure was adopted further [20–24]. Several studies have
demonstrated that homo-layered structure PENGs can significantly improve output
performance. To overcome the limitations of homo-layered PENGs, a
hetero-structured PENG (HT-PENG) was created, showing enhanced voltage and
current output. The schematic of the layer-by-layer hetero-structure PENG with
interspace metal sheet and cross-sectional SEM images of the as-prepared HT-PENG
are shown in Figs. 1(II-a) and 1(II-b), respectively. The open-circuit voltage
and short-circuit current of the HT-PENG are shown in Figs. 1(II-c) and 1(II-d),
respectively. Furthermore, the open-circuit voltage and short-circuit current of
the optimized 6th layer HT-PENG are shown in Figs. 1(II-e) and 1(II-f),
respectively. The optimized six-layered HT-PENG achieved an open circuit output
voltage of 350 V, a short circuit current of 6 μA, and a power output of 3.62
W·m−2 [6].


2.2 TRIBOELECTRIC ENERGY HARVESTERS

2.2.1 MECHANISM OF TRIBOELECTRIC EFFECTS

In addition to PENGs, mechanical energy can be efficiently converted into
electrical energy using Triboelectric Nanogenerators (TENGs), which operate in
four distinct modes: vertical contact separation (VCS), linear sliding mode
(LSM), single-electrode mode (SEM), and free-standing mode (FSM), as depicted in
Fig. 2(a) [14,25]. TENGs function based on the principles of the parallel-plate
capacitor model and the dependence of the electric field on the distance to
optimally match electrical loads [14]. Table 2 presents a detailed overview of
the structural characteristics, advantages, disadvantages, and potential
applications of each operational mode [14]. Fig. 2(b) demonstrates a TENG
operating in the VCS mode. Initially (Fig. 2(b-I)), when the layers of the
device are compressed together, triboelectric charges are generated. As these
layers are released and separate (Fig. 2(b-II)), a potential difference is
created between the charged layers. This difference drives the movement of free
charges in the electrodes to balance the potential, thereby generating a current
flow when the device is connected to a load resistance (R). Once the surface
charge balances, the current flow ceases (Fig. 2(b-III)). Re-compressing the
films allows the previously accumulated charges to flow back into the circuit,
producing a current flow in the opposite direction.

FIG. 2

Fundamental modes of triboelectric nanogenerators and triboelectric effects for
energy harvesting, [14] (Adapted from Ref. 14 with permission). (a) Four
fundamental modes of operation of TENGs, (b) triboelectric effect in
contact-separation mode for energy harvesting [14] (Adapted from Ref. 14 with
permission). (c) Schematic illustration of electrospinning of Nylon 11 followed
by PLL surface modification. (d), (e) Output performances (Voc, and Isc), [31]
(Adapted from Ref. 31 with permission). (f) The microporous hierarchical
composite TENG, dielectric permittivity of TPU and its different composite
films, and the output voltage of TPU and its composite based TENGs, [32]
(Adapted from Ref. 32 with permission, Copyright © 2022, American Chemical
Society). (g) The schematic representation of the fabrication process of
LC-MXene/ZiF-67, (h) variation of power and power density with load resistance
from CM-TENG, [34] (Adapted from Ref. 34 with permission).



TABLE 2

Comparison of different working modes of TENGs

Operation modes Structure Benefits Drawbacks Key parameters Potential uses VCS
Vertical movement, large gap in between High open-circuit output voltage Pulse
output Average velocity, dielectric thickness; separation distance Pressure,
force, angle position, and pulse sensing LSM Horizontal/rotational movement,
very small gap High bandwidth, continuous and high electricity output Poor
long-term reliability Sliding velocity and distance Flow energy harvesting SE
One operated electrode; one grounded Simple, versatile, easy to fabricate; can
be integrated on other devices Relatively low output power Active aera size;
electrode gap distance Touching/typingscreen FSM Multiple forms of movements,
symmetric electrodes, asymmetric, charge distribution High energy conversion
efficiency Fixed electrodes difficult to integrate Free-standing height,
electrode gap Rotational and vibration energy harvesting



2.2.2 TRIBOELECTRIC MATERIALS AND ITS PROGRESS

TENGs generate static electricity through contact electrification. When two
materials come into contact, charges are exchanged between them, resulting in
one material becoming positively charged and the other becoming negatively
charged [26–28]. Tremendous research work has been carried out in order to
improve the electrical performance of TENGs for energy harvesting and sensor
applications [25,29,30]. However, there is still room for further improvement in
terms of energy conversion efficiency, open circuit output voltage, short
circuit current, power density, and sensitivity for self-powered wearable
sensors in human-machine interaction. The charge transfer mechanism occurring on
the surface of the two tribo materials during physical contact stands as a
pivotal factor in optimizing the output performance of a TENG. To increase the
surface charge density, many methods have been adopted, including surface
modifications (e.g., physical and chemical), material modifications (e.g.,
dielectric constant and mechanical properties) or surface and bulk
modifications, and the layer-by-layer self-assembly approach has also been
adopted [29]. For example, Prasad et al. investigated the self-powered
triboelectric sensors (TES) through a straightforward poly-L-lysine (PLL)
post-surface-modification method. This approach aimed to enhance the positive
polarity of Nylon 11 electrospun sheets [31]. The Nylon 11 fabrication and
post-surface-modification using PLL is shown in Fig. 2(c). The as fabricated
TENG exhibited superior electrical output performance (such as, output
voltage~270 V, short circuit current~7.2 μA, and power density~2 W·m−2) under
8.5 N imparting force (Figs. 2d and 2e). Ghosh et al. suggested modifying
materials by creating a polyurethane polymer composite film infused with
ferroelectric barium-titanate-coupled (BTO-coupled) 2D MXene (Ti3C2Tx)
nanosheets [32]. MXene enhances the dielectric constant, while coupling with the
ferroelectricity of BTO reduces dielectric loss, improving the nanogenerator’s
output performance. The fabricated device uses quantum-mechanical calculations
to convert biomechanical energy into electricity, producing 260 V open-circuit
voltage, 160 mA·m−2 short-circuit current, and 6.65 W·m−2 power output, ideal
for charging various consumer electronics. Fig. 2(f) illustrates the microporous
hierarchical composite TENG, the dielectric permittivity of TPU and its various
composite films, and the output voltage of TPU and its composite-based TENGs
respectively. Interlayer engineering is a promising method for enhancing
triboelectric performance, in addition to surface and bulk modifications. Feng
et al. found that using a polyimide (PI) layer as a charge storage layer between
a PVDF tribo-material and a Cu electrode enhanced the triboelectric performance
significantly [33]. The PI layer stored negative charges, leading to a 9-fold
improvement in triboelectric output compared to a PVDF monolayer-based TENG. The
TENG with a PI transition layer reaches a peak output voltage of 1,010 V and a
short-circuit current of 65 μA. Salauddin et al. developed a composite material
called LC-MXene/ZiF-67 with a silicone friction layer [34]. The LC-MXene/ZiF-67
intermediate layer has abundant charge trapping sites and a porous structure,
leading to improved charge trapping properties. The voltage and current
densities of CM-TENG are 13.4 and 14.5 times higher than a single layer. The
schematic illustration of the fabrication process of LC-MXene/ZiF-67 is shown in
Fig. 2(g). The as prepared CM-TENG shown superior power density of 65W·m−2 under
a matching load impedance of 1.3 MΩ as shown in Fig. 2(h).


2.3 PYROELECTRIC ENERGY HARVESTERS

2.3.1 MECHANISM OF PYROELECTRIC EFFECTS

In addition to environmental mechanical energy harvesters, pyroelectric
nanogenerators (PyNGs) convert environmental waste heat into electrical energy
through pyroelectric effects [35]. PyNG technology integrated into wearable
electronics can efficiently harness wasted heat from the environment. It can
also be integrated into masks, which have become essential due to the Covid-19
pandemic, a global health crisis. Numerous research studies have been conducted
to refine the design of PyNGs using pyroelectric materials [3,4,35–38].
Pyroelectric materials display inherent spontaneous polarization (Ps) even in
the absence of an electric field. The pyroelectric effect is observed when Ps
undergoes temporary changes in response to variations in temperature within the
material [39]. When the temperature increases, the surface charges bound to the
surface decrease due to thermal vibration, leading to a decrease in Ps. This
generates an electrical potential across the pyroelectric material if it is
under an open circuit condition. In the case of a short circuit condition,
electrical current flows through the external circuit. The equation governing
the pyroelectric current output is given as Eq. (1).

(1)

i=dQdt=pAdTdt
Here, “i” represents current, “Q” signifies pyroelectric charge, “p” is the
pyroelectric coefficient, “A” is the surface area of pyroelectric materials, and
“t” signifies time. Various methods are used to accurately measure the
pyroelectric coefficient (p), including static and dynamic techniques [40].
Static methods include charge compensation, hysteresis measurement, and X-ray
techniques. Dynamic methods involve temperature ramping and optical techniques.
The practical assessment of the pyroelectric coefficient of PyNG can be attained
by measuring the output current and relevant physical parameters. This
coefficient is estimated using the following Eq. (2):

(2)

p=iA.dT/dt
Fig. 3(a) depicts the energy harvesting system utilizing the pyroelectric
effect. The working mechanism of PyNG is detailed in Figs. 3(b)–3(d), based on
temperature-induced changes in spontaneous polarization (Ps) [37,41]. Polymers
with crystalline structures, where molecular chains align, can exhibit (Ps) due
to the alignment of polarized covalent bonds. Similarly, ceramics with ionic
bonding can also show Ps due to polarization within their crystal lattice [42].
Ideally, internal dipoles should align in one direction, but wiggling atoms
disrupt this. When polarization and wiggling angle (θ) remain constant at a
constant temperature, no current flows through the external circuit (Fig. 3(b)).
As the temperature rises (dT/dt > 0), thermal energy causes dipole alignment to
change, with the dipoles wiggling around their respective pole axes (Fig. 3(c)).
Higher temperatures result in larger wiggling angles for diverse polarizations,
leading to a decrease in the intensity of Ps. The decrease in induced surface
charges on pyroelectric material is a result of the rising temperature,
prompting released surface charges to traverse through the external circuit.
Upon returning to the initial state, the dipole alignment reverts, inducing
reverse current flows in the external circuit. Conversely, a temperature
decrease (dT/dt < 0) leads to internal dipoles with reduced angles (θ2 < θ),
owing to diminished thermal energy. This, in turn, amplifies the intensity of Ps
significantly, as illustrated in Fig. 3(d). The surface charges on pyroelectric
material increase when temperature changes, causing them to flow through the
external circuit. When the temperature returns to normal, the dipole alignment
of the material is restored, leading to a decrease in surface charges and a
reverse current flow through the external circuit. This process generates
electrical energy through the pyroelectric effect. Fig. 3(e) shows the
temperature-dependent Ps change in pyroelectric materials [43].

FIG. 3

(a) Pyroelectric energy harvesting system schematic. Schematic diagrams showing
the working principle of the PyNG under different temperature conditions. (b)
constant temperature, (c) heated, and (d) cooled conditions [37] (Adapted from
Ref. 37 with permission), (e) A graph depicting the temperature dependence of
internal spontaneous polarization and pyroelectric coefficient of the material
[37] (Adapted from Ref. 37 with permission). (f) Schematic diagram showing the
structure of a single PZT microwire PyNG [51] (Adapted from Ref. 51 with
permission), (g) The optical image when a self-powered sensor was attached on a
metallic body, (h) the optical image of a LCD screen in normal condition, (i)
optical image when the sensor is in contact with a hot-plate, (j) image of LCD
screen, which is connected to the PyNG in panel h [51] (Adapted from Ref. 51
with permission). (k) Schematic of the experimental setup for characterizing
PyNG, (l) schematic showing the multilayered Au/LDH/Al device structure, (m)
short circuit output current of ZnAl-LDH, and MgAl-LDH PyNGs with temperature
change [59] (Adapted from Ref. 59 with permission)



2.3.2 PYROELECTRIC MATERIALS AND ITS PROGRESS

Pyroelectric materials have shown great potential in sensors, energy harvesting
devices, and even in medical applications. The ability of pyroelectric materials
to convert temperature changes into electrical signals makes them valuable in a
wide range of technologies. Researchers continue to explore new ways to enhance
the performance and versatility of pyroelectric materials for future
applications [35,43,44]. Selection of pyroelectric materials from a wide variety
of materials, including both ferroelectric and non-ferroelectric materials, is a
significant area of research. All ferroelectric materials exhibit pyroelectric
properties, and all pyroelectric materials demonstrate piezoelectric behavior,
but the reverse is not necessarily the case [43,45,46]. It can be observed that
triglycine sulphide (TGS) is extremely potential materials for pyroelectric
energy harvesters. TGS, with the chemical formula (NH2CH2COOH)3H2SO4, consists
of crystals derived from the glycine group (NH2CH2COOH) that are polar and
demonstrate exceptionally high pyroelectric figures of merit (FOM) [42,47]. TGS
(Triglycine Sulfate) faces limited interest for energy harvesting applications
primarily because of its low Curie temperature of 49°C, water solubility,
hygroscopic nature, and relatively low mechanical strength [48]. Lead magnesium
niobate-lead titanate (PMN-PT) and lead zirconate titanate (PZT) are popular
ceramics known for their simple fabrication process and excellent piezoelectric
properties. These materials have garnered attention for their potential in
pyroelectric energy harvesting applications [49–51]. Yang et al. showcased the
initial use of a PyNG as a self-powered sensor to detect temperature variations
with a single PZT micro/nanowire. The sensor’s response time and reset time were
approximately 0.9 and 3 seconds, respectively [51]. The schematic of a single
PZT microwire PyNG is shown in Fig. 3(f). Figs. 3(g)–3(j) show the self-power
sensor demonstrations. The sensor is attached to a metallic body as shown in
Fig. 3(g) with an LCD screen in Fig. 3(h). When there is no change in
temperature in the sensor, the LCD is off, whereas the LCD is on and showing a
number on the screen as shown in Fig. 3(j) while the sensor is under heat
treatment at a temperature of 473 K as shown in Fig. 3(j). Lead-free
ferroelectric materials such as bismuth sodium titanate-barium titanate (BNT-BT)
and Mn:BNT-BT offer high pyroelectric coefficients and figure of merit, making
them appealing alternatives to lead-based materials [52,53]. Additionally,
Ba0.65Sr0.35TiO3 (BST) thin films are commonly used to enhance pyroelectric
energy harvesting [54]. Besides these, lithium tantalate (LiTaO3, LTO), lithium
niobate (LiNbO3, LNO), and potassium sodium niobate-based materials have gained
popularity over lead-based pyroelectric materials due to their low dielectric
loss [43], high Curie temperature [55], and excellent pyroelectric coefficient
[56], respectively. Besides ferroelectric materials, certain non-ferroelectric
materials are also crucial in the design of a PyNG. These materials include
wurtzite-based compounds like AlN, GaN, CdS, and ZnO [43]. However, their
pyroelectric coefficients are lower than those of ferroelectric materials, but
they have higher thermal conductivities [43].
The materials mentioned above are usually ceramic-like, resulting in high
density, stiffness, and brittleness. If mechanical flexibility and toughness are
desired, a polymeric pyroelectric material like polyvinylidene fluoride (PVDF)
and its copolymers (e.g. polyvinylidene-difluoride trifluoro-ethane; P(VDFTrFE))
can be used for pyroelectric energy harvesting [3,9,57,58]. Mahanty et al.
proposed an all-fiber pyro- and piezo-electric nanogenerator (PPNG) that was
demonstrated using MWCNT-doped PVDF composite nanofiber [3]. The PVDF-MWCNT
composite nanofiber possesses fifteenth times higher pyroelectric coefficient
(~60 nC·m−2·K−1) compare to that of pure PVDF nanofibers (~4 nC·m−2·K−1). In
another study, Sultana et al. proposed a composite electrospun nanofiber made of
methylammonium lead iodide (CH3NH3PbI3) and PVDF to harvest thermal energy [57].
The prepared PyNG showed a fast response time of 1.14 s, a reset time of 1.25 s,
a voltage of 41.78 mV, and a pyroelectric coefficient of approximately 44 pC
·m−2·K−1. Recently, there has been a growing demand for layered double hydroxide
(LDH)-based pyroelectric nanogenerators (PyNGs) due to their unique properties,
including high gradients of composition and energy levels, size effects, and the
ease of fabrication and tuning [59]. Prestopino et al. demonstrated experiments
where they fabricated several LDH-based PyNGs. Remarkably, they observed that
without the need for poling treatment, the pyroelectric coefficient can range
from positive, up to 150 μC·m−2·K−1 for PyNGs made of ZnAl-LDH, to negative,
down to −160 μC·m−2·K−1 for those composed of MgAl-LDH [59].


2.4 MAGNETOELECTRIC ENERGY HARVESTERS

2.4.1 MECHANISM OF MAGNETOELECTRIC EFFECTS

In addition to mechanical and heat energy converters, magnetoelectric (ME)
energy harvesters stand out as a notable energy harvesting technology. These
devices convert magnetic energy into electrical energy by leveraging mechanical
strain/stress-mediated magnetoelectric (ME) coupling effect. Multiferroic
composites, which exhibit both ferromagnetism and ferroelectricity, have
attracted considerable interest for their magnetoelectric (ME) couplings, making
them promising candidates for energy harvesting applications. The
magnetoelectric (ME) effect emerges from the coupling between magnetic and polar
sublattices within single-phase materials. It is uncommon to find long-range
ordered magnetic moments and electric dipoles coexisting in the same phase,
leading to the discovery of only a few single-phase compounds exhibiting the ME
effect. Obtaining significant magnetoelectric (ME) coupling in single-phase
compounds at room temperature has proven to be challenging due to the concurrent
transitions from ferroelectric to paraelectric states and from
ferro/ferri/antiferromagnetic to paramagnetic states [60–62]. However, these
constraints can be surpassed through the integration of ferroelectric and
ferromagnetic materials within ME composites, capitalizing on the remarkable
properties inherent in these phases. Research has shown that multiphase ME
composites can achieve a significantly improved ME response [63] compared to
single-phase ME materials [64] at ambient temperature. Layered ME composites,
which combine piezoelectric and magnetostrictive materials in an elastic
structure, have been extensively researched due to their simple manufacturing
process and adaptable design. Various factors such as strain, spin, or charge
carrier exchange among the constituent phases are responsible for the interplay
of magneto-electricity within the composite materials. While the mechanism of
strain-mediated coupling is comprehensively understood, the exploration of the
other two mechanisms remains ongoing [10,65,66]. In composites, strain-mediated
coupling occurs due to the elastic interaction between piezoelectric and
magnetostrictive components, as shown in Fig. 4(a) [63,67]. The detailed working
mechanism is illustrated below. The ME effect encompasses the process wherein
the imposition of a magnetic field induces mechanical strain within the magnetic
layer, a phenomenon referred to as magnetostriction. Subsequently, this strain
propagates to the piezoelectric layer, obtaining an electric displacement via
the piezoelectric effect, as illustrated in Fig. 4(a). The ME response is
quantified using the ME voltage coefficient αME=δEacδHac, which indicates the
ratio of induced Eac to applied Hac (expressed in V·cm−1·Oe−1). This coefficient
measures the efficiency of energy conversion between the applied Hac and induced
Eac under a bias field Hdc. Fig. 4(b) illustrates the magneto-elasto-electric
coupling process in the (1-1) composite, along with its corresponding
longitudinal magnetization and transverse polarization (L-T) mode ME-coupling
equivalent-circuit expression [63].

FIG. 4

(a) Schematic representation of the direct magnetoelectric effect in a 2–2
configuration ferroelectric (FE)/ferromagnetic (FM) composite system (the
numbers 2–2 refer to the connectivity of the phases in free space). Here the
applied magnetic field (Hac/Hdc) generates strain (ɛ) in the magnetic layer via
the magnetostriction effect and this strain is transferred to the piezoelectric
layer resulting in electric displacement or dielectric polarization (P) through
the piezoelectric effect [67] (Adapted from Ref. 67 with permission), (b)
magnetoelastoelectric coupling process and its L-T mode equivalent-circuit
expression in which the magnetostriction and piezoelectric effects in the
magnetic and piezoelectric phases, and elastic strain coupling between the two
phases are clearly illustrated, [63] (Adapted from Ref. 63 with permission). (c)
Schematic of the experimental setup, [81] (Adapted from Ref. 81 with
permission). (d) Schematic and digital photograph of the as-fabricated device
along with the harvesting process (pink circles indicate the positions of the
MENG device). (e) Harvested voltage output from the household device. (f)
Cole−Cole plot of the impedance. Upper inset: Frequency-dependent impedance plot
of the PS10-based nanogenerator. Lower inset: RT dc conductivity plots of all
film samples as a function of the volume percentage of the filler NPs (the
dotted red line corresponds the onset of the percolation threshold) [81]
(Adapted from Ref. 81 with permission). (g) Schematic representation of the
magneto-mechano-electric (MME) mechanism of TrFE/NFO 0–3 nanocomposites to
harvest stray magnetic field from an electric power cable [10] (Adapted from
Ref. 10 with permission). (h) (i) Schematic of the device architecture and (ii)
magnetic field energy harvesting using MMENG, (iii) digital photograph of the
original device (with the TrFE/NFO1 composite), which is (iv) flexible and (v)
rollable; (i) harvested output voltages from TrFE/NFO-based MMENGs; (j) voltage
output from the flat TrFE/NFO2-based MMENG at several distances from the power
cable of electric kettle; (k) peak output voltage and evaluated power density as
a function of load resistance [10] (Adapted from Ref. 10 with permission)



2.4.2 MAGNETOELECTRIC MATERIALS AND ITS PROGRESS

In the past decade, there has been significant research on magnetoelectric (ME)
composites [9,68]. The ME effect involves converting magnetic energy into
electric energy and vice versa. This transducer responds to changes in electric
polarization due to a magnetic field (direct ME effect) or changes in
magnetization due to an electric field (converse ME effect). These transducers
consist of magnetostrictive and piezoelectric layers, which can function as
sensors, actuators, or energy harvesters. These devices efficiently transform AC
magnetic fields into vibration and electric charge, rendering them ideal for
harvesting energy from diverse sources. This includes but is not limited to
mobile base stations, Wi-Fi routers, satellite communications, radio and TV
transmitters, and power distribution lines [69]. According to Ampere’s circuital
law, current-carrying conductors connected to house hold appliances can generate
a low-amplitude magnetic field with a low frequency. The ME effect has indeed
been observed in single-phase materials like Cr2O3 and BiFeO3, though typically
it is rather weak at room temperature [70]. Van Suchtelen [71] demonstrated that
piezoelectric-piezomagnetic composites could manifest a more dominant ME effect.
The constitutive relations for these composites are typically expressed using
the following equations [72],

(3)

ɛɛ=sσ+dE+d′H

(4)

ɛD=dσ+ɛE+βH

(5)

B=d′σ+βE+μH
where B, and H are the magnetic induction and magnetic field intensity, σ, μ,
and β are the elastic compliance, magnetoelastic constant, magnetic
permeability, and ME susceptibility, respectively.
Tremendous research has been conducted in the field of magnetoelectric energy
scavenging/harvesting technology using a variety of materials and composites
[10,73–84]. Wu et al. developed a rotational parameter sensor using a FeNi/PZT
magnetostrictive/piezoelectric laminated composite (MPLC) and a multi-pole
magnetic ring [85]. Tang et al. developed a self-biased magnetoelectric (ME)
charge coupling within a two-phase laminate stack termed Ni/PZT. This stack
incorporates Nickel foils and a Pb (Zr,Ti)O3 (PZT) plate boasting high
capacitance [74]. Experimental findings reveal that the Ni/PZT-stack with n =
0.4 showcases a remarkable zero-biased resonant ME charge coefficient (αQ,r) of
47.52 nC· Oe−1, notably surpassing the values reported for other ME laminates in
prior research. Additionally, Ghosh et al. developed an increased
magneto-electric (ME) effect at room temperature (RT) and above in a
nanocomposite of LaYFe2O6/P(VDF-HFP) [81]. At room temperature, this
nanocomposite exhibits a first-order ME coupling coefficient of approximately
2.92 mV·cm−1·Oe−1 and a second-order ME coupling coefficient of around 0.051
μV·cm−1·Oe−2. The experimental setup is illustrated in Fig. 4(c). Fig. 4(d)
shows the schematic and digital photograph of the fabricated device, as well as
the harvesting process. The harvested output voltage from the household device
and the Cole-Cole plot of the impedance are depicted in Figs. 4(e) and 4(f),
respectively. Recently, Ghosh et al. reported an enhanced ME effect in
spin-photon coupled single-phase La1-x SmxYFe2O6 (0 ≤ x ≤ 1) [84]. The
composition with x = 0.75 exhibited the most effective polarization and
magnetoelectric response. It demonstrated a first-order ME coupling coefficient
approximately 31% higher and a second-order ME coupling coefficient
approximately 1 order higher than the original x = 0 sample. The
spin-reorientation transition significantly impacts the magnetic and
magnetoelectric properties, making it a valuable tool for adjusting these
properties. With advancements in inorganic materials, polymer-based ME materials
have achieved similar levels of ME coefficients, and their usage as energy
harvesters is rising owing to their excellent flexibility, lightweight, and
biocompatibility [10,86,87]. To date, many research works have been carried out
using polymer-based materials to improve magnetoelectric energy harvesting
[10,73,77,88–90]. Kwon et al. showed a bilayer composite sample consisting of
Metglas and PVDF with epoxy bonding in their study [89]. DC and AC magnetic
fields were produced using a pair of Helmholtz coils. The fields were adjusted
from 0 to 3 kA·m−1 (~37.7 Oe), and the AC frequency was varied from 0 to 200 Hz.
The magnetic field intensity was monitored using a Hall sensor to control the
field level. Silva et al. proposed a three-layer
(piezoelectric+epoxy+magnetostrictive) (PVDF/epoxy/Vitrovac) ME structure [73].
Experimental results demonstrate that the magnetostrictive effect response
improves with the increase of the PVDF thickness. The highest response of 53
V·cm−1·Oe−1 was achieved with a 110 μm thick PVDF/M-Bond epoxy/Vitrovac
laminate. This excellent ME response makes it a prominent material for use in
sensors, actuators, memories, and energy harvesting devices. Additional research
by Martins et al. explored the dispersion of cobalt ferrite (CoFe2O4)
nanoparticles in a poly (vinylidene fluoride)-trifluoroethylene (P(VDF-TrFE))
matrix [79]. The study investigated the impact of nanoparticle dispersion on the
piezoelectric, magnetic, and magnetoelectric characteristics of the
nanocomposite. Two distinct dispersion techniques were employed in sample
preparation: ultrasound and citric acid nanoparticle surfactation. No
significant distinctions were found in the ferroelectric, piezoelectric,
magnetic, and magnetoelectric properties between samples fabricated with or
without surfactants, thereby streamlining the process for large-scale
production. Ghosh et al. introduced a versatile and flexible
magneto-mechano-electric nanogenerator (MMENG) that can be rolled up [10]. This
study showcased the fabrication of a fully rollable MMENG employing
P(VDF-TrFE)/nickel ferrite (NiFe2O4/NFO) 0–3-type magnetoelectric
nanocomposites. This device is designed for wireless Internet of Things (IoT)
sensors to detect and harness environmental magnetic noise even without a direct
current magnetic field. The working principles of MMENG with TrFE/NFO 0–3
nanocomposites is illustrated in Fig. 4(g). When subjected to an AC magnetic
field (Fig. 4(g-i)), the NFO nanoparticles in the MMENG undergo
magnetostriction, causing them to elongate or contract in sync with the magnetic
field frequency (Fig. 4(g-ii)). This strain is then transferred to the P
(VDF-TrFE) polymer chain through strong interfacial interactions, resulting in
stress application (Fig. 4(g-iii)) that generates electric charges due to
polarization alignment. Subsequently, the generated voltage is delivered across
an external electrical load via the direct piezoelectric effect
(mechano-electric coupling). The harvested electrical power can be utilized to
power consumer electronics (Fig. 4(g-iv)). Fig. 4(g-i) shows the fabricated
MMENG. Fig. 4(h-ii) illustrates the demonstration of magnetic field energy
harvesting from the stray magnetic field surrounding the power cable of an
electric kettle (1 kW, 50/60 Hz). Additionally, Fig. 4(h-iii) presents a digital
photograph of the MMENG. The MMENG is known for its flexibility, as depicted in
Fig. 4(h-iv), and rollability, as showcased in Fig. 4(h-v). Fig. 4(i)
illustrates the MMENG producing an AC voltage output with a sinusoidal waveform.
The MMENG using TrFE/NFO1 yielded a peak-to-peak output voltage (Vpp) of
approximately 640 mV, while TrFE/NFO2 produced a Vpp of around 1.4 V. Increasing
the distance between the MMENG and power cable from 0.5 to 2 mm resulted in a
decrease in voltage output from approximately 1.4 to 0.4 V as the AC magnetic
field strength decreased from 1.7 to 0.4 mT (Fig. 4(j)). The power output of the
MMENG was assessed by capturing peak output voltages across various external
load resistances (RL), ranging from 0.25 MΩ to 1 TΩ, during the boiling of water
in an electric kettle (Fig. 4(k)). The peak power density reached 0.05 μW·cm−3,
across RL~100MΩ.
Go to :



3 APPLICATIONS IN SELF-POWERED SENSOR SYSTEMS

Recent advancement in energy harvesting have gained momentum owing to the
growing demand for self-powered portable and wireless electronics, as well as
systems with extended lifespans, which have opened up a wide range of
applications. In this section, we showcase some applications of
self-/auto-powered wearable sensors, implantable medical devices, human machine
interactions, and wireless healthcare systems utilizing energy harvesters.
Significant advancements have been made in self-powered electronics through the
use of energy harvesters [10,29,91–94]. Meanwhile, the energy harvesting
outlooks for some of the potential applications in self-powered electronics will
be illustrated in this section. For instance, Kim et al. proposed a wireless
communication system for a healthcare system that utilized in vivo energy
harvesting with excellent output performance PMN-PZT PENG technology [91]. Fig.
5(a) shows the experimental setup for self-powered wireless data transmission
through in vivo energy harvesting. Energy generated by cardiac motions was
stored in a 22 μF capacitor via a full-wave bridge rectifier. The transmitting
part could operate wirelessly when connected to the charged capacitor. Data was
wirelessly transmitted to the receiver utilizing a communication protocol known
as Wireless Universal Serial Bus (WUSB). To visually confirm the data
transmission, instructions were sent to switch a light bulb on and off at a
distance of approximately 5 m. Gupta et al. demonstrated MXene-incorporated PVDF
composite nanofiber based PyNG for advanced breathing sensors and IR data
receivers with machine learning prediction [92]. To validate pyroelectric sensor
data for advanced applications, a machine learning algorithm was adopted on the
obtained data as shown in Fig. 5(b). The breathing response was captured using a
pyroelectric sensor in two scenarios: before and after exercise. The breathing
rate differed significantly between the two cases, with approximately 14 breaths
per minute before exercise and around 30 breaths per minute after exercise.
Additionally, the peaks in the breathing response varied between the two
conditions. These sensor data were utilized for machine learning applications to
differentiate between pre- and post-exercise breathing signals. Multiple data
sets were generated, preprocessed, and split into training and test data for the
development of machine learning algorithms. Four algorithms (Logistic
Regression, K-Nearest Neighbors, Support Vector Machine, and Random Forest) were
employed to train the models. The results indicated that K-Nearest Neighbors and
Random Forest were the most effective in identifying breathing patterns based on
the input features. Further, Roy et al. proposed a self-powered wearable
pressure and pyroelectric breathing sensor based on graphene oxide (GO)
interfaced with PVDF nanofibers [58]. The performance of this breathing sensor
was enhanced by incorporating conductive GO nanofillers into the PVDF
nanofibers. During the demonstration, the PyNG was mounted on an N95 mask worn
on the human face. The temperature of the airflow during respiration was
detected by the PyNG as voltage or current fluctuations. Thus, the breathing
rate and pattern, vital signs of human health, especially regarding the
cardiorespiratory system, were monitored. In addition, Xue et al. proposed a
wearable PyNG as a self-powered breathing sensor using PVDF thin film [93]. Due
to temperature fluctuations from human breathing at 5°C, the PyNG generates
output signals with an open-circuit voltage of 42 V and a short-circuit current
of 2.5 μA. The fabricated PyNG was attached inside a mask, mounted on the face,
and driven by human breathing. The temperature sensor fixed on the PyNG recorded
the real-time temperature during the respiratory process. The output electrical
signals of the PyNG directly record the respiratory rate of the human being.
Therefore, the prepared PyNG can be used as a breathing sensor for human health
monitoring. Ghosh et al. engineered a flexible and rollable MMENG using nickel
ferrite (NiFe2O4) nanoparticles alongside a piezoelectric PVDF polymer-based
wireless IoT sensor. This device captures and utilizes environmental magnetic
noise without the need for a direct current magnetic field [10]. The MMENG was
showcased as a wireless IoT sensor within a position monitoring system,
illustrated in Fig. 5(c). The signal generated by MMENG (using TrFE/NFO2) from
an electric kettle’s power cable during water boiling was wirelessly transmitted
to a smartphone via an Arduino MCU-based platform. The wireless data
transmission circuit schematic is depicted in Fig. 5(d), alongside real-time
images showcasing the Arduino MCU board connected to a Bluetooth module (HC-05)
and an Android smartphone displaying the signals. The measured wireless signal
output is illustrated in Figs. 5(e) and 5(f). This demonstrates the potential of
the MMENG as a position monitoring IoT sensor. When a user approaches the
Bluetooth transmitter with a smart device, the signal amplitude increases, and
decreases when the user moves away, confirming the MMENG’s ability to harvest
magnetic fields for IoT applications. Maharjan et al. developed a highly
sensitive self-powered triboelectric flex sensor (STFS), capable of effectively
detecting finger bending motion and monitoring hand gestures with high precision
[94]. The flex sensor can detect pressure in a wide range from 0.2 to 500 kPa.
It has been successfully used in a real-time sign language interpretation system
that detects finger gestures and converts them into voice and text using a
smartphone application. Sensors are attached to the human finger joints, and
their raw output voltage signals are filtered and processed in the signal
processor unit. Each alphabet letter in American Sign Language (ASL) corresponds
to a specific hand gesture, generating unique sensor output voltages. The
processed signals are converted from analog to digital using an ADC and
transmitted to a microcontroller, which wirelessly sends the data to a
smartphone via Bluetooth. A custom Android app displays the data from the smart
glove in text and voice formats. The smart glove incorporates five STFS, a
microcontroller unit equipped with Bluetooth Low Energy (BLE) capability, and a
smartphone application. Due to its easy fabrication process, exceptional sensing
capabilities, and robust mechanical durability, the STFS emerges as a
cost-effective solution viable for mass production. It is ideal for assisting
individuals with speech disabilities in interpreting sign language. Furthermore,
Park et al. demonstrated frequency - selective acoustic and haptic smart skin
for dual-mode dynamic/static human-machine interface system [95]. They
demonstrated that their dual-mode sensor, featuring linear response and
frequency selectivity across a broad range of dynamic pressures, effectively
differentiates surface textures and controls an avatar robot using both acoustic
and mechanical inputs without interference from ambient noise. They fabricated a
smart glove by integrating triboelectric sensors (TES) onto the tips and joints
of the fingers to detect surface texture and finger movements, respectively
(Fig. 5(g)). To evaluate the texture perception capability, the proposed TES was
placed on 3D-printed target surfaces with regular line patterns and scanned
using a homebuilt system that controlled the scanning speed and micro-unit
displacement. They collected large quantities of time-dependent current data
corresponding to different surface textures (e.g., polyester, cotton, nylon,
silk, glass, paper, and sandpaper) for ANN training and transformed the data
into FFT spectra to extract frequency features. The resulting classification
matrix indicated a high positive predictive value of 92.7% for the proposed
training model, providing a simple platform for robotics requiring sophisticated
tasks (Fig. 5(h)) [94]. In addition to the single-layer PENG, multilayer PENGs
have also been demonstrated to improve device performance further [6]. Mahanty
et al. proposed a multilayered PENG for real-time applications as self-powered
wearable sensors on different parts of the human body to measure biomedical
activity [6]. They also showcased a wireless remote healthcare monitoring system
(Figs. 5(i) and 5(j)). The circuit diagram and schematic of the IoT-based remote
health monitoring system are presented in Fig. 5(i), emphasizing key components
such as a single-chip ESP8266A Wi-Fi module and a PC/smartphone running the
Blynk app. Furthermore, the real-time practical circuit is illustrated in Fig.
5(j-i), demonstrating the output response of the multilayered PENG under gentle
finger touch. This response is displayed on a smartphone screen (Fig. 5(j-ii)
via the local server for the IoT-based remote healthcare monitoring system.
Recently, Wang et al. demonstrated non-contact sensing technology aimed at
seamless data acquisition and intelligent perception, which brings innovative
interactive experiences to wearable human-machine interaction [96]. This study
introduces triboelectric nanopaper prepared through a phase-directed assembly
strategy, showcasing both low charge transfer mobility (1,618 cm2·V−1·s−1) and
remarkable stability at high temperatures. The noncontact sensing based on
triboelectric nanopaper is shown in Fig. 5(k-p). The schematic diagram of the
noncontact sensors for wearable motion monitoring and spatial position
perception is depicted in Fig. 5(k). The sensor was attached on the volunteer’s
arms and inner sides of the shoes (Fig. 5(k)). By analyzing the peak pattern and
numerical characteristics of the open-circuit voltage signal, the sensor can
distinguish step frequency, foot distance, and movement speed (Fig. 5(l)),
enabling monitoring of motion states such as stationary, walking, running, and
jumping (Fig. 5(m)). The system uses wearable non-contact sensors to capture
motion signals (e.g., walking, running) and transmits them wirelessly via
Bluetooth to a mobile app, enabling real-time movement visualization (Figs. 5(n)
and 5(o)). When the distance to the instrument fell below 30 cm, the non-contact
sensor’s signal exceeded 4 V, warning workers of harmful temperatures and
preventing thermal injuries (Fig. 5(p)). Thus, the triboelectric nanopaper-based
sensor also enables spatial positioning, movement detection, and functions
effectively in high-temperature environments. The examples mentioned here are
only part of the relevant technologies, and the development of self-powered
advanced sensor technologies for better lives is still growing remarkably from
wearable applications to industrial applications.

FIG. 5

(a) Experimental schematics of the self-powered wireless data transmission using
biomechanical energy. The flexible energy harvester attached to porcine heart
generates electricity from cardiac contraction and relaxation motions. The
energy derived from cardiac motion was stored in the capacitor, and then the
appointed data was transmitted to receiver wirelessly. A light bulb was
repeatedly turned on and off as the data was used for the instruction of
switching on and off the light bulb to visually verify data transmission [91]
(Adapted from Ref. 91 with permission). (b) Schematics for the ML algorithm [92]
(Adapted from Ref. 92 with permission). (c) Conceptual schematics of the
MMENG-based position monitoring system, (d) schematic diagram of the MMENG-based
wireless signal processing unit, (e) digital photograph of the wireless
transmission of the harvested signal by MMENG from the electric kettle power
cable, and (f) captured image of the transmitted signal to the smart phone [10]
(Adapted from Ref. 10 with permission). (g) Schematic of the smart glove for HMI
applications, enabling the texture perception and remote control of robotic
hands. The inset shows each pixel composition with sensor, encapsulation layer,
and adhesive tape. (h) ANN to recognize different textures and surface roughness
[94] (Adapted from Ref. 94 with permission). (i) Circuit diagram of the IoT
based experimental setup using multilayered PENG [6] (Adapted from Ref. 6 with
permission). (j), (i) Digital image ofthe practical circuit with (ii) mobile
screen showing the received sensor data wirelessly using the Blynk app [6]
(Adapted from Ref. 6 with permission). Noncontact sensing based on triboelectric
nanopaper. (k) Schematic diagram of the noncontact sensors for wearable motion
monitoring and spatial position perception [95] (Adapted from Ref. 95 with
permission) (l) Foot movement tracking detection [95] (Adapted from Ref. 95 with
permission). (m) Different state of motion monitoring [95] (Adapted from Ref. 95
with permission). (n) Schematic diagram of a noncontact temperature warning
system [95] (Adapted from Ref. 95 with permission). (o) Noncontact wireless
temperature warning system for motion tracking detection, [95] (Adapted from
Ref. 95 with permission). (p) Hazardous temperature monitoring [96] (Adapted
from Ref. 96 with permission)



Go to :



4 CONCLUSIONS AND FUTURE PERSPECTIVES

This paper provides a concise review of recent advancements in piezo-, tribo-,
pyro-, and magneto-electric energy harvesters and their applications in
self-powered electronics. Self-powered sensor systems are poised for significant
growth in the electronics sector, with potential applications ranging from
monitoring human health to environmental conditions in the era of the Internet
of Things (IoT). We highlight cutting-edge developments in energy harvesters
concerning their materials, fabrication techniques, applications, and
development processes. These advancements indicate substantial progress across
various domains, suggesting imminent technological breakthroughs.
Nanogenerator-based self-powered sensor systems have shown promising
developments; however, several challenges hinder their widespread commercial
adoption:

 * 1) Efficiency: Enhancing the energy conversion efficiency of these devices.

 * 2) Reliability and Durability: Ensuring consistent performance and long-term
   usability.

 * 3) Compatibility and Interfacing: Integrating seamlessly with existing
   electronic systems.

 * 4) Miniaturization and Integration: Reducing size while maintaining
   functionality.

 * 5) Cost-effectiveness: Making the devices economically viable for mass
   production.

 * 6) Wearability: Designing comfortable and practical wearables

Addressing these challenges requires a collaborative approach in
interdisciplinary research, merging insights from materials science, mechanical
engineering, electronics, and energy harvesting technologies. As we advance in
these areas, nanogenerator-based sensor systems are anticipated to increasingly
influence the development of sensing and IoT technologies. In conclusion,
surmounting the obstacles in developing self-powered wearable devices with
diverse energy harvesting and sensing capabilities could unlock new
opportunities and insights for the future of these technologies.
Go to :



ACKNOWLEDGEMENTS

This work was supported by the National Research Foundation of Korea (NRF) grant
funded by the Korean government (MSIT) (RS-2022-00165505 and 2020R1A5A8018367).
Go to :



DECLARATIONS

Declaration of Competing Interest

The authors declare no competing financial interest.

Go to :






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Go to :



BIOGRAPHY


Dr. Biswajit Mahanty received his Bachelor’s degree in Electronics from Burdwan
University, West Bengal, India, and a Master’s degree in Electronic Science from
Jadavpur University, West Bengal, India. He completed his M.Tech in Software
Engineering from MAKAUT, Kolkata, India, and received his Ph.D. in Physics from
Jadavpur University, West Bengal, India. Currently, he is working as a
post-doctoral researcher at the MEMS and Nanotechnology Laboratory, School of
Mechanical Engineering, Chonnam National University, Republic of Korea. His
research interests include the design and development of Piezo-, Tribo-,
Pyro-electric, Tribo-voltaic Nanogenerators, Self-powered Flexible Sensors,
Supercapacitors, and Wireless energy transfers.
Go to :



BIOGRAPHY


Prof. Dong-Weon Lee received his Ph.D. degrees in Mechatronics Engineering from
Tohoku University, Sendai, Japan in 2001. He has been a Professor of Mechanical
Engineering at Chonnam National University (CNU), Republic of Korea since 2004.
Previously, he was with the IBM Zurich Research Laboratory in Switzerland,
working mainly on microcantilever devices for chemical AFM applications. At CNU,
his research interests include smart cantilever devices, miniaturized energy
harvesters & flexible supercapacitors, smart structures & materials, and
nanoscale transducers. He is a member of the technical program committee of IEEE
MEMS conference, IEEE Sensors Conference, Transducers, and Microprocesses and
Nanotechnology Conference etc.
Go to :

Abstract
1 Introduction
2 Classification of Energy Harvesters
3 Applications in Self-powered Sensor Systems
4 Conclusions and Future Perspectives
Acknowledgements
Declarations
References
Biography
Biography

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