Advanced Materials Technologies,
Journal Year:
2024,
Volume and Issue:
9(5)
Published: Jan. 20, 2024
Abstract
With
the
rapid
development
of
industry
and
information
technology,
rough
challenges
have
been
put
forward
for
traditional
sensor
technology
to
meet
increasingly
complex
diverse
application
demands
in
actual
production
daily
life,
widely
distributed
network
also
faces
power
supply
maintenance
problems.
As
a
new
energy
conversion
triboelectric
nanogenerators
(TENGs)
based
on
triboelectrification
electrostatic
induction
effect
can
respond
weak
mechanical
stimuli
surrounding
environment
generate
corresponding
electrical
signals
realize
sensing
function
without
external
supply.
In
addition,
TENGs
advantages
wide
selection
fabrication
materials,
flexible
fundamental
modes,
which
be
customized
different
applications
functions.
recent
years,
sensors
developed
rapidly,
researchers
variable
scenarios.
this
paper,
sensos
classified
into
categories,
advanced
strategy
prepare
materials
used
manufacturing
integration
introduced.
This
work
summarizes
main
current
challenges,
so
as
provide
guidance
instructions
future
sensors.
Small Methods,
Journal Year:
2022,
Volume and Issue:
6(10)
Published: Sept. 8, 2022
Wireless
wearable
sweat
analysis
devices
can
monitor
biomarkers
at
the
molecular
level
continuously
and
in
situ,
which
is
highly
desired
for
personalized
health
care.
The
miniaturization,
integration,
wireless
operation
of
sensors
improve
comfort
convenience
while
also
bringing
forward
new
challenges
power
supply
technology.
Herein,
a
self-powered
system
(SWSAS)
designed
that
effectively
converts
mechanical
energy
human
motion
into
electricity
through
hybrid
nanogenerator
modules
(HNGMs).
HNGM
shows
stable
output
characteristics
low
frequency
with
current
15
mA
voltage
60
V.
Through
real-time
on-body
powered
by
HNGM,
SWSAS
demonstrated
to
selectively
(Na+
K+
)
wirelessly
transmit
sensing
data
user
interface
via
Bluetooth.
Advanced Energy Materials,
Journal Year:
2022,
Volume and Issue:
12(43)
Published: Sept. 13, 2022
Abstract
Natural
wind
energy
harvesting
enables
a
far‐reaching
and
sustainable
solution
to
supply
pervasive
sensors
in
the
Internet
of
Things
(IoT).
Electromagnetic
generators
(EMGs)
struggle
harvest
from
breezes,
which
causes
regrettable
wastage.
Herein,
triboelectric‐electromagnetic
hybridized
nanogenerator
(TEHG)
is
designed
with
dual‐rotor
structure
consolidate
band
for
high
efficiency
triboelectric
nanogenerators
(TENGs)
breeze
EMG
speeds.
The
TEHG
performs
an
efficient
collection
(41.05
W
m
−3
)
smooth
output
speed
2−16
s
−1
,
attributed
environmental
self‐adaptive
cooperation
between
TENGs
EMGs.
TENG
power
contribution
more
than
70%
at
low
speeds
(<5
).
Moreover,
dual‐channel
management
topology
(DcPMT)
established
co‐manage
outputs
two
modules
TEHG.
By
virtue
DcPMT
hierarchically
combining
isolated
storage
undervoltagelockout
strategy,
steadily
supplies
standardized
3.3
V
voltage
commercial
electronics.
Furthermore,
TEHG‐based
self‐powered
system
demonstrated
driving
monitor
meteorological
information.
advantageous
broad‐band
high‐efficiency
harvesting,
thus
exhibiting
great
potential
elevating
self‐adaptability
stability
margin
IoT.
Advanced Energy Materials,
Journal Year:
2023,
Volume and Issue:
13(31)
Published: June 29, 2023
Abstract
In
the
age
of
artificial
intelligence
things
(AIoT),
wearable
devices
have
been
extensively
developed
for
smart
healthcare.
This
paper
proposes
a
self‐powered
and
self‐sensing
lower‐limb
system
(SS‐LS)
with
negative
energy
harvesting
motion
capture
The
SS‐LS
achieves
self‐sustainability
via
half‐wave
electromagnetic
generator
(HW‐EMG)
that
recovers
work
from
walking
low
cost
harvesting.
Additionally,
function
is
achieved
by
three‐channel
triboelectric
nanogenerator
(TC‐TENG)
based
on
binary
code,
which
can
accurately
detect
angle
direction
knee
joint
rotation.
bench
test
experiment
indicates
HW‐EMG
has
an
average
output
power
11.2
mW,
sufficient
to
wireless
sensor.
voltage
signal
TC‐TENG
fits
well
signal,
precisely
Furthermore,
demonstrates
identification
accuracy
99.68%
detection
99.96%
LSTM
deep
learning
model.
Demonstrations
Parkinson's
disease
fall
monitoring
three
training
modes
(sit‐and‐stand,
balance,
training)
are
also
performed,
exhibit
outstanding
sensing
capabilities.
highly
promising
in
sports
rehabilitation
medicine
contribute
development
Advanced Science,
Journal Year:
2024,
Volume and Issue:
11(22)
Published: April 1, 2024
Abstract
Precise
agriculture
based
on
intelligent
plays
a
significant
role
in
sustainable
development.
The
agricultural
Internet
of
Things
(IoTs)
is
crucial
foundation
for
agriculture.
However,
the
development
IoTs
has
led
to
exponential
growth
various
sensors,
posing
major
challenge
achieving
long‐term
stable
power
supply
these
distributed
sensors.
Introducing
self‐powered
active
biochemical
sensor
can
help,
but
current
sensors
have
poor
sensitivity
and
specificity
making
this
application
challenging.
To
overcome
limitation,
triboelectric
nanogenerator
(TENG)‐based
urea
which
demonstrates
high
developed.
This
device
achieves
signal
enhancement
by
introducing
volume
effect
enhance
utilization
charges
through
novel
dual‐electrode
structure,
improves
detection
utilizing
an
enzyme‐catalyzed
reaction.
successfully
used
monitor
variation
concentration
during
crop
with
concentrations
as
low
4
µ
m
,
without
being
significantly
affected
common
fertilizers
such
potassium
chloride
or
ammonium
dihydrogen
phosphate.
first
capable
highly
specific
sensitive
fertilizer
detection,
pointing
toward
new
direction
developing
systems
within
development‐oriented
IoTs.
