ACS Applied Materials & Interfaces,
Год журнала:
2025,
Номер
unknown
Опубликована: Апрель 29, 2025
A
self-biased
thin-film
transistor
(TFT)
has
been
fabricated
by
using
poly(3,
4-ethylenedioxythiophene)-poly(styrenesulfonate)
(PEDOT:
PSS)
as
a
conducting
channel
that
works
an
efficient
mechanical
energy
harvesting
device.
The
self-biasing
of
this
top-gated
TFT
accomplished
through
the
integration
two
voltage
sources
within
device
structure,
which
are
essential
for
its
operation.
LiF/Al
and
MoO3/Ag
electrodes
serve
source
drain,
respectively,
work-function
difference
∼-1.16
eV,
drain
bias
(VD).
poly(vinylidene
fluoride-co-hexafluoropropylene)
(PVDF-HFP)
thin
film
employed
gate
dielectric
generates
piezo-potential
due
to
application
external
pressure
(VG)
TFT.
unique
feature
is
prolonged
electrical
power
generation
in
DC
form
during
force
enables
us
measure
mechanical-to-electrical
conversion
accurately.
extracted
efficiencies
hard
flexible
(flat)
substrate-based
TFTs
0.4
1.9%,
respectively.
Interestingly,
efficiency
increases
with
bending
can
reach
up
33%
unusually
high
In
addition,
characterization
these
devices
shows
transistor-like
behavior
On-Off
ratio
subthreshold
swing
2
×
102
5.88
N/decade,
substrate,
while
on
values
1
104
1.35
Energies,
Год журнала:
2025,
Номер
18(5), С. 1068 - 1068
Опубликована: Фев. 22, 2025
Lithium-ion
batteries
(LIBs)
are
widely
used
in
the
fields
of
consumer
electronics,
new
energy
vehicles,
and
grid
storage
due
to
their
high
density
long
cycle
life.
However,
how
effectively
evaluate
State
Charge
(SOC),
Health
(SOH),
overcharging
behavior
has
become
a
key
issue
improving
battery
safety
lifespan.
Acoustic
sensing
technology,
as
an
advanced
non-destructive
monitoring
method,
achieves
real-time
internal
state
accurate
evaluation
parameters
through
ultrasonic
testing
technology
acoustic
emission
technology.
This
article
systematically
reviews
research
progress
SOC,
SOH,
overcharge
LIBs,
analyzes
its
working
principle
application
advantages,
explores
future
optimization
directions
industrialization
prospects.
provides
important
support
for
building
efficient
safe
management
systems.
ACS Omega,
Год журнала:
2025,
Номер
10(9), С. 9381 - 9389
Опубликована: Фев. 26, 2025
With
the
rapid
development
of
Internet
Things
(IoT)
and
5G
technology,
there
has
been
a
considerable
increase
in
demand
for
self-powered
flexible
sensors.
However,
existing
solutions
frequently
prove
inadequate
regarding
flexibility,
energy
efficiency,
accuracy
with
which
gestures
can
be
recognized,
particularly
noncontact
operation
scenarios.
As
result,
is
need
innovative
developments
sensor
technology.
This
study
proposes
an
artificial
intelligence-based
gesture
recognition
system
comprising
triboelectric
ring,
Arduino
signal
processing
module,
deep
learning
module.
Our
approach
enables
direct
reading
signals
by
through
integrated
circuits,
thereby
maintaining
output
voltage
within
input
range
commonly
used
microcontrollers.
The
integration
technology
sophisticated
methodologies,
notably
utilization
one-dimensional
convolutional
neural
network
(CNN),
enabled
that
exhibits
rate
exceeding
95%
12
distinct
gestures.
demonstrates
prospective
utility
sensors
realms
recognition,
wearable
human–machine
interaction.
