Advanced Energy Materials,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Sept. 10, 2024
Abstract
In
the
era
of
Internet
Things
(IoT)
and
Artificial
Intelligence
(AI),
sensors
have
become
an
integral
part
intelligent
systems.
Although
traditional
sensing
technology
is
very
mature
in
long‐term
development,
there
are
remaining
defects
limitations
that
make
it
difficult
to
meet
growing
demands
current
applications,
such
as
high‐sensitivity
detection
self‐supplied
sensing.
As
a
new
type
sensor,
array
triboelectric
nanogenerators
(TENG)‐based
tactile
can
respond
wide
dynamic
range
mechanical
stimuli
surrounding
environment
converting
them
into
quantifiable
electrical
signals,
thus
realizing
real‐time
The
structure
allows
for
fine
delineation
area
improved
spatial
resolution,
resulting
accurate
localization
quantification
detected
been
widely
used
wearable
devices,
smart
interaction,
medical
health
detection,
other
fields.
this
paper,
latest
research
progress
functional
based
on
arrayed
systematically
reviewed
from
aspects
working
mechanism,
material
selection,
processing,
structural
design,
integration,
application.
Finally,
challenges
faced
by
summarized
with
view
providing
inspiration
guidance
future
development
sensors.
Advanced Functional Materials,
Journal Year:
2024,
Volume and Issue:
34(25)
Published: Feb. 4, 2024
Abstract
Hydrogel
electrolyte
is
not
resistant
to
freezing
and
has
weak
mechanical
properties,
its
fabrication
time‐consuming
energy‐consuming,
limiting
application.
Here,
a
simple,
universal,
fast
gelation
based
on
dealkaline
lignin
(DL)
‐alkali
metal
ions
developed.
The
complex
formed
by
catechol
alkali
promotes
the
equilibrium
of
redox
reactions.
produced
SO
4
−
·,
OH·
singlet
oxygen
(
1
O
2
)
radicals
are
responsible
for
rapid
polymerization
vinyl
monomers.
Alkali
play
dual
role
in
frost
resistance
hydrogel
electrolytes.
By
modulating
mass
ratio
DL
ion
concentration,
preferred
can
be
fabricated
an
alkaline
aqueous
solution
min
at
room
temperature
possesses
excellent
anti‐freezing
performance
(0.51
mS
cm
−1
−40
°C)
strong
properties
(tensile
stress:
0.4
MPa,
strain:
1125%).
electrolyte‐assembled
supercapacitor
exhibits
high
stability
low
temperatures.
specific
capacitance
retention
89.7
%
88.7
after
5000
charge/discharge
cycles
25
−20
°C,
respectively.
lignin‐alkali
self‐catalytic
system
completely
different
from
reported
lignin‐oxidizing
will
open
up
new
way
ionic
conductors
energy
storage
devices.
Advanced Functional Materials,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Jan. 7, 2025
Abstract
Bio‐based
hydrogels,
valued
for
their
flexibility,
tunable
mechanical
properties,
and
biocompatibility,
are
promising
materials
wearable
skins
sensing
devices
in
bionic
hand
control
systems.
Lignin,
a
biopolymer
rich
functional
groups,
can
be
modified
into
UV‐curable
monomers,
enabling
the
development
of
3D‐printed
hydrogels
via
photopolymerization.
However,
inherent
rigidity
lignin's
aromatic
rings,
coupled
with
covalent
cross‐linking
between
lignin
other
often
limits
hydrogel's
stretchability
(poor
strain)
compressibility.
Additional
challenges,
including
poor
moisture
retention
freeze
resistance,
further
hinder
wider
application.
In
this
study,
lignin‐based
hydrogel
is
developed
high
tensile
strain
(≥350%),
compressive
(≈95%),
fatigue
resistance
(up
to
10
000
cycles
under
50%
strain,
200–800
95%
strain),
which
achieved
by
incorporating
glycerol
lithium
chloride
facilitate
dynamic
hydrogen
ion
bonds,
while
accordingly
reducing
sites
monomers.
The
enhanced
allow
effective
performance
at
−40±1
°C.
Afterward,
using
3D
printing
technology,
sensors
ripple‐shaped
3
×
Matrix
pressure
fabricated,
demonstrated
uniform
stress
distribution
improved
controlling
complex
movements,
underscoring
application
advancing
human–machine
interfaces.
Sensors,
Journal Year:
2024,
Volume and Issue:
24(10), P. 3032 - 3032
Published: May 10, 2024
The
domain
of
human
locomotion
identification
through
smartphone
sensors
is
witnessing
rapid
expansion
within
the
realm
research.
This
boasts
significant
potential
across
various
sectors,
including
healthcare,
sports,
security
systems,
home
automation,
and
real-time
location
tracking.
Despite
considerable
volume
existing
research,
greater
portion
it
has
primarily
concentrated
on
activities.
Comparatively
less
emphasis
been
placed
recognition
localization
patterns.
In
current
study,
we
introduce
a
system
by
facilitating
both
physical
location-based
utilizes
capabilities
to
achieve
its
objectives.
Our
goal
develop
that
can
accurately
identify
different
activities,
such
as
walking,
running,
jumping,
indoor,
outdoor
To
this,
perform
preprocessing
raw
sensor
data
using
Butterworth
filter
for
inertial
Median
Filter
Global
Positioning
System
(GPS)
then
applying
Hamming
windowing
techniques
segment
filtered
data.
We
extract
features
from
GPS
select
relevant
variance
threshold
feature
selection
method.
extrasensory
dataset
exhibits
an
imbalanced
number
samples
certain
address
this
issue,
permutation-based
augmentation
technique
employed.
augmented
are
optimized
Yeo–Johnson
power
transformation
algorithm
before
being
sent
multi-layer
perceptron
classification.
evaluate
our
K-fold
cross-validation
technique.
datasets
used
in
study
Extrasensory
Sussex
Huawei
Locomotion
(SHL),
which
contain
experiments
demonstrate
achieves
high
accuracy
with
96%
94%
over
SHL
activities
91%
outperforming
previous
state-of-the-art
methods
recognizing
types
