Advanced Materials Technologies,
Год журнала:
2024,
Номер
9(7)
Опубликована: Фев. 6, 2024
Abstract
Triboelectric
nanogenerator
(TENG)
has
become
a
promising
candidate
for
wearable
energy
harvesting
and
self‐powered
sensing
systems.
However,
processing
large
amounts
of
data
imposes
computing
power
barrier
practical
application.
Machine
learning‐assisted
sensors
based
on
TENG
have
been
widely
used
in
data‐driven
applications
due
to
their
excellent
characteristics
such
as
no
additional
supply,
high
accuracy,
low
cost,
good
biocompatibility.
This
work
comprehensively
reviews
the
latest
progress
machine
learning
(ML)‐assisted
TENG‐based
sensors.
The
future
challenges
opportunities
are
discussed.
First,
fundamental
principles
including
working
mode
ML‐assisted
sensor
common
algorithms
systematically
illustrated,
which
emphasizes
algorithm
definition
principle.
Subsequently,
ML
methods
field
is
further
reviewed,
summarizing
advantages
disadvantages
various
examples,
providing
guidance
suggestions
how
choose
appropriate
methods.
Finally,
prospects
summarized.
Directions
important
insights
development
AI
integration
provided.
Advanced Functional Materials,
Год журнала:
2024,
Номер
34(49)
Опубликована: Авг. 8, 2024
Abstract
Recent
developments
in
robotics
increasingly
highlight
the
importance
of
sensing
technology,
especially
tactile
perception,
enabling
robots
to
effectively
engage
with
their
environment
and
interpret
physical
interactions.
Due
power
efficiency
low
cost,
triboelectric
mechanism
has
been
frequently
studied
for
measuring
pressure
identifying
materials
enhance
robot
perception.
Nevertheless,
there
limited
exploration
using
effect
detect
curved
surfaces,
despite
prevalence
daily
lives.
Here,
a
multimodal
sensor
(TMTS)
multilayered
structural
design
is
proposed
recognize
distinct
materials,
curvatures,
simultaneously,
thus
decoupling
different
modalities
enable
more
accurate
detection.
By
attaching
sensors
robotic
fingertips
leveraging
deep
learning
analytics,
quantitative
curvature
measurement
provides
precise
insights
into
an
object's
detailed
geometric
characteristics
rather
than
merely
assessing
its
overall
shape,
hence
achieving
automatic
recognition
12
grasped
objects
99.2%
accuracy.
The
can
be
further
used
accurately
softness
under
touch
gestures
hand,
94.1%
accuracy,
demonstrating
significant
potential
wide‐ranging
applications
future
robotic‐enabled
intelligent
society.
Applied Physics Letters,
Год журнала:
2025,
Номер
126(5)
Опубликована: Фев. 3, 2025
The
electricity
generation
of
triboelectric
nanogenerators
(TENGs)
originates
from
charge
transfer
enabled
by
contact
electrification.
However,
the
inherent
barrier
between
two
contacting
surfaces
hampers
transfer.
There
are
mainly
four
ways
to
promote
triboelectrification
TENGs.
While
synergy
among
them
has
never
been
achieved.
Herein,
we
reported
an
effective
strategy
boost
efficiency
synergizing
strong
ferroelectric
polarization
and
high
permittivity
embedded
lead
zirconate
titanate
fillers.
influence
interfacial
intensity
dielectric
permittivity,
as
well
corona
poling,
on
composite
film
was
systematically
investigated.
Notably,
switching
direction
renders
increase
(207%)
or
a
decrease
(71%)
in
output
comparison
with
non-poled
counterpart.
Theoretical
modeling
established
combining
Kelvin
probe
force
microscopy
characterization
electron
cloud
overlap
energy
band
derivation.
This
work
not
only
offers
unprecedented
insight
into
fundamental
mechanism
but
also
opens
up
possibility
development
next-generation
wearable
electronics.
Wearable
electronic
textiles
(e‐textiles)
have
emerged
as
a
transformative
technology
revolutionizing
healthcare
monitoring
and
communication
by
seamlessly
integrating
with
the
human
body.
However,
their
practical
application
has
been
limited
lack
of
compatible
sustainable
power
sources.
Various
energy
sources,
including
solar,
thermal,
mechanical,
wind,
explored
for
harvesting,
leading
to
diverse
harvesting
technologies,
such
photovoltaic,
thermoelectric,
piezoelectric,
triboelectric
systems.
Notably,
2D
materials
gained
significant
attention
attractive
candidates
storage
in
e‐textiles
due
unique
properties,
high
surface‐to‐volume
ratio,
mechanical
strength,
electrical
conductivity.
Textile‐based
harvesters
employing
offer
promising
solutions
powering
next‐generation
smart
wearable
devices
integrated
into
clothing.
This
comprehensive
review
explores
utilization
textile‐based
harvesters,
covering
preparation,
fabrication,
characterization
strategies.
Recent
advancements
are
highlighted,
focusing
on
integration
implementations,
shedding
light
performance
effectiveness
2D‐material‐based
e‐textiles,
highlighting
potential
alternative
conventional
supplies
technologies.
