Advanced Functional Materials,
Journal Year:
2024,
Volume and Issue:
34(25)
Published: Feb. 1, 2024
Abstract
Empowering
displays
with
intelligent
functions
enables
their
application
in
image
processing
and
interactive
displays,
which
is
the
combination
of
future
display
artificial
intelligence
technologies.
However,
existing
technologies
face
significant
transmission
burdens
due
to
conventional
hardware
separation
architecture,
separates
memory
from
processor
module
module.
To
address
these
challenges,
a
highly
integrated
memory‐
processing‐display
light‐emitting
(MPDIH)
capable
information
generation,
memory,
processing,
visualization
proposed.
The
MPDIH,
based
on
an
organic
light‐sensitive
layer
activated
by
ultraviolet
light
irradiation,
exhibits
unique
photoinhibition
behavior
attributed
reverse
light‐induced
electric
field
formed
directional
arrangement
photo‐generated
excitons.
This
dynamic
regulation
autonomous
learning
during
device
training
process.
Leveraging
this
phenomenon,
successfully
demonstrated,
achieving
contrast
improvement
maximum
enhancement
261%
compared
unprocessed
raw
signals.
Furthermore,
memory‐processing‐display
scheme
fashion
MNIST
recognition
using
neural
network,
achieves
noticeably
higher
accuracy
(>89%)
original
fuzzy
images
(<59%).
Consequently,
proposed
holds
promise
for
applications
photonic
systems
displays.
Nature Communications,
Journal Year:
2022,
Volume and Issue:
13(1)
Published: Dec. 23, 2022
Devices
with
sensing-memory-computing
capability
for
the
detection,
recognition
and
memorization
of
real
time
sensory
information
could
simplify
data
conversion,
transmission,
storage,
operations
between
different
blocks
in
conventional
chips,
which
are
invaluable
sought-after
to
offer
critical
benefits
accomplishing
diverse
functions,
simple
design,
efficient
computing
simultaneously
internet
things
(IOT)
era.
Here,
we
develop
a
self-powered
vertical
tribo-transistor
(VTT)
based
on
MXenes
multi-sensing-memory-computing
function
multi-task
emotion
recognition,
integrates
triboelectric
nanogenerator
(TENG)
transistor
single
device
configuration
organic
field
effect
(VOFET).
The
tribo-potential
is
found
be
able
tune
ionic
migration
insulating
layer
Schottky
barrier
height
at
MXene/semiconductor
interface,
thus
modulate
conductive
channel
MXene
drain
electrode.
Meanwhile,
sensing
sensitivity
can
significantly
improved
by
711
times
over
TENG
device,
VTT
exhibits
excellent
function.
Importantly,
this
function,
multi-sensing
integration
multi-model
constructed,
improves
accuracy
up
94.05%
reliability.
This
structure
high
sensitivity,
efficiency
accuracy,
provides
application
prospects
future
human-mechanical
interaction,
IOT
high-level
intelligence.
Advanced Materials,
Journal Year:
2023,
Volume and Issue:
35(24)
Published: April 4, 2023
Light-stimulated
optoelectronic
synaptic
devices
are
fundamental
compositions
of
the
neuromorphic
vision
system.
However,
there
still
huge
challenges
to
achieving
both
bidirectional
behaviors
under
light
stimuli
and
high
performance.
Herein,
a
bilayer
2D
molecular
crystal
(2DMC)
p-n
heterojunction
is
developed
achieve
high-performance
behaviors.
The
2DMC
heterojunction-based
field
effect
transistor
(FET)
exhibit
typical
ambipolar
properties
remarkable
responsivity
(R)
3.58×104
A
W-1
weak
as
low
0.008
mW
cm-2
.
Excitatory
inhibitory
successfully
realized
by
same
different
gate
voltages.
Moreover,
superior
contrast
ratio
(CR)
1.53×103
demonstrated
ultrathin
high-quality
heterojunction,
which
transcends
previous
synapses
enables
application
for
motion
detection
pendulum.
Furthermore,
network
based
on
device
detect
recognize
classic
vehicles
in
road
traffic
with
an
accuracy
exceeding
90%.
This
work
provides
effective
strategy
developing
high-contrast
shows
great
potential
intelligent
bionic
future
artificial
vision.
Nature Communications,
Journal Year:
2023,
Volume and Issue:
14(1)
Published: May 8, 2023
Realizing
multi-modal
information
recognition
tasks
which
can
process
external
efficiently
and
comprehensively
is
an
urgent
requirement
in
the
field
of
artificial
intelligence.
However,
it
remains
a
challenge
to
achieve
simple
structure
high-performance
demonstrations
owing
complex
execution
module
separation
memory
processing
based
on
traditional
complementary
metal
oxide
semiconductor
(CMOS)
architecture.
Here,
we
propose
efficient
sensory
system
(SMPS),
generate
synapse-like
multi-wavelength
light-emitting
output,
realizing
diversified
utilization
light
recognition.
The
SMPS
exhibits
strong
robustness
encoding/transmission
capability
visible
display
through
multi-level
color
responses,
implement
pain
warning
organisms
intuitively.
Furthermore,
different
from
conventional
that
requires
independent
circuit
modules,
proposed
with
unique
optical
multi-information
parallel
output
realize
dynamic
step
frequency
spatial
positioning
simultaneously
accuracy
99.5%
98.2%,
respectively.
Therefore,
this
work
component,
flexible
operation,
robustness,
highly
efficiency
promising
for
future
sensory-neuromorphic
photonic
systems
interactive
Advanced Energy Materials,
Journal Year:
2024,
Volume and Issue:
14(20)
Published: Feb. 14, 2024
Abstract
Machine
learning
(ML)
exhibits
substantial
potential
for
predicting
the
properties
of
solid‐state
electrolytes
(SSEs).
By
integrating
experimental
or/and
simulation
data
within
ML
frameworks,
discovery
and
development
advanced
SSEs
can
be
accelerated,
ultimately
facilitating
their
application
in
high‐end
energy
storage
systems.
This
review
commences
with
an
introduction
to
background
SSEs,
including
explicit
definition,
comprehensive
classification,
intrinsic
physical/chemical
properties,
underlying
mechanisms
governing
conductivity,
challenges,
future
developments.
An
in‐depth
explanation
methodology
is
also
elucidated.
Subsequently,
key
factors
that
influence
performance
are
summarized,
thermal
expansion,
modulus,
diffusivity,
ionic
reaction
energy,
migration
barrier,
band
gap,
activation
energy.
Finally,
it
offered
perspectives
on
design
prerequisites
upcoming
generations
focusing
real‐time
property
prediction,
multi‐property
optimization,
multiscale
modeling,
transfer
learning,
automation
high‐throughput
experimentation,
synergistic
optimization
full
battery,
all
which
crucial
accelerating
progress
SSEs.
aims
guide
novel
SSE
materials
practical
realization
efficient
reliable
technologies.
Energy & Environmental Science,
Journal Year:
2023,
Volume and Issue:
16(9), P. 3873 - 3884
Published: Jan. 1, 2023
A
self-powered
system
composed
of
an
electrochemical
recycling
reactor
and
a
triboelectric
nanogenerator
is
proposed
for
spent
lithium-ion
battery
with
the
advantages
high
purity,
self-powering,
simplified
procedure,
profit.
Small,
Journal Year:
2023,
Volume and Issue:
19(18)
Published: Feb. 7, 2023
Abstract
Stretchable
synaptic
transistors,
a
core
technology
in
neuromorphic
electronics,
have
functions
and
structures
similar
to
biological
synapses
can
concurrently
transmit
signals
learn.
transistors
are
usually
soft
stretchy
accommodate
various
mechanical
deformations,
which
presents
significant
prospects
machines,
electronic
skin,
human–brain
interfaces,
wearable
electronics.
Considerable
efforts
been
devoted
developing
stretchable
implement
device
functions,
remarkable
advances
achieved.
Here,
this
review
introduces
the
basic
concept
of
artificial
summarizes
recent
progress
structures,
functional‐layer
materials,
fabrication
processes.
Classical
including
electric
double‐layer
electrochemical
optoelectronic
as
well
applications
light‐sensory
systems,
tactile‐sensory
multisensory
artificial‐nerves
discussed.
Finally,
current
challenges
potential
directions
analyzed.
This
detailed
introduction
from
applications,
providing
reference
for
development
future.
ACS Nano,
Journal Year:
2024,
Volume and Issue:
18(26), P. 17041 - 17052
Published: June 21, 2024
Flexible
tactile
sensors
show
promise
for
artificial
intelligence
applications
due
to
their
biological
adaptability
and
rapid
signal
perception.
Triboelectric
enable
active
dynamic
sensing,
while
integrating
static
pressure
sensing
real-time
multichannel
transmission
is
key
further
development.
Here,
we
propose
an
integrated
structure
combining
a
capacitive
sensor
spatiotemporal
mapping
triboelectric
recognition.
A
liquid
metal-based
flexible
dual-mode
triboelectric-capacitive-coupled
(TCTS)
array
of
4
×
pixels
achieves
spatial
resolution
7
mm,
exhibiting
detection
limit
0.8
Pa
fast
response
6
ms.
Furthermore,
neuromorphic
computing
using
the
MXene-based
synaptic
transistor
100%
recognition
accuracy
handwritten
numbers/letters
within
90
epochs
based
on
signals
collected
by
TCTS
array,
cross-spatial
information
communication
from
perceived
data
realized
in
mixed
reality
space.
The
results
illuminate
considerable
application
possibilities
technology
human-machine
interfaces
advanced
robotics.
Advanced Materials,
Journal Year:
2024,
Volume and Issue:
36(33)
Published: June 15, 2024
Biomimetic
humidity
sensors
offer
a
low-power
approach
for
respiratory
monitoring
in
early
lung-disease
diagnosis.
However,
balancing
miniaturization
and
energy
efficiency
remains
challenging.
This
study
addresses
this
issue
by
introducing
bioinspired
humidity-sensing
neuron
comprising
self-assembled
peptide
nanowire
(NW)
memristor
with
unique
proton-coupled
ion
transport.
The
proposed
shows
low
Ag
Advanced Materials,
Journal Year:
2024,
Volume and Issue:
36(37)
Published: Feb. 29, 2024
Abstract
Human–machine
interaction
(HMI)
technology
has
undergone
significant
advancements
in
recent
years,
enabling
seamless
communication
between
humans
and
machines.
Its
expansion
extended
into
various
emerging
domains,
including
human
healthcare,
machine
perception,
biointerfaces,
thereby
magnifying
the
demand
for
advanced
intelligent
technologies.
Neuromorphic
computing,
a
paradigm
rooted
nanoionic
devices
that
emulate
operations
architecture
of
brain,
emerged
as
powerful
tool
highly
efficient
information
processing.
This
paper
delivers
comprehensive
review
developments
device‐based
neuromorphic
computing
technologies
their
pivotal
role
shaping
next‐generation
HMI.
Through
detailed
examination
fundamental
mechanisms
behaviors,
explores
ability
memristors
ion‐gated
transistors
to
intricate
functions
neurons
synapses.
Crucial
performance
metrics,
such
reliability,
energy
efficiency,
flexibility,
biocompatibility,
are
rigorously
evaluated.
Potential
applications,
challenges,
opportunities
using
HMI
technologies,
discussed
outlooked,
shedding
light
on
fusion
with
