The Journal of Physical Chemistry Letters,
Journal Year:
2024,
Volume and Issue:
15(34), P. 8667 - 8675
Published: Aug. 19, 2024
Emerging
optoelectronic
memristive
devices
with
high
parallelism
and
low-power
consumption
have
made
neuromorphic
computing
hardware
a
tangible
reality.
The
coordination
of
conductivity
regulation
through
both
electrical
light
signals
is
pivotal
for
advancing
the
development
synaptic
memristors
brainlike
functionalities.
Here,
an
artificial
visual
synapse
presented
Ti3C2
MXene
memristor
which
demonstrates
not
only
nonvolatile
memory
effect
(Set/Reset:
0.58/–0.55
V;
Retention:
>103
s)
sustained
multistage
conductivity,
but
also
facile
modulation
electrical-
light-stimulated
behaviors.
By
adjusting
stimulus
parameters,
enables
realization
biosynaptic
excitatory
postsynaptic
current,
stable
long-term
facilitation/depression,
paired
pulse
facilitation,
spiking-timing-dependent
plasticity,
experiential
learning.
Particularly,
benefiting
from
distinguishable
photoconductive
effects
multiple
near-infrared
intensities
(7–13
mW/cm2),
potential
applications
in
nociceptive
perception
("threshold",
"noadaption",
"relaxation")
imaging
(e.g.,
"Superman"
cartoon
character)
infrared
environments
are
well
achieved
such
memristors.
These
results
hold
significant
implications
future
advancement
integrated
sensing,
memory,
nociception,
systems.
Chemical Society Reviews,
Journal Year:
2023,
Volume and Issue:
52(20), P. 7071 - 7136
Published: Jan. 1, 2023
This
review
highlights
the
film
preparation
methods
and
application
advances
in
memory
neuromorphic
electronics
of
porous
crystalline
materials,
involving
MOFs,
COFs,
HOFs,
zeolites.
Advanced Functional Materials,
Journal Year:
2023,
Volume and Issue:
33(26)
Published: March 24, 2023
Abstract
With
the
demand
for
low‐power‐operating
artificial
intelligence
systems,
bio‐inspired
memristor
devices
exhibit
potential
in
terms
of
high‐density
memory
functions
and
emulation
synaptic
dynamics
human
brain.
The
2D
material
MXene
attracts
considerable
interest
use
resistive‐switching
synapse
owing
to
its
excellent
physicochemical
properties
devices.
However,
few
memristive
that
display
increased
switching
performances
are
reported,
with
no
significant
results.
Herein,
conductivity
(Ti
3
C
2
T
x
)
is
engineered
via
etching
oxidation
enhance
performance
device.
exceptional
partially
oxidized
memristors
include
large
windows
low
threshold
biases,
complex
spike‐timing‐dependent
plasticity
rules
also
emulated.
distribution,
reliable
retention
time
(10
4
s),
distinct
resistance
states
a
high
ON–OFF
ratio
(>10
main
memory‐related
features
this
experimentally
determined
potentials
optimized
device
uniformly
distributed,
according
statistical
probability‐based
approach.
This
investigation
may
promote
essential
non‐volatile
storage
systems
field
innovative
nanoelectronic
Advanced Materials,
Journal Year:
2023,
Volume and Issue:
35(33)
Published: June 20, 2023
A
high-density
neuromorphic
computing
memristor
array
based
on
2D
materials
paves
the
way
for
next-generation
information-processing
components
and
in-memory
systems.
However,
traditional
2D-materials-based
devices
suffer
from
poor
flexibility
opacity,
which
hinders
application
of
memristors
in
flexible
electronics.
Here,
a
artificial
synapse
TiOx
/Ti3
C2
Tx
film
is
fabricated
by
convenient
energy-efficient
solution-processing
technique,
realizes
high
transmittance
(≈90%)
oxidation
resistance
(>30
days).
The
shows
low
device-to-device
variability,
long
memory
retention
endurance,
ON/OFF
ratio,
fundamental
synaptic
behavior.
Furthermore,
satisfactory
(R
=
1.0
mm)
mechanical
endurance
(104
bending
cycles)
are
achieved,
superior
to
other
prepared
chemical
vapor
deposition.
In
addition,
high-precision
(>96.44%)
MNIST
handwritten
digits
recognition
classification
simulation
indicates
that
holds
promise
future
applications,
provides
excellent
neuron
circuits
new
intelligent
electronic
equipment.
Advanced Functional Materials,
Journal Year:
2023,
Volume and Issue:
33(42)
Published: June 23, 2023
Abstract
The
booming
development
of
artificial
intelligence
(AI)
requires
faster
physical
processing
units
as
well
more
efficient
algorithms.
Recently,
reservoir
computing
(RC)
has
emerged
an
alternative
brain‐inspired
framework
for
fast
learning
with
low
training
cost,
since
only
the
weights
associated
output
layers
should
be
trained.
Physical
RC
becomes
one
leading
paradigms
computation
using
high‐dimensional,
nonlinear,
dynamic
substrates.
Among
them,
memristor
appears
to
a
simple,
adaptable,
and
constructing
they
exhibit
nonlinear
features
memory
behavior,
while
memristor‐implemented
neural
networks
display
increasing
popularity
towards
neuromorphic
computing.
In
this
review,
systems
from
following
aspects:
architectures,
materials,
applications
are
summarized.
It
starts
introduction
structures
that
can
simulated
blocks.
Specific
interest
then
focuses
on
behaviors
memristors
based
various
material
systems,
optimizing
understanding
relationship
between
relaxation
which
provides
guidance
references
building
coped
on‐demand
application
scenarios.
Furthermore,
recent
advances
in
memristor‐based
surveyed.
end,
further
prospects
system
view
envisaged.
Advanced Science,
Journal Year:
2023,
Volume and Issue:
10(16)
Published: April 18, 2023
In
the
era
of
big
data
and
artificial
intelligence
(AI),
advanced
storage
processing
technologies
are
in
urgent
demand.
The
innovative
neuromorphic
algorithm
hardware
based
on
memristor
devices
hold
a
promise
to
break
von
Neumann
bottleneck.
recent
years,
carbon
nanodots
(CDs)
have
emerged
as
new
class
nano-carbon
materials,
which
attracted
widespread
attention
applications
chemical
sensors,
bioimaging,
memristors.
focus
this
review
is
summarize
main
advances
CDs-based
memristors,
their
state-of-the-art
synapses,
computing,
human
sensory
perception
systems.
first
step
systematically
introduce
synthetic
methods
CDs
derivatives,
providing
instructive
guidance
prepare
high-quality
with
desired
properties.
Then,
structure-property
relationship
resistive
switching
mechanism
memristors
discussed
depth.
current
challenges
prospects
memristor-based
synapses
computing
also
presented.
Moreover,
outlines
some
promising
application
scenarios
including
sensors
vision,
low-energy
quantum
computation,
human-machine
collaboration.
Advanced Functional Materials,
Journal Year:
2024,
Volume and Issue:
34(16)
Published: Jan. 4, 2024
Abstract
Memristors
have
recently
become
powerful
competitors
toward
artificial
synapses
and
neuromorphic
computation,
arising
from
their
structural
electrical
similarity
to
biological
neurons.
From
the
diversity
of
materials,
numerous
organic
inorganic
materials
proven
exhibit
great
potential
in
application
memristors.
Herein,
this
work
focuses
on
a
class
memristors
based
frameworks
(OFs)
pay
attention
most
advanced
experimental
demonstrations.
First,
typical
device
structures
memristive
switching
mechanisms
are
introduced.
Second,
latest
progress
OFs‐based
is
comprehensively
summarized,
including
metal‐organic
(MOFs),
covalent
(COFs),
hydrogen‐bonded
(HOFs),
as
well
applications
data
storage,
synapses,
devices.
Finally,
future
challenges
prospects
deeply
discussed.
Chemical Reviews,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Jan. 2, 2025
Recent
breakthroughs
in
brain-inspired
computing
promise
to
address
a
wide
range
of
problems
from
security
healthcare.
However,
the
current
strategy
implementing
artificial
intelligence
algorithms
using
conventional
silicon
hardware
is
leading
unsustainable
energy
consumption.
Neuromorphic
based
on
electronic
devices
mimicking
biological
systems
emerging
as
low-energy
alternative,
although
further
progress
requires
materials
that
can
mimic
function
while
maintaining
scalability
and
speed.
As
result
their
diverse
unique
properties,
atomically
thin
two-dimensional
(2D)
are
promising
building
blocks
for
next-generation
electronics
including
nonvolatile
memory,
in-memory
neuromorphic
computing,
flexible
edge-computing
systems.
Furthermore,
2D
achieve
biorealistic
synaptic
neuronal
responses
extend
beyond
logic
memory
Here,
we
provide
comprehensive
review
growth,
fabrication,
integration
van
der
Waals
heterojunctions
optoelectronic
devices,
circuits,
For
each
case,
relationship
between
physical
properties
device
emphasized
followed
by
critical
comparison
technologies
different
applications.
We
conclude
with
forward-looking
perspective
key
remaining
challenges
opportunities
applications
leverage
fundamental
heterojunctions.
The Journal of Physical Chemistry Letters,
Journal Year:
2023,
Volume and Issue:
14(32), P. 7173 - 7192
Published: Aug. 4, 2023
Neuromorphic
computing
could
enable
the
potential
to
break
inherent
limitations
of
conventional
von
Neumann
architectures,
which
has
led
widespread
research
interest
in
developing
novel
neuromorphic
memory
devices,
such
as
memristors
and
bioinspired
artificial
synaptic
devices.
Covalent
organic
frameworks
(COFs),
crystalline
porous
polymers,
have
tailorable
skeletons
pores,
providing
unique
platforms
for
interplay
with
photons,
excitons,
electrons,
holes,
ions,
spins,
molecules.
Such
features
encourage
rising
COF
materials
electronics.
To
develop
high-performance
COF-based
it
is
necessary
comprehensively
understand
materials,
applications.
Therefore,
this
Perspective
focuses
on
discussing
use
devices
terms
molecular
design,
thin-film
processing,
Finally,
we
provide
an
outlook
future
directions
applications
