Resistive
switching
(RS)
memories
are
novel
devices
that
have
attracted
significant
attention
recently
in
view
of
their
potential
integration
deep
neural
networks
for
intense
big
data
processing
within
the
explosive
artificial
intelligence
era.
While
oxide-
or
silicon-based
memristive
been
thoroughly
studied
and
analyzed,
there
alternative
material
technologies
compatible
with
lower
manufacturing
cost
less
environmental
impact
exhibiting
RS
characteristics,
thus
providing
a
versatile
platform
specific
in-memory
computing
neuromorphic
applications
where
sustainability
is
priority.
The
these
emerging
based
on
solution-processed
methods
at
low
temperatures
onto
flexible
substrates,
some
cases,
active
layer
composed
natural,
environmentally
friendly
materials
replacing
expensive
deposition
critical
raw
toxic
materials.
In
this
Perspective,
we
provide
an
overview
recent
developments
field
sustainable
by
insights
into
fundamental
properties
mechanisms,
categorizing
key
figures
merit
while
showcasing
representative
use
cases
each
technology.
challenges
limitations
practical
analyzed
along
suggestions
to
resolve
pending
issues.
Journal of Semiconductors,
Год журнала:
2025,
Номер
46(2), С. 022403 - 022403
Опубликована: Фев. 1, 2025
Abstract
The
hierarchical
and
coordinated
processing
of
visual
information
by
the
brain
demonstrates
its
superior
ability
to
minimize
energy
consumption
maximize
signal
transmission
efficiency.
Therefore,
it
is
crucial
develop
artificial
synapses
that
integrate
optical
sensing
synaptic
functions.
This
study
fully
leverages
excellent
photoresponsivity
properties
PM6
:
Y6
system
construct
a
vertical
photo-tunable
organic
memristor
conducts
in-depth
research
on
resistive
switching
performance,
photodetection
capability,
simulation
photo-synaptic
behavior,
showcasing
performance
in
simulating
neuromorphic
behaviors.
device
achieves
stable
gradual
resistance
change,
successfully
voltage-controlled
long-term
potentiation/depression
(LTP/LTD),
exhibits
various
photo-electric
synergistic
regulation
plasticity.
Moreover,
has
simulated
image
perception
recognition
functions
human
nervous
system.
non-volatile
Au/PM6
Y6/ITO
used
as
an
synapse
neuron
modeling,
building
SLP-CNN
cascade
neural
network
for
training,
linear
tunable
photoconductivity
characteristic
serves
weight
update
network,
achieving
accuracy
up
93.4%.
Compared
with
single-layer
target
model,
this
scheme
improved
19.2%.
Abstract
Memristors
and
artificial
synapses
have
attracted
tremendous
attention
due
to
their
promising
potential
for
application
in
the
field
of
neural
morphological
computing,
but
at
same
time,
continuous
optimization
improvement
energy
consumption
are
also
highly
desirable.
In
recent
years,
it
has
been
demonstrated
that
heterojunction
is
great
significance
improving
memristors
synapses.
By
optimizing
material
composition,
interface
characteristics,
device
structure
heterojunctions,
can
be
reduced,
performance
stability
durability
improved,
providing
strong
support
achieving
low‐power
computing
systems.
Herein,
we
review
progress
on
heterojunction‐based
by
summarizing
working
mechanisms
advances
memristors,
terms
selection,
design,
fabrication
techniques,
strategies,
etc.
Then,
applications
neuromorphological
deep
learning
introduced
discussed.
After
that,
remaining
bottlenecks
restricting
development
discussed
detail.
Finally,
corresponding
strategies
overcome
challenges
proposed.
We
believe
this
may
shed
light
high‐performance
synapse
devices.
Advanced Functional Materials,
Год журнала:
2025,
Номер
unknown
Опубликована: Апрель 16, 2025
Abstract
The
utilization
of
organic
cocrystal‐based
superlattice
materials
(OCSMs)
in
the
field
optoelectronics
is
experiencing
significant
advancements
attributable
to
their
accurate
stoichiometric
coefficient
and
distinctive
supramolecular
self‐assembly
structures.
Herein,
an
exhaustive
review
on
development
OCSMs
reported
over
past
few
years
presented,
with
a
primary
focus
following
major
aspects.
First,
emerging
nanostructures
primarily
consist
hydrogen‐bonded
frameworks
(HOFs)
halogen‐bonded
(XOFs),
innovative
cocrystal
heterostructures
(OHSs),
nanomeshes
(OMSs).
Further,
comprehensive
summary
provided
investigation
crystals
film
preparation
techniques
for
OCSMs,
which
encompasses
liquid‐phase
growth,
physical‐vapor‐transfer
methods,
solid‐phase
processes.
characteristics
tunable
fluorescence
emission
rapid
stimulus
response
exhibited
by
these
as
well
applications
memristors,
photothermal
conversion
imaging,
sensors,
FETs,
spin
devices,
are
also
elucidated.
mechanisms
underlying
charge
transfer
effects,
π–π
interactions,
hydrogen
bonds,
halogen
bonds
finally
analyzed
provide
valuable
insights
into
material
design
promising
applications.
With
the
increasing
limitations
of
conventional
computing
techniques,
particularly
von
Neumann
bottleneck,
brain's
seamless
integration
memory
and
processing
through
synapses
offers
a
valuable
model
for
technological
innovation.
Inspired
by
biological
synapse
facilitating
adaptive,
low-power
computation
modulating
signal
transmission
via
ionic
conduction,
iontronic
synaptic
devices
have
emerged
as
one
most
promising
candidates
neuromorphic
computing.
Meanwhile,
atomic-scale
thickness
tunable
electronic
properties
van
der
Waals
two-dimensional
(2D)
materials
enable
possibility
designing
highly
integrated,
energy-efficient
that
closely
replicate
plasticity.
This
review
comprehensively
analyzes
advancements
in
based
on
2D
materials,
focusing
electron-ion
interactions
both
transistors
memristors.
The
challenges
material
stability,
scalability,
device
are
evaluated,
along
with
potential
solutions
future
research
directions.
By
highlighting
these
developments,
this
insights
into
advancing
systems.
Nano-Micro Letters,
Год журнала:
2025,
Номер
17(1)
Опубликована: Май 8, 2025
Abstract
Neuromorphic
computing
has
the
potential
to
overcome
limitations
of
traditional
silicon
technology
in
machine
learning
tasks.
Recent
advancements
large
crossbar
arrays
and
silicon-based
asynchronous
spiking
neural
networks
have
led
promising
neuromorphic
systems.
However,
developing
compact
parallel
for
integrating
artificial
into
hardware
remains
a
challenge.
Organic
computational
materials
offer
affordable,
biocompatible
devices
with
exceptional
adjustability
energy-efficient
switching.
Here,
review
investigates
made
development
organic
devices.
This
explores
resistive
switching
mechanisms
such
as
interface-regulated
filament
growth,
molecular-electronic
dynamics,
nanowire-confined
vacancy-assisted
ion
migration,
while
proposing
methodologies
enhance
state
retention
conductance
adjustment.
The
survey
examines
challenges
faced
implementing
low-power
computing,
e.g.,
reducing
device
size
improving
time.
analyses
these
adjustable,
flexible,
consumption
applications,
viz.
biohybrid
circuits
interacting
biological
systems,
systems
that
respond
specific
events,
robotics,
intelligent
agents,
bioelectronics,
neuroscience,
other
prospects
this
technology.
Materials Horizons,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 1, 2025
Ionic
liquid-functionalized
geopolymers
fabricated
at
the
micron-scale
exhibit
enhanced
memristive
retention
and
biologically
relevant
synaptic
functions,
establishing
a
sustainable
platform
for
neuromorphic
hardware
integration.
Abstract
The
roles
of
keratan
sulfate
(KS)
as
a
proton
detection
glycosaminoglycan
in
neurosensory
processes
the
central
and
peripheral
nervous
systems
is
reviewed.
functional
properties
KS-proteoglycans
aggrecan,
phosphacan,
podocalyxcin
components
perineuronal
nets
neuronal
plasticity,
cognitive
learning
memory
are
also
discussed.
KS-glycoconjugate
gels
used
electrolocation
elasmobranch
fish
species
KS
substituted
mucin
like
conjugates
some
tissue
contexts
mammals
need
to
be
considered
sensory
signalling.
Parallels
drawn
between
KS’s
its
mammalian
electro
mechanical
transduction
acoustic
liquid
displacement
signals
cochlea
by
tectorial
membrane
stereocilia
inner
outer
hair
cells
into
neural
for
sound
interpretation.
sophisticated
structural
proteins
which
maintain
unique
high
precision
physical
detection,
transmittance
interpretation
hearing
process
important.
maintenance
material
essential
transmission
processes.
Specific,
emerging
low
sulfation
bioregulation
contrasted
with
charge
density
isoforms.
Some
speculations
made
on
how
molecular
electrical
may
potential
application
futuristic
nanoelectronic,
memristor
technology
advanced
ultrafast
computing
devices
energy
requirements
nanomachines,
nanobots
or
switches
could
potentially
useful
artificial
synapse
development.
Application
such
innovative
areas
eagerly
awaited.
Applied Physics Reviews,
Год журнала:
2024,
Номер
11(4)
Опубликована: Окт. 9, 2024
Synaptic
transistors,
which
emulate
the
behavior
of
biological
synapses,
play
a
vital
role
in
information
processing
and
storage
neuromorphic
systems.
However,
occurrence
excessive
current
spikes
during
updating
synaptic
weight
poses
challenges
to
stability,
accuracy,
power
consumption
transistors.
In
this
work,
we
experimentally
investigate
main
factors
for
generation
three-terminal
transistors
that
use
LiCoO2
(LCO),
mixed
ionic-electronic
conductor,
as
channel
layer.
Kelvin
probe
force
microscopy
impedance
testing
results
reveal
ion
migration
adsorption
at
drain–source-channel
interface
cause
compromise
device's
performance.
By
controlling
crystal
orientation
LCO
layer
impede
in-plane
lithium
ions,
show
with
(104)
preferred
can
effectively
suppress
both
peak
Our
study
provides
unique
insight
into
crystallographic
design
high-speed,
high-robustness,
low-power
nano-memristor
devices.
Dalton Transactions,
Год журнала:
2024,
Номер
53(35), С. 14610 - 14622
Опубликована: Янв. 1, 2024
This
study
explores
the
impact
of
organic
cations
in
bismuth
iodide
complexes
on
their
memristive
behavior
metal–insulator–metal
(MIM)
type
thin-layer
devices.
