Reconfigurable Al2O3-Based Memristor for All-in-One Artificial Synapse and Nociceptor Neurons
The Journal of Physical Chemistry Letters,
Год журнала:
2025,
Номер
unknown, С. 2722 - 2730
Опубликована: Март 6, 2025
Multifunctional
bionic
devices
have
widespread
applications
in
neuromorphic
computing,
intelligent
sensors,
and
robotics.
The
inherent
properties
of
memristors
make
them
suitable
for
these
emerging
applications,
but
different
require
either
volatile
or
nonvolatile
operations
a
unique
device.
In
this
work,
we
developed
novel
reconfigurable
Ag/Al2O3/ITO
memristor,
which
achieves
adjustable
switching
behavior
between
by
modulating
the
compliance
current.
A
proposed
mechanism
controls
state
conductive
filaments
device
adjusting
current,
elucidating
process
states.
Additionally,
synaptic
functionality
nociceptor
characteristics,
including
threshold,
relaxation,
inadaptation,
sensitization,
been
successfully
simulated.
This
integration
artificial
functions
into
single
is
achieved,
with
single-pulse
power
consumption
reaching
as
low
0.912
nJ
when
threshold
reached.
These
results
provide
insights
construction
multifunctional
demonstrate
significant
potential
future
network
applications.
Язык: Английский
Leveraging Dual Resistive Switching in Quasi-2D Perovskite Memristors for Integrated Non-volatile Memory, Synaptic Emulation, and Reservoir Computing
ACS Applied Materials & Interfaces,
Год журнала:
2025,
Номер
unknown
Опубликована: Март 19, 2025
The
increasing
computational
demands
of
artificial
intelligence
(AI)
algorithms
are
exceeding
the
capabilities
conventional
computing
architectures,
creating
a
strong
need
for
novel
materials
and
paradigms.
Memristors
that
integrate
diverse
resistive
switching
(RS)
behaviors
provide
promising
avenue
developing
architectures.
In
this
study,
we
achieve
coexistence
volatile
nonvolatile
RS
in
quasi-2D
perovskite
memristor
(Q-2DPM).
Q-2DPM
exhibits
competitive
performance
as
memory.
Multiple
synaptic
functions
have
been
successfully
simulated
on
Q-2DPM,
such
excitatory
postsynaptic
currents,
paired-pulse
facilitation,
long-term
potentiation/depression.
Furthermore,
neural
networks
using
synapses
high
accuracy
MNIST
image
classification
tasks.
Q-2DPM's
inherent
characteristics
suitable
reservoir
also
demonstrated
through
its
application
pulse-stream-based
digital
experiment,
showcasing
impressive
performance.
elucidation
dual
mechanisms
within
provides
fresh
insights
into
behavior
underscores
potential
achieving
units
single
device.
This
work
paves
way
implementation
physical
neuromorphic
hardware
architectures
advancement
sophisticated
primitives,
offering
significant
step
toward
next
generation
technologies.
Язык: Английский
Kinetics of Volatile and Nonvolatile Halide Perovskite Devices: The Conductance-Activated Quasi-Linear Memristor (CALM) Model
The Journal of Physical Chemistry Letters,
Год журнала:
2024,
Номер
unknown, С. 69 - 76
Опубликована: Дек. 19, 2024
Memristors
stand
out
as
promising
components
in
the
landscape
of
memory
and
computing.
are
generally
defined
by
a
conductance
mechanism
containing
state
variable
that
imparts
effect.
The
current–voltage
cycling
causes
transitions
conductance,
which
determined
different
physical
mechanisms,
such
formation
conducting
filaments
an
insulating
surrounding.
Here,
we
provide
unified
description
set
reset
processes
using
conductance-activated
quasi-linear
memristor
(CALM)
model
with
unique
voltage-dependent
relaxation
time
variable.
We
focus
on
halide
perovskite
memristors
their
intersection
neuroscience-inspired
show
modeling
approach
adeptly
replicates
experimental
traits
both
volatile
nonvolatile
memristors.
Its
versatility
extends
across
various
device
materials
configurations,
W/SiGe/a-Si/Ag,
Si/SiO2/Ag,
SrRuO3/Cr-SrZrO3/Au
memristors,
capturing
nuanced
behaviors
scan
rate
upper
vertex
dependence.
also
describes
response
to
sequences
voltage
pulses
cause
synaptic
potentiation
effects.
This
is
potent
tool
for
comprehending
probing
dynamical
indicating
properties
control
observable
responses.
Язык: Английский
Microstructure-modulated conductive filaments in Ruddlesden-Popper perovskite-based memristors and their application in artificial synapses
Materials Today Physics,
Год журнала:
2025,
Номер
unknown, С. 101708 - 101708
Опубликована: Март 1, 2025
Язык: Английский
DFT insights on the chloride double perovskites X2AuBiCl6 (X = K, Rb, and Cs) with semiconductor nature for PV and optoelectronic applications
Computational Condensed Matter,
Год журнала:
2025,
Номер
unknown, С. e01040 - e01040
Опубликована: Апрель 1, 2025
Язык: Английский
Coupling Light into Memristors: Advances in Halide Perovskite Resistive Switching and Neuromorphic Computing
Small Methods,
Год журнала:
2025,
Номер
unknown
Опубликована: Апрель 25, 2025
Abstract
Resistive
switching
memristor
is
an
emerging
nonvolatile
memory
technology
designed
to
overcome
the
physical
limitations
of
conventional
systems
and
performance
bottleneck
von
Neumann
architecture.
Notably,
halide
perovskite
(HP)‐based
memristors
have
gained
significant
attention
in
recent
years
due
their
unique
ionic
migration
behavior
exceptional
photoelectric
properties.
This
review
highlights
HP‐based
resistive
switching,
focusing
on
its
developments
coupling
light
into
discussing
implications
for
neuromorphic
computing.
The
mechanisms
are
explored
alongside
role
HP
properties
enhancing
dynamics.
advantages
applications
light‐coupled
including
reduced
voltage,
enhanced
operation
reliability,
multilevel
capability,
development
light‐integrated
artificial
synapses
discussed
comprehensively.
By
fully
harnessing
optoelectronic
HPs,
this
field
may
pave
way
innovative
approaches
technologies
light‐responsive
systems.
Язык: Английский
Electrochemical Doping of Halide Perovskites with Silver Interstitial Ions: Mechanistic Insights and Enhanced Performance in Memristor Applications
The Journal of Physical Chemistry Letters,
Год журнала:
2025,
Номер
unknown, С. 4480 - 4488
Опубликована: Апрель 26, 2025
Halide
perovskites
have
garnered
significant
attention
for
their
exceptional
carrier
mobility,
balanced
bipolar
transport
properties,
and
ion-electron
mixing
conductivity,
making
them
highly
promising
applications,
such
as
solar
cells,
photodetectors,
memristors.
Despite
potential,
intrinsic
ions
defects
within
these
materials
complicate
effective
doping,
interactions
between
metal
electrodes
perovskite
can
trigger
interfacial
chemical
reactions
that
compromise
device
stability
performance.
This
study
examines
the
influence
of
Ag
on
devices,
specifically
investigating
n-doping
effects
Agi+
interstitial
in
MAPbI3
through
an
integrated
approach
combining
first-principles
density
functional
theory
(DFT)
calculations
experimental
analysis.
Findings
reveal
ions,
generated
electrochemically
at
electrodes,
penetrate
structure
migrate
under
applied
electric
field,
achieving
stable
controlled
bias
conditions.
Detailed
characterization
doping
process
was
conducted
using
current
density-time
(J-t)
measurements,
electrochemical
AC
impedance
(EIS),
TOF-SIMS/XPS
depth
profiling,
temperature/illumination-dependent
studies.
Additionally,
memristive
behavior
device,
including
mechanisms
formation
metallic
conductive
filaments,
demonstrated,
offering
insights
into
its
potential
applications
advanced
electronics.
These
findings
elucidate
physicochemical
metal-perovskite
interfaces
diode
devices.
Язык: Английский
A balanced view of ion migration in halide perovskite electronics
Newton,
Год журнала:
2025,
Номер
1(3), С. 100096 - 100096
Опубликована: Май 1, 2025
Язык: Английский
Unveiling the potential of all-inorganic perovskite memristors for neuromorphic and logic applications
Journal of Energy Chemistry,
Год журнала:
2025,
Номер
unknown
Опубликована: Май 1, 2025
Язык: Английский
Emerging materials for resistive switching memories: Prospects for enhanced sustainability and performance for targeted applications
APL Energy,
Год журнала:
2024,
Номер
2(4)
Опубликована: Дек. 1, 2024
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.
Язык: Английский