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
Deciphering Mechanisms of Oxygen Vacancy Conducting Channel-Based LiSiOx Artificial Nociceptors
Z.Y. Li,
Yao Shi,
Dianyou Song
и другие.
Vacuum,
Год журнала:
2025,
Номер
unknown, С. 114296 - 114296
Опубликована: Март 1, 2025
Язык: Английский
Flexible Memristor Based on Lead‐Free Cs2AgBiBr6 Perovskite for Artificial Nociceptors and Information Security
Advanced Functional Materials,
Год журнала:
2024,
Номер
unknown
Опубликована: Сен. 9, 2024
Abstract
The
emergence
of
the
artificial
intelligence
urgently
requires
novel
devices
to
handle
massive
data
and
bionic
simulations.
As
one
new
generation
memory
devices,
memristor
has
great
potential
in
information
storage
brain‐like
learning
due
its
merits,
such
as
low
energy
consumption,
high
speed
etc.
In
addition,
randomness
for
breakage
conducting
filaments
can
generate
true
random
numbers
realize
image
encryption.
this
work,
ITO/Cs
2
AgBiBr
6
/Al
based
exhibit
prominent
resistance
variation
characteristics
long‐term
environmental
stability
(≥6
months).
Additionally,
flexible
PET/ITO/Cs
are
assembled
measured
properties,
which
adopt
cryptographic
processing
information.
synaptic
plasticity
is
also
verified,
including
paired
pulse
facilitation
spiking
timing‐dependent
plasticity.
Finally,
nociceptive
responses
simulated
with
via
imposing
different
voltage.
Nociceptive
“threshold,”
“relaxation,”
“sensitization”
have
been
successfully
determined.
work
provides
possibility
lead‐free
perovskite
memristors
security
biomimicry.
Язык: Английский
Performance improvement of bilayer memristor based on hafnium oxide by Ti/W synergy and its synaptic behavior
Vacuum,
Год журнала:
2024,
Номер
227, С. 113392 - 113392
Опубликована: Июнь 12, 2024
Язык: Английский
Artificial pain-perceptual nociceptor emulation based on graphene oxide synaptic transistors
Chemical Engineering Journal,
Год журнала:
2024,
Номер
498, С. 155571 - 155571
Опубликована: Сен. 7, 2024
Язык: Английский
A pectin-based artificial nociceptor enabling actual tactile perception
Journal of Materials Chemistry C,
Год журнала:
2024,
Номер
unknown
Опубликована: Янв. 1, 2024
This
work
focuses
on
biocompatible
material-pectin
based
artificial
nociceptor
design,
successfully
mimicking
four
basic
pain
perception
characteristics
and
validating
tactile
functions
by
constructing
a
sensing
system.
Язык: Английский
Dual‐Electrolyte Neuromorphic Transistor for Risk Detection and Image Processing
Advanced Materials Technologies,
Год журнала:
2024,
Номер
unknown
Опубликована: Ноя. 30, 2024
Abstract
The
human
brain
is
a
highly
efficient
structure
that
can
easily
perform
various
complex
tasks,
such
as
shape
recognition,
presentation,
and
classification,
while
consuming
minimal
energy
occupying
only
small
volume.
This
study
introduces
bio‐inspired
electrolyte‐gated
neuromorphic
transistor
mimics
the
functionality
of
brain.
A
dual‐electrolyte
combining
lithium
phosphorus
oxynitride
silicate
achieves
best
performance,
with
mobility
3.1
cm
2
V
−1
s
,
paired‐pulse
facilitation
index
162.6%,
nonlinearity
coefficients
0.02
0.03
(for
potentiation
depression,
respectively).
Further,
risk
pre‐detection
image
recognition
are
successfully
demonstrated
using
developed
synaptic
transistors.
test
conducted
on
Modified
National
Institute
Standards
Technology
database
indicates
an
accuracy
91.0%.
Thus,
device
has
potential
to
advance
artificial
vision
systems.
Язык: Английский