Advanced Materials Technologies,
Journal Year:
2024,
Volume and Issue:
9(16)
Published: July 20, 2024
Abstract
The
rapid
advancement
of
neuromorphic
computing
demands
innovative
hardware
solutions
capable
efficiently
mimicking
the
functionality
biological
neural
systems.
In
this
context,
dynamic
memristors
have
emerged
as
promising
candidates
for
realizing
reservoir
(RC)
architectures.
characterized
by
their
ability
to
exhibit
nonlinear
conductance
variations
and
transient
memory
behaviors
offer
unique
advantages
constructing
RC
Unlike
recurrent
networks
(RNNs)
that
face
challenges
such
vanishing
or
exploding
gradients
during
training,
leverages
a
fixed‐size
layer
acts
memory.
Researchers
can
capitalize
on
adaptable
efficient
characteristics
integrating
into
systems
enable
information
processing
with
low
learning
costs.
This
perspective
provides
an
overview
recent
developments
in
applications
RC.
It
highlights
potential
revolutionize
artificial
intelligence
offering
faster
speeds
enhanced
energy
efficiency.
Furthermore,
it
discusses
opportunities
associated
architectures,
paving
way
developing
next‐generation
cognitive
Physical review. E,
Journal Year:
2024,
Volume and Issue:
109(4)
Published: April 24, 2024
We
demonstrate
that
nanofluidic
diodes
in
multipore
membranes
show
a
memristive
behavior
can
be
controlled
not
only
by
the
amplitude
and
frequency
of
external
signal
but
also
series
parallel
arrangements
membranes.
Each
memristor
consists
polymeric
membrane
with
conical
nanopores
allow
current
rectification
due
to
electrical
interaction
between
ionic
solution
pore
surface
charges.
This
charge-regulated
transport
shows
rich
nonlinear
physics,
including
memory
inductive
effects,
which
are
characterized
here
current-voltage
curves
impedance
spectroscopy.
Also,
neuromorphiclike
potentiation
conductance
following
voltage
pulses
(spikes)
is
observed.
The
physical
concepts
should
have
application
for
information
processing
conversion
iontronics
hybrid
devices.
Advanced Functional Materials,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Sept. 2, 2024
Abstract
To
achieve
cost‐effectiveness,
researchers
are
exploring
various
memristors
for
their
adaptation
in
neuromorphic
computing.
Recent
studies
have
focused
on
developing
versatile
functioning
singular
memristors,
such
as
those
involved
on‐receptor
computing,
which
integrates
sensory
functions
into
current
computing
paradigms.
Additionally,
adaptations
like
reservoir
being
investigated
systems.
In
this
study,
a
memristor
composed
of
stack
Ti/NbO
x
/Pt
layers
is
fabricated
to
explore
multifunctional
behaviors
within
single
memristor.
By
applying
bias
toward
the
top
Ti
electrode,
gradual
changes
with
volatile
features
demonstrated,
revealing
an
ion‐migration‐based
nonfilamentary
switching
Leveraging
functionality,
artificial
nociceptor
first
implemented,
demonstrating
key
biological
nociceptors
including
thresholding,
relaxation,
no‐adaptation,
and
sensitization.
Subsequently,
synapse
emulation
akin
brain
achieved
through
easy
conductance
potentiation
depression
diverse
functions,
enabling
mimic
learning
activities
spike
firing.
Lastly,
computational
applications
explored
by
adapting
edge
multi‐bit
expanding
memristor's
across
fields
behaviors.
Journal of Applied Physics,
Journal Year:
2025,
Volume and Issue:
137(4)
Published: Jan. 23, 2025
Conventional
computing
architectures
are
not
suited
to
meet
the
unique
workload
requirements
of
artificial
intelligence
and
deep
learning,
which
has
sparked
a
growing
interest
in
memory-centric
computing.
One
primary
challenge
this
field
is
sneak
path
current
memory
devices,
degrades
data
storage
reliability.
Another
critical
issue
ensuring
device
performance
stability
over
time
under
varying
environmental
conditions.
To
overcome
these
challenges,
work,
we
introduce
Dion–Jacobson
perovskite-based
self-rectifying
cell
that
only
reduces
but
also
demonstrates
remarkable
electrical
parameters.
The
fabricated
maintains
consistent
performance,
including
rectification
ratio
(∼103),
on/off
set
voltage
(∼0.52
V),
for
200+
days
within
temperature
range
25–70
°C
relative
humidity
conditions
up
70%RH.
Importantly,
our
work
represents
an
innovative
step
forward
observation
self-rectification
stable
showing
way
their
widespread
application
architectures.
Furthermore,
understand
behavior
across
its
different
states,
i.e.,
high
resistance
state
low
state,
electrochemical
impedance
spectroscopy
performed,
gives
insight
into
individual
contribution
resistance,
capacitance,
inductance.
Advanced Intelligent Systems,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Feb. 17, 2025
In‐sensor
reservoir
computing
has
recently
gained
considerable
attention
for
its
efficient
training
process
and
advanced
integration
of
sensing,
storage,
processing
functionalities.
However,
developing
a
highly
in‐sensor
system
remains
challenging,
mainly
due
to
the
lack
suitable
devices
with
appropriate
architectures.
In
this
study,
graphene/MoSe
2
‐based
ohmic
contact
optoelectronic
synaptic
memory
device
optimized
(RC)
is
introduced,
designed
emulate
biological
functions
enable
neuromorphic
computing.
Based
on
dynamic
characteristics
fading
device,
gesture
recognition,
including
six
types
gestures,
stimulated,
achieving
recognition
rate
95%.
This
work
provides
potential
solution
hardware‐software
co‐design
in
recognition.
Advanced Electronic Materials,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Jan. 13, 2025
Abstract
Brain‐inspired
(or
neuromorphic)
computing
circumvents
costly
bottlenecks
in
conventional
Von
Neumann
architectures
by
collocating
memory
and
processing.
This
is
accomplished
through
dynamic
material
architectures,
strengthening
or
weakening
internal
conduction
pathways
similar
to
synaptic
connections
within
the
brain.
A
new
class
of
neuromorphic
materials
approximates
interfaces
using
lipid
membranes
assembled
via
droplet
interface
bilayer
(DIB)
technique.
These
DIB
have
been
studied
as
novel
memristors
memcapacitors
owing
soft,
reconfigurable
nature
both
membrane
geometry
embedded
ion‐conducting
channels.
In
this
work,
a
biomolecular
approach
expanded
from
model
synapses
charge‐integrating
neuron
.
these
serial
networks,
it
possible
create
distributions
voltage‐sensitive
gates
capable
trapping
ionic
charge.
trapped
charge
creates
transmembrane
potential
differences
that
drive
changes
system's
net
capacitance
electrowetting,
providing
weight
response
history
timing
input
signals.
fundamental
change
interfacial
(dimensions
membrane)
(charge
droplets)
provides
functional
plasticity
multiple
weights,
longer‐term
retention
roughly
an
order
magnitude
greater
than
stored
alone,
programming‐erasure.
Advanced Functional Materials,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Feb. 19, 2025
Abstract
In
this
study,
a
highly
rectifying
memristor
composed
of
Pt/TaO
x
/TiN
stack,
incorporating
complementary
metal‐oxide
semiconductor‐friendly
metal
oxide
switching
layer,
is
fabricated
to
assess
its
performance
in
diverse
range
applications.
The
exhibits
characteristics
due
the
Schottky
barrier
formed
by
work
function
difference
between
Pt
and
TiN
electrodes.
For
compliance
current
1
mA,
displays
volatile
memory
properties,
attributed
migration
oxygen
ions
within
TaO
layer.
Leveraging
behavior,
synaptic
functions—where
changes
plasticity
occur
response
incoming
spikes—are
emulated.
Additionally,
complete
functions
biological
nociceptor
are
demonstrated,
including
threshold,
relaxation,
no‐adaptation,
sensitization,
recovery.
These
dynamic
then
utilized
mimic
neuronal
firing
with
array,
Morse
code
implementation
enabling
data
generation,
computing
through
cost‐effective
reservoir
computing.
simplicity
fabrication
process
broad
implemented
single
make
device
promising
candidate
for
future
Science Advances,
Journal Year:
2025,
Volume and Issue:
11(13)
Published: March 26, 2025
Traditional
robotic
vehicle
control
algorithms,
implemented
on
digital
devices
with
firmware,
result
in
high
power
consumption
and
system
complexity.
Advanced
systems
based
different
device
physics
are
essential
for
the
advancement
of
sophisticated
vehicles
miniature
mobile
robots.
Here,
we
present
a
nanoelectronics-enabled
analog
mimicking
conventional
controllers’
dynamic
responses
real-time
controls,
substantially
reducing
training
cost,
consumption,
footprint.
This
uses
reservoir
computing
network
interconnected
memristive
channels
made
from
layered
semiconductors.
The
network’s
nonlinear
switching
short-term
memory
characteristics
effectively
map
input
sensory
signals
to
high-dimensional
data
spaces,
enabling
generation
motor
simply
trained
readout
layer.
approach
minimizes
software
analog-to-digital
conversions,
enhancing
energy
resource
efficiency.
We
demonstrate
this
two
tasks:
rover
target
tracking
drone
lever
balancing,
achieving
similar
performance
traditional
controllers
~10-microwatt
consumption.
work
paves
way
ultralow-power
edge
systems.
The Innovation Materials,
Journal Year:
2025,
Volume and Issue:
unknown, P. 100127 - 100127
Published: Jan. 1, 2025
<p>Reservoir
computing
has
emerged
as
an
efficient
computational
paradigm
for
processing
temporal
and
dynamic
data,
driving
advancements
in
neuromorphic
electronics
physical
implementation.
This
review
covers
the
devices
implementing
reservoir
computing,
emphasizing
device-level
innovations
that
address
challenges
of
low-latency,
energy-efficient,
multimodal
implementations.
The
advantages,
disadvantages,
core
various
spatial
architectures
building
systems
are
discussed.
Realistic
paths
on
algorithmic
implementations
input
output
layers
system
investigated,
issues
such
heterogeneous
device
integration,
consistent
readout,
stability
analyzed.
topical
emphasizes
reconfigurability
scalability
fully
analogized
adaptive
nodes.
We
discuss
future
directions
across
algorithmic,
device,
architectural,
application
domains.
establishes
a
foundational
framework
provides
strategic
guidance
edge
artificial
intelligent
systems.</p>