Journal of the American Chemical Society,
Год журнала:
2025,
Номер
unknown
Опубликована: Май 11, 2025
Memristors
have
been
positioned
at
the
forefront
of
purposes
for
carrying
out
neuromorphic
computation.
Their
tunable
conductance
properties
enable
imitation
synaptic
behavior.
Nanofluidic
memristors
made
multipore
membranes
shown
their
memristic
and
are
candidate
devices
liquid
systems.
Such
visible
through
an
inductive
hysteresis
in
current-voltage
sweeps,
which
is
then
confirmed
by
characteristics
impedance
spectroscopy
measurements.
The
dynamic
behavior
largely
determined
a
voltage-dependent
relaxation
time.
Here,
we
obtain
kinetic
time
nanofluidic
memristor
via
its
spectra,
modeling
it
deriving
general
equation
this
as
function
applied
voltage,
fully
correlated
with
system's
internal
parameters.
We
show
that
characteristic
comparable
to
natural
neural
Hence,
open
way
study
mimic
neuron
searching
same
times.
Abstract
Iontronic
fluidic
ionic/electronic
components
are
emerging
as
promising
elements
for
artificial
brain‐like
computation
systems.
Nanopore
ionic
rectifiers
can
be
operated
a
synapse
element,
exhibiting
conductance
modulation
in
response
to
train
of
voltage
impulses,
thus
producing
programmable
resistive
states.
We
propose
model
that
replicates
hysteresis,
rectification,
and
time
domain
properties,
based
on
between
two
conducting
modes
relaxation
the
state
variable.
show
kinetic
effects
observed
hysteresis
loops
govern
potentiation
phenomena
related
conductivity
modulation.
To
illustrate
efficacy
model,
we
apply
it
replicate
different
experimental
systems:
polymer
membrane
with
conical
pores,
blind‐hole
nanoporous
anodic
alumina
barrier
oxide
layer.
transient
analysis
develops
depression
synaptic
properties.
ACS Applied Materials & Interfaces,
Год журнала:
2024,
Номер
16(43), С. 58818 - 58826
Опубликована: Окт. 18, 2024
Solid-state
nanochannels
have
emerged
as
a
promising
platform
for
the
development
of
ionic
circuit
components
with
analog
properties
to
their
traditional
electronic
counterparts.
In
last
years,
nanofluidic
devices
memristive
attracted
special
interest
due
applicability
in,
example,
construction
brain-like
computing
systems.
this
work,
an
asymmetric
track-etched
channel
memory-enhanced
ion
transport
is
reported.
The
results
illustrate
that
formation
nanoprecipitates
on
walls
induces
memory
effects
in
transport,
leading
characteristic
hysteresis
loops
current–voltage
curves,
hallmark
behavior.
Notably,
these
are
achievable
straightforward
experimental
setup
combines
aqueous
solvent
and
relatively
low-soluble
inorganic
salt.
various
conductance
states
can
be
rapidly
reversibly
tuned
over
prolonged
time
scales.
Furthermore,
under
appropriate
measurement
conditions,
device
alternate
between
different
iontronic
regimes
states,
encompassing
current
rectification,
ON–OFF
memristor-like
These
findings
provide
insights
into
design
optimization
bioinspired
components.
Nano Letters,
Год журнала:
2024,
Номер
24(34), С. 10475 - 10481
Опубликована: Авг. 8, 2024
Memristors
show
promising
features
for
neuromorphic
computing.
Here
we
report
a
soft
memristor
based
on
the
liquid–vapor
surface
of
microbubble.
The
thickness
liquid
film
was
modulated
by
electrostatic
and
interfacial
forces,
enabling
resistance
switches.
We
found
pinched
current
hysteresis
at
scanning
periods
between
1.6
51.2
s,
while
representing
resistor
below
s
diode-like
behavior
above
s.
approximate
thickening/thinning
dynamics
pressure-driven
flow
interface
derived
impacts
salt
concentration
voltage
amplitude
memory
effects.
Our
work
opens
new
approach
to
building
nanofluidic
memristors
interface,
which
may
be
useful
types
computing
in
future.
The
fast
development
of
artificial
intelligence
and
big
data
drives
the
exploration
low-power
computing
hardware.
Neuromorphic
devices
represented
by
memristors
may
provide
a
possible
paradigm
beyond
von
Neumann's
architecture
because
they
enable
integration
processing
storage
units
mimicking
how
brain
processes
complex
information
in
parallel.
In
brain,
is
processed
via
multilevel
spiking
coding
event-driven
mechanisms,
whose
simplified
neural
circuit
leaky-integration-and-fire
model
combining
volatile
threshold
switching
capacitors.
As
unit
to
emulate
working
environment
explore
unique
functions
ions
molecules
biological
systems,
nanofluidic
ionic
become
essential
but
are
still
missing.
This
Perspective
will
review
mechanism
role
as
building
block
for
neuromorphic
list
three
routes
ones.
Abstract
Transport
of
ions
and
water
is
essential
for
diverse
physiological
activities
industrial
applications.
As
the
dimension
approaches
nano
even
angstrom
scale,
exhibit
anomalous
behaviors
that
differ
significantly
from
bulk.
One
key
reasons
these
distinctive
prominent
influence
surface
effects
related
transport
properties
occurring
at
interface
under
such
(sub)nanoconfinement.
Therefore,
exploring
nanofluidic
interfaces
could
not
only
contribute
to
unraveling
intriguing
ion
but
also
facilitate
development
devices
with
tunable
mass
practical
In
this
review,
we
focus
on
three
crucial
governing
transport,
namely
liquid–gas
interface,
liquid–solid
liquid–liquid
emphasis
elucidating
their
intricate
interfacial
structures
critical
roles
phenomena.
Additionally,
potential
applications
associated
liquid–gas,
liquid–solid,
are
discussed.
Finally,
present
a
perspective
pivotal
nanofluidics,
as
well
challenges
in
advancing
field.
Reproducing
neural
functions
with
artificial
nanofluidic
systems
has
long
been
an
aspirational
goal
for
neuromorphic
computing.
In
this
study,
functions,
such
as
activation
and
synaptic
plasticity,
are
successfully
accomplished
a
polarity-switchable
memristor
(PSNM),
which
is
based
on
the
anodized
aluminum
oxide
(AAO)
nanochannel
array.
The
PSNM
unipolar
memristive
behavior
at
high
electrolyte
concentrations
bipolar
low
concentrations,
can
emulate
respectively.
mechanisms
behaviors
related
to
polyelectrolytic
Wien
(PEW)
effect
ion
accumulation/depletion
effect,
These
findings
beneficial
advancement
of
computing
platforms.
Synaptic
plasticity,
the
dynamic
tuning
of
signal
transmission
strength
between
neurons,
serves
as
a
fundamental
basis
for
memory
and
learning
in
biological
organisms.
This
adaptive
nature
synapses
is
considered
one
key
features
contributing
to
superior
energy
efficiency
brain.
Here,
we
use
molecular
dynamics
simulations
demonstrate
synaptic-like
plasticity
subnanoporous
two-dimensional
membrane.
We
show
that
train
voltage
spikes
dynamically
modifies
membrane’s
ionic
permeability
process
involving
competitive
bicationic
transport.
shown
be
repeatable
after
given
resting
period.
Because
combination
subnanometer
pore
size
atomic
thinness
membrane,
this
system
exhibits
dissipation
0.1
100
aJ
per
spike,
which
several
orders
magnitude
lower
than
10
fJ
spike
human
synapse.
reveal
underlying
physical
mechanisms
at
detail
investigate
local
energetics
apparent
behavior.
Proceedings of the National Academy of Sciences,
Год журнала:
2025,
Номер
122(10)
Опубликована: Март 5, 2025
The
fluidic
memristor
has
attracted
growing
attention
as
a
promising
candidate
for
neuromorphic
computing
and
brain-computer
interfaces.
However,
with
ion
selectivity
that
of
natural
channels
remains
key
challenge.
Herein,
inspired
by
the
structure
biomembranes,
we
developed
an
ion-shuttling
(ISM)
utilizing
organic
solvents
artificial
carriers
to
emulate
embedded
in
which
exhibited
both
functions
selectivity.
Pinched
hysteresis
I-V
loop
curve,
scan
rate
dependency,
distinctive
impedance
spectra
confirmed
memristive
characteristics
as-prepared
device.
Moreover,
memory
mechanism
was
discussed
theoretically
validated
finite-element
modeling.
ISM
features
multiple
functions,
such
paired-pulse
facilitation,
depression,
learning-experience
behavior.
More
importantly,
observed,
allowed
further
emulation
ion-selective
neural
like
resting
membrane
potential.
Benefiting
from
structural
similarity
membrane-embedded
channels,
opens
door
ion-based
sophisticated
chemical
regulation
manipulating
multifarious
ions
functions.
