Crystals,
Год журнала:
2025,
Номер
15(6), С. 538 - 538
Опубликована: Июнь 5, 2025
The
relationship
between
structure
and
properties
is
fundamental
in
materials
science,
particularly
for
aliovalently
doped
perovskites,
where
structural
changes
significantly
influence
material
performance.
Accurate
prediction
of
key
parameters
essential
tailoring
these
advanced
applications.
In
this
study,
we
developed
an
Artificial
Neural
Network
(ANN)
model
to
predict
lattice
constants
with
high
accuracy,
achieving
near-perfect
R2
values
minimal
errors
across
training
testing
datasets.
To
address
the
interpretability
challenge
commonly
associated
black-box
models,
integrated
Partial
Dependence
Plots
(PDPs),
enabling
a
transparent
analysis
how
input
features,
including
a,
b,
c,
number
formula
units
per
unit
cell
(Z),
affect
predictions.
Our
findings
show
that
c
generally
contribute
expansion,
while
Z
exhibits
inverse
due
its
impact
on
packing
density.
inclusion
PDPs
offers
novel
insights
into
underlying
physical
relationships
enhances
trustworthiness
machine
learning
(ML)
predictions
context
perovskite
design.
This
approach
demonstrates
utility
combining
high-accuracy
ML
models
techniques
accelerate
discovery
science.
Inorganic Chemistry Frontiers,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 1, 2025
Multidentate
chelating
passivation
via
DIP
molecules
significantly
reduces
the
surface
trap
density,
improves
carrier
transport,
and
achieves
an
efficiency
of
23.68%.
Polymers for Advanced Technologies,
Год журнала:
2025,
Номер
36(3)
Опубликована: Март 1, 2025
ABSTRACT
Electrochromic
energy
storage
devices
(EESDs)
have
emerged
as
innovative
technologies
in
and
smart
materials,
generating
considerable
interest
for
numerous
applications,
such
wearables,
windows,
color‐changing
sunglasses.
EESDs
consist
of
two
primary
categories:
electrochromic
supercapacitors
(ESCs)
batteries
(ECBs).
These
are
particularly
appreciated
their
multifunctional
features,
which
allow
them
to
alter
color
response
different
charge
densities.
The
performance
efficiency
rely
on
three
essential
components:
(I)
the
current
collector
or
substrate
(cc/substrate),
serves
conductive
base
device;
(II)
electrolyte,
supports
ion
movement
improves
overall
electrochemical
performance;
(III)
materials
(ECMs),
responsible
changes
functions.
Careful
selection
optimization
these
components
crucial
enhancing
devices'
efficiency,
stability,
lifespan.
Advanced
flexible
stretchable
shown
significant
potential.
Their
natural
flexibility
facilitates
seamless
incorporation
into
curved
surfaces
diverse
shapes,
making
especially
suitable
wearable
other
cutting‐edge
applications.
However,
this
also
brings
challenges,
including
concerns
related
delamination,
material
dissociation,
degradation
over
time.
A
thorough
investigation
is
progressing
conversion
systems.
Grasping
vital
creating
sustainable
solutions
improving
capabilities.
Nanomaterials,
Год журнала:
2025,
Номер
15(7), С. 534 - 534
Опубликована: Апрель 1, 2025
Maghemite
(γ-Fe2O3)
nanoparticles
have
attracted
considerable
interest
for
electronic
applications
due
to
their
tunable
electrical
properties.
Doping
strategies
offer
an
effective
way
optimize
resistive
behavior
use
in
devices.
In
this
study,
cobalt
(Co)
was
incorporated
into
γ-Fe2O3
enhance
its
X-ray
diffraction
(XRD)
confirmed
the
retention
of
cubic
P4332
phase,
with
Co
doping
inducing
subtle
lattice
distortions
ionic
substitution.
Scanning
and
transmission
electron
microscopy
(SEM/TEM)
revealed
morphological
changes,
where
incorporation
influenced
particle
shape
size
distribution.
Electrical
conductivity
analysis
demonstrated
a
decrease
both
AC
DC
increase
content,
indicating
enhanced
behavior.
The
activation
energy
suggests
reduction
charge
carrier
mobility,
leading
higher
resistivity.
Impedance
spectroscopy
further
increased
real
imaginary
impedance
values,
reinforcing
role
suppressing
transport.
These
results
position
cobalt-doped
maghemite
as
promising
material
devices,
such
resistors
negative
temperature
coefficient
(NTC)
thermistors,
controlled
stable
are
essential.
