Advanced Functional Materials,
Journal Year:
2025,
Volume and Issue:
unknown
Published: April 24, 2025
Abstract
Kesterite
Cu
2
ZnSn(S,Se)
4
(CZTSSe)
has
emerged
as
a
highly
promising
photovoltaic
material
because
of
its
environmentally
friendly
characteristics
and
low
cost.
However,
multicomponent
inorganic
semiconductor
material,
the
complex
nature
CZTSSe
leads
to
disorder
in
crystallization
reaction
process
at
high‐temperature
selenization,
resulting
numerous
antisite
defects
that
cause
significant
non‐radiative
recombination
open
circuit
voltage
loss
final
device.
Therefore,
it
is
great
challenge
fabricate
high‐quality
absorbers
with
homogeneous
chemical
composition
uniform
cation
distribution
for
achieving
high‐efficiency
solar
cells.
Herein,
synergistic
have
been
successfully
realized
via
temperature‐modulated
nucleation
strategy.
This
strategy
effectively
more
sites
larger
nuclei
sizes
thin
films
distribution.
As
result,
cells
over
14%
realized.
work
reveals
mechanism
nucleation,
providing
simple
feasible
route
ChemistrySelect,
Journal Year:
2025,
Volume and Issue:
10(17)
Published: April 29, 2025
Abstract
This
study
introduces
a
swift
framework
utilizing
machine
learning
(ML)
techniques
to
design
dyes.
The
involves
training
of
ML
models
predict
oscillator
strength.
Subsequently,
employing
the
breaking
retrosynthetically
interesting
chemical
substructures
(BRICS)
methodology,
10,000
new
dyes
are
generated,
and
their
strength
values
forecasted
using
pre‐trained
model.
Dyes
with
higher
predicted
retained
for
further
consideration.
To
make
future
experiments
easier,
synthetic
accessibility
these
chosen
is
also
assessed.
structural
diversity
among
investigated,
revealing
high
degree
variation.
Advanced Theory and Simulations,
Journal Year:
2025,
Volume and Issue:
unknown
Published: May 3, 2025
Abstract
The
discovery
of
polymers
with
high
dielectric
constants
is
significant
interest
for
advanced
electronic
applications,
such
as
capacitors,
flexible
electronics,
and
energy
storage
devices.
In
this
study,
data
mining
machine
learning
(ML)
techniques
are
applied
to
identify
superior
constant.
Molecular
descriptors
calculated.
These
used
train
several
models,
including
linear
regression,
gradient
booting
histgradient
boosting
bagging
decision
tree
random
forest
regression.
By
employing
cross‐validation
hyperparameter
tuning,
best
model
optimized
robust
predictive
performance.
A
database
10k
generated
their
constant
predicted
ML
model.
Thirty
higher
values
selected.
This
work
demonstrates
the
power
data‐driven
approaches
in
accelerating
high‐performance
applications.
Nano-Micro Letters,
Journal Year:
2024,
Volume and Issue:
17(1)
Published: Dec. 3, 2024
Abstract
The
presence
of
Sn
Zn
-related
defects
in
Cu
2
ZnSn(S,Se)
4
(CZTSSe)
absorber
results
large
irreversible
energy
loss
and
extra
electron–hole
non-radiative
recombination,
thus
hindering
the
efficiency
enhancement
CZTSSe
devices.
Although
incorporation
Ag
can
effectively
suppress
significantly
improve
resulting
cell
performance,
an
excellent
has
not
been
achieved
to
date
primarily
owing
poor
electrical-conductivity
low
carrier
density
film
induced
by
substitution.
Herein,
this
study
exquisitely
devises
Ag/H
co-doping
strategy
via
substitution
programs
followed
hydrogen-plasma
treatment
procedure
for
achieving
efficient
In-depth
investigation
demonstrate
that
H
Ag-based
is
expected
caused
Importantly,
C=O
O–H
functional
groups
hydrogen
incorporation,
serving
as
electron
donor,
interact
with
under-coordinated
cations
material,
passivating
defects.
Consequently,
appropriate
amount
mitigates
prolongs
minority
lifetime,
yields
a
champion
14.74%,
showing
its
promising
application
kesterite-based
