Journal of Alloys and Compounds,
Год журнала:
2024,
Номер
1005, С. 175962 - 175962
Опубликована: Авг. 11, 2024
Thermal
spray
high-entropy
alloy
(HEA)
coatings
have
demonstrated
potential
for
improving
the
wear
resistance
of
conventional
materials
used
in
extreme
engineering
environments.
In
present
work,
an
equiatomic
AlCoCrFeNi
HEA
coating
was
manufactured
using
high
velocity
air
fuel
(HVAF)
process.
The
phase
and
microstructural
transformations
gas-atomized
(GA)
powder
during
HVAF
spraying
were
analyzed
SEM,
EDS
EBSD
techniques.
tribological
properties
this
sliding
against
Al2O3
ball
at
both
room
temperature
(RT)
600
°C
also
evaluated.
GA
composed
Body
Centred
Cubic
(BCC)
+
ordered
BCC
(B2)
phases,
which
transformed
to
B2
minor
Face
(FCC)
phases
process,
validating
thermodynamic
prediction
projected
by
Scheil
simulation
non-equilibrium
processing
conditions.
rapid
solidification
impact-assisted
deformation
resulted
significant
grain
refinement
coating,
ultimately
improved
mechanical
micro
nanoscale
levels.
RT
severely
impacted
relatively
brittle
BCC/B2
structure,
leading
susceptibility
abrasive
surface
fatigue.
slightly
lower
due
formation
a
oxide
layer
on
worn
surface,
induced
fatigue
aggravated
mass
loss
coating.
The
global
pursuit
of
sustainable
energy
is
focused
on
producing
hydrogen
through
electrocatalysis
driven
by
renewable
energy.
Recently,
High
entropy
alloys
(HEAs)
have
taken
the
spotlight
in
electrolysis
due
to
their
intriguing
cocktail
effect,
broad
design
space,
customizable
electronic
structure,
and
stabilization
effect.
tunability
complexity
HEAs
allow
a
diverse
range
active
sites,
optimizing
adsorption
strength
activity
for
electrochemical
water
splitting.
This
review
comprehensively
covers
contemporary
advancements
synthesis
technique,
framework,
physio-chemical
evaluation
approaches
HEA-based
electrocatalysts.
Additionally,
it
explores
principles
strategies
aimed
at
catalytic
activity,
stability,
effectiveness
evolution
reaction
(HER),
oxygen
(OER),
overall
Through
an
in-depth
investigation
these
aspects,
inherent
constituent
element
interactions,
processes,
sites
associated
with
unravel.
Eventually,
outlook
regarding
challenges
impending
difficulties
outline
future
direction
HEA
provided.
thorough
knowledge
offered
this
will
assist
formulating
designing
catalysts
based
next
generation
electrochemistry-related
applications.
Nano-Micro Letters,
Год журнала:
2024,
Номер
17(1)
Опубликована: Сен. 26, 2024
Abstract
The
synthesis
of
carbon
supporter/nanoscale
high-entropy
alloys
(HEAs)
electromagnetic
response
composites
by
carbothermal
shock
method
has
been
identified
as
an
advanced
strategy
for
the
collaborative
competition
engineering
conductive/dielectric
genes.
Electron
migration
modes
within
HEAs
manipulated
electronegativity,
valence
electron
configurations
and
molar
proportions
constituent
elements
determine
steady
state
efficiency
equivalent
dipoles.
Herein,
enlightened
skin-like
effect,
a
reformative
using
carbonized
cellulose
paper
(CCP)
supporter
is
used
to
preserve
oxygen-containing
functional
groups
(O·)
fibers
(CCF).
Nucleation
construction
emblematic
shell-core
CCF/HEAs
heterointerfaces
are
inextricably
linked
metabolism
induced
O·.
Meanwhile,
mode
switchable
electron-rich
sites
promotes
orientation
polarization
anisotropic
By
virtue
reinforcement
strategy,
CCP/HEAs
composite
prepared
35%
ratio
Mn
element
(CCP/HEAs-Mn
2.15
)
achieves
efficient
wave
(EMW)
absorption
−
51.35
dB
at
ultra-thin
thickness
1.03
mm.
mechanisms
resulting
dielectric
properties
HEAs-based
EMW
absorbing
materials
elucidated
combining
theoretical
calculations
with
experimental
characterizations,
which
provide
bases
feasible
strategies
simulation
practical
application
devices
(e.g.,
ultra-wideband
bandpass
filter).
Materials & Design,
Год журнала:
2024,
Номер
238, С. 112634 - 112634
Опубликована: Янв. 13, 2024
High-entropy
alloys
(HEAs)
have
attracted
considerable
attention
for
their
exceptional
microstructures
and
properties.
Discovering
new
HEAs
with
desirable
properties
is
crucial,
but
traditional
design
methods
are
laborious
time-consuming.
Fortunately,
the
emerging
Machine
Learning
(ML)
offers
an
efficient
solution.
In
this
study,
composition-microhardness
data
pairs
from
various
alloy
systems
were
collected
expanded
using
a
Generative
Adversarial
Network
(GAN).
These
converted
into
empirical
parameter-microhardness
pairs.
Then
Active
(AL)
was
employed
to
screen
Al-Co-Cr-Cu-Fe-Ni
system
identify
eXtreme
Gradient
Boosting
(XGBoost)
as
optimal
ML
master
model.
Millions
of
training
iterations
employing
XGBoost
sub-model
accuracy
evaluations
Expected
Improvement
(EI)
algorithm
establish
relationship
between
HEA
compositions
microhardness.
The
proposed
aligns
well
experimental
data,
wherein
four
Al-rich
exhibit
ultra-high
microhardness
(>740
HV,
maximum
∼780.3
HV)
low
density
(<5.9
g/cm3)
in
as-cast
bulk
state.
hardening
increment
originates
precipitation
disordered
BCC
nanoparticles
ordered
AlCo-rich
B2
matrix
compared
dilute
AlCo
intermetallics.
This
lightweight,
high-performance
shows
potential
engineering
applications
thin
films
or
coatings.
