Molecular dynamics simulations of heat transport using machine-learned potentials: A mini-review and tutorial on GPUMD with neuroevolution potentials
Journal of Applied Physics,
Год журнала:
2024,
Номер
135(16)
Опубликована: Апрель 24, 2024
Molecular
dynamics
(MD)
simulations
play
an
important
role
in
understanding
and
engineering
heat
transport
properties
of
complex
materials.
An
essential
requirement
for
reliably
predicting
is
the
use
accurate
efficient
interatomic
potentials.
Recently,
machine-learned
potentials
(MLPs)
have
shown
great
promise
providing
required
accuracy
a
broad
range
In
this
mini-review
tutorial,
we
delve
into
fundamentals
transport,
explore
pertinent
MD
simulation
methods,
survey
applications
MLPs
transport.
Furthermore,
provide
step-by-step
tutorial
on
developing
highly
predictive
simulations,
utilizing
neuroevolution
as
implemented
GPUMD
package.
Our
aim
with
to
empower
researchers
valuable
insights
cutting-edge
methodologies
that
can
significantly
enhance
efficiency
studies.
Язык: Английский
Phonon coherent transport leads to an anomalous boundary effect on the thermal conductivity of a rough graphene nanoribbon
Physical Review Applied,
Год журнала:
2024,
Номер
21(6)
Опубликована: Июнь 4, 2024
Coherent
phonons
can
give
rise
to
phenomena
and
physical
mechanisms
in
different
systems.
Understanding
phonon-boundary
scattering
is
critical
for
the
manipulation
of
thermal
properties.
In
this
paper,
it
found
that
conductivity
rough
graphene
nanoribbon
first
monotonically
changes,
then
exhibits
an
oscillatory
manner
with
varying
surface
boundary
roughness.
An
obvious
increase
conductivity,
up
25.33%,
be
observed
as
roughness
increases
from
0.61
0.72.
This
contrast
conventional
understanding
typically
decreases
when
increases.
Further,
a
frequency-resolved
picture
lattice
dynamics
analysis
identify
anomalous
effect
originates
coherent
nature
phonons,
which
results
roughness-selected
destructive
interference
modes.
Besides,
oscillation
will
reduced
by
introducing
boundaries
sinusoidal
shapes,
randomness.
abnormal
also
extended
other
materials,
example,
hexagonal
boron
nitride
monolayer,
depending
mainly
on
anharmonicity.
The
study
reveals
insights
into
may
aid
design
heat
management
thermoelectric
devices
based
effect.
Язык: Английский
Insight into the effect of force error on the thermal conductivity from machine-learned potentials
Materials Today Physics,
Год журнала:
2024,
Номер
unknown, С. 101638 - 101638
Опубликована: Дек. 1, 2024
Язык: Английский
Tuning phonon transport via complex nanostructure design using an X+EA hybrid optimization strategy
Physical Review Materials,
Год журнала:
2025,
Номер
9(4)
Опубликована: Апрель 17, 2025
Язык: Английский
Prediction of phonon properties of cubic boron nitride with vacancy defects and isotopic disorders by using a neural network potential
Applied Physics Letters,
Год журнала:
2024,
Номер
124(15)
Опубликована: Апрель 8, 2024
Cubic
boron
nitride
(c-BN)
is
a
promising
ultra-wide
bandgap
semiconductor
for
high-power
electronic
devices.
Its
thermal
conductivity
can
be
substantially
modified
by
controlling
the
isotope
abundance
and
quality
of
single
crystal.
Consequently,
an
understanding
phonon
transport
in
c-BN
crystals,
with
both
vacancy
defects
isotopic
disorders
at
near-ambient
temperatures,
practical
importance.
In
present
study,
neural
network
potential
(NNP)
has
been
developed,
which
facilitated
investigation
properties
under
these
circumstances.
As
result,
dispersion
three-
four-phonon
scattering
rates
that
were
predicted
this
NNP
close
agreement
those
obtained
from
density-functional
theory
(DFT)
calculations.
The
conductivities
crystals
also
investigated,
(B)
vacancies
ranging
0.0%
to
0.6%,
using
equilibrium
molecular
dynamics
simulations
based
on
Green-Kubo
formula.
These
accurately
capture
vacancy-induced
softening,
localized
vibration
modes,
localization
effects.
previously
experimentally
prepared,
four
isotope-modified
samples
selected
analyses
evaluation
impact
disorders.
calculated
aligned
well
DFT
benchmarks.
addition,
study
was
extended
include
crystal
natural
B
atoms,
contained
vacancies.
Reasonable
vibrational
characteristics,
within
temperature
range
250–500
K,
then
obtained.
Язык: Английский
Tuning lattice thermal conductivity in NbMoTaW refractory high-entropy alloys: Insights from molecular dynamics using machine learning potential
Journal of Applied Physics,
Год журнала:
2024,
Номер
136(15)
Опубликована: Окт. 17, 2024
Refractory
high-entropy
alloys
(RHEAs)
have
attracted
increasing
interest
due
to
their
excellent
mechanical
properties
under
extreme
conditions.
However,
the
lattice
thermal
conductivity
is
still
not
well
studied.
In
this
paper,
we
calculate
of
NbMoTaW
RHEA
using
equilibrium
molecular
dynamics
method
with
a
machine
learning-based
interatomic
potential.
We
find
that
Mo
concentration,
increased
from
1.72
2.16
W/mK,
an
increase
25.6%.
The
underlying
mechanism
explained
by
phonon
density
states
and
mode
participation.
Increasing
concentration
can
induce
blueshift
in
both
low-frequency
high-frequency
phonons.
Moreover,
at
frequency
corresponding
peak,
NbMo1.5TaW
has
largest
participation
rate,
which
main
reason
for
anomalous
conductivity.
addition,
investigate
effect
temperature
on
results
show
anharmonicity
dominant
effect.
Finally,
compressive
strain
explored.
Our
work
discloses
associated
plays
critical
roles
RHEA,
rather
than
previously
recognized
conformational
entropy.
This
contributes
understanding
behavior
provides
effective
route
tune
its
Язык: Английский