Applications of machine learning in surfaces and interfaces
Chemical Physics Reviews,
Journal Year:
2025,
Volume and Issue:
6(1)
Published: March 1, 2025
Surfaces
and
interfaces
play
key
roles
in
chemical
material
science.
Understanding
physical
processes
at
complex
surfaces
is
a
challenging
task.
Machine
learning
provides
powerful
tool
to
help
analyze
accelerate
simulations.
This
comprehensive
review
affords
an
overview
of
the
applications
machine
study
systems
materials.
We
categorize
into
following
broad
categories:
solid–solid
interface,
solid–liquid
liquid–liquid
surface
solid,
liquid,
three-phase
interfaces.
High-throughput
screening,
combined
first-principles
calculations,
force
field
accelerated
molecular
dynamics
simulations
are
used
rational
design
such
as
all-solid-state
batteries,
solar
cells,
heterogeneous
catalysis.
detailed
information
on
for
Language: Английский
Experimental study on the ignition and combustion of aluminium–lithium alloy particles in oxidizing atmospheres
Jun Su,
No information about this author
Jianxin Hu,
No information about this author
Linsong Gao
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et al.
Fuel,
Journal Year:
2024,
Volume and Issue:
386, P. 134222 - 134222
Published: Dec. 30, 2024
Language: Английский
Development of Machine Learning Potentials for Ce-Ti and Ce-Ta Binary Systems and Studies of the Liquid-Solid Interfaces
Hongjian Chen,
No information about this author
Jianfeng Cai,
No information about this author
Yunhan Zhang
No information about this author
et al.
Corrosion Science,
Journal Year:
2025,
Volume and Issue:
unknown, P. 112766 - 112766
Published: Feb. 1, 2025
Language: Английский
Understanding Surface/Interface‐Induced Chemical and Physical Properties at Atomic Level by First Principles Investigations
Wiley Interdisciplinary Reviews Computational Molecular Science,
Journal Year:
2025,
Volume and Issue:
15(3)
Published: May 1, 2025
ABSTRACT
The
scientific
trajectory
in
contemporary
materials
research
has
transitioned
toward
surface
and
interface
engineering
as
critical
determinants
of
functional
performance,
facilitating
atomic‐level
precision
modulating
physical
chemical
properties
for
advanced
applications
spanning
device
architectures,
catalytic
systems,
electrochemical
technologies.
However,
persistent
challenges
atomic‐scale
characterization
the
resource‐intensive
nature
empirical
optimization
necessitate
systematic
implementation
first‐principles
calculations
to
elucidate
fundamental
mechanisms
underlying
experimental
observations
enable
rational
design
surface/interface
modifications.
This
review
examines
three
advancements
ab
initio
interfacial
engineering:
(1)
revealing
mechanism
selective
assembly
activation
phenomena
on
surfaces,
(2)
theoretical
predictions
strategies,
(3)
developing
material
databases
with
ionic/van
der
Waals
components.
We
further
address
computational
while
proposing
quantum‐mechanical
methods
next‐gen
customized
properties.
Language: Английский