Nature Communications,
Год журнала:
2025,
Номер
16(1)
Опубликована: Март 14, 2025
Understanding
active
phases
across
interfaces,
interphases,
and
even
within
the
bulk
under
varying
external
conditions
environmental
species
is
critical
for
advancing
heterogeneous
catalysis.
Describing
these
through
computational
models
faces
challenges
in
generation
calculation
of
a
vast
array
atomic
configurations.
Here,
we
present
framework
automatic
efficient
exploration
phases.
This
approach
utilizes
topology-based
algorithm
leveraging
persistent
homology
to
systematically
sample
configurations
diverse
coordination
environments
material
morphologies.
Simultaneously,
machine
learning
force
fields
enable
rapid
computations.
We
demonstrate
effectiveness
this
two
systems:
hydrogen
absorption
Pd,
where
penetrates
subsurface
layers
bulk,
inducing
"hex"
reconstruction
CO2
electroreduction,
explored
50,000
sampled
configurations;
oxidation
dynamics
Pt
clusters,
oxygen
incorporation
renders
clusters
less
during
reduction
reactions,
investigated
100,000
In
both
cases,
predicted
their
impacts
on
catalytic
mechanisms
closely
align
with
previous
experimental
observations,
indicating
that
proposed
strategy
can
model
complex
systems
discovery
specific
conditions.
Discovering
heterocatalysis
entails
configuration
sampling
optimization.
authors
developed
based
topology
effectively
explore
structures,
applied
electroreduction
Oxygen
Reduction
Reaction
Advanced Functional Materials,
Год журнала:
2024,
Номер
34(34)
Опубликована: Апрель 25, 2024
Abstract
The
rapid
advancement
of
high‐performance
computing
and
artificial
intelligence
technology
has
opened
up
novel
avenues
for
the
development
various
metal
electrocatalysts.
In
particular,
dilute
high‐entropy
alloys
have
garnered
significant
attention
owing
to
their
unique
electronic
spatial
structures,
as
well
exceptional
electrocatalytic
performance.
Commencing
with
exploration
single‐atom
alloy
catalysts,
latest
advancements
in
machine
learning
(ML)
techniques
are
presented
efficient
screening
a
broad
spectrum
spaces.
Subsequently,
review
delves
into
prevailing
trend
research,
focusing
specifically
on
rare‐metal
electrocatalysts,
offers
an
overview
progress
outcomes
achieved
through
application
ML
these
domains.
Finally,
highlighted
promising
category
electrocatalysts
underscore
importance
potential
applications
addressing
complex
challenging
research
issues
underscored.
Advanced Materials,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 31, 2025
The
utilization
of
2D
materials
as
catalysts
has
garnered
significant
attention
in
recent
years,
primarily
due
to
their
exceptional
features
including
high
surface
area,
abundant
exposed
active
sites,
and
tunable
physicochemical
properties.
unique
geometry
imparts
them
with
versatile
sites
for
catalysis,
basal
plane,
interlayer,
defect,
edge
sites.
Among
these,
hold
particular
significance
they
not
only
enable
the
activation
inert
but
also
serve
platforms
engineering
achieve
enhanced
catalytic
performance.
Here
it
is
comprehensively
aimed
summarize
state-of-the-art
advancements
on
electrocatalysis
photocatalysis,
applications
ranging
from
water
splitting,
oxygen
reduction,
nitrogen
reduction
CO2
reduction.
Additionally,
various
approaches
harnessing
modifying
are
summarized
discussed.
guidelines
rational
heterogeneous
catalysis
provided.
Advanced Materials,
Год журнала:
2023,
Номер
36(22)
Опубликована: Авг. 28, 2023
Abstract
The
inherent
discontinuity
and
unique
dimensional
attributes
of
nanomaterial
surfaces
interfaces
bestow
them
with
various
exceptional
properties.
These
properties,
however,
also
introduce
difficulties
for
both
experimental
computational
studies.
advent
machine
learning
interatomic
potential
(MLIP)
addresses
some
the
limitations
associated
empirical
force
fields,
presenting
a
valuable
avenue
accurate
simulations
these
surfaces/interfaces
nanomaterials.
Central
to
this
approach
is
idea
capturing
relationship
between
system
configuration
energy,
leveraging
proficiency
(ML)
precisely
approximate
high‐dimensional
functions.
This
review
offers
an
in‐depth
examination
MLIP
principles
their
execution
elaborates
on
applications
in
realm
surface
interface
systems.
prevailing
challenges
faced
by
potent
methodology
are
discussed.
ACS Catalysis,
Год журнала:
2023,
Номер
13(11), С. 7428 - 7436
Опубликована: Май 18, 2023
The
complexity
and
dynamics
of
catalytic
systems
make
it
challenging
to
study
the
catalysts
reactions.
Fortunately,
advance
machine
learning
(ML)
has
made
descriptor-based
catalyst
screening
rational
design
a
mainstream
research
approach.
Herein,
spectroscopic
descriptors
reported
in
recent
years
are
highlighted
field
catalysis.
Both
vibrational
spectra
X-ray
absorption
have
demonstrated
strong
ability
predict
structures
properties.
Through
several
cases,
interpretable
ML
models
based
on
discussed
reveal
physical
knowledge
mechanism
exhibit
superiority
transfer
tasks
imperfect
data
scenarios.
Finally,
this
Viewpoint,
we
illustrate
challenges
with
provide
perspectives.
ACS Catalysis,
Год журнала:
2023,
Номер
13(24), С. 15663 - 15672
Опубликована: Ноя. 21, 2023
Two-dimensional
metal–organic
frameworks
(2D
MOFs)
can
serve
as
effective
electrocatalysts
for
oxygen
reduction
reaction
(ORR)
to
improve
fuel
cell
technology.
However,
how
further
the
electrocatalytic
performance
of
2D
MOFs
and
reveal
mechanism
ORR
remains
a
great
challenge.
Hence,
density
functional
theory
is
used
investigate
influence
organic
ligand
characteristics
on
activity
MOFs,
in
which
cobalt
atoms
act
metal
nodes.
Combined
with
calculations
formation
energy
dissolution
potential,
all
Co-MOFs
different
ligands
show
good
structural
stability.
The
calculation
results
showed
that
nodes
modified
by
synergistic
regulation
triphenylene
hydroxyl
groups
exhibit
superior
selectivity
low
overpotential
0.23
V
ORR.
Based
analysis
electronic
structure,
enhanced
spin
state
endows
Co
node's
moderate
interaction
key
intermediates,
conducive
facilitating
process.
Therefore,
revealed
this
work,
provide
theoretical
guidance
design
development
high-performance
future.
Advanced Functional Materials,
Год журнала:
2023,
Номер
34(14)
Опубликована: Дек. 27, 2023
Abstract
Urea
is
not
only
a
primary
fertilizer
in
modern
agriculture
but
also
crucial
raw
material
for
the
chemical
industry.
In
past
hundred
years,
prevailing
industrial
synthesis
of
urea
heavily
relies
on
Bosch–Meiser
process
to
couple
NH
3
and
CO
2
under
harsh
conditions,
resulting
high
carbon
emissions
energy
consumption.
The
conversion
carbon‐
nitrogen‐containing
species
into
through
electrochemical
reactions
ambient
conditions
represents
sustainable
strategy.
Despite
increasing
reports
electrosynthesis,
comprehensive
review
that
delves
profound,
atomic‐level
comprehension
fundamental
reaction
mechanisms
currently
absent.
this
Perspective,
recent
advancements
from
/CO
various
nitrogenous
(i.e.,
N
,
NO
x
−
NO)
are
presented,
with
special
emphasis
theoretical
understanding
C─N
coupling
mechanisms.
Several
key
strategies
facilitate
then
pinpointed,
which
enhance
their
applicability
practical
experiments
highlight
significant
progress
achieved
field.
At
end,
major
obstacles
potential
opportunities
advancing
electrosynthesis
accelerated
by
simulations
situ
techniques
discussed.
This
hoped
act
as
roadmap
ignite
fresh
insights
inspiration
development
electrocatalytic
synthesis.
Journal of Materials Chemistry A,
Год журнала:
2023,
Номер
11(8), С. 3849 - 3870
Опубликована: Янв. 1, 2023
In
this
review,
we
focus
on
the
systematic
construction
of
data-driven
electrocatalyst
design
framework
and
discuss
its
principles,
current
challenges,
opportunities.
Chemical Reviews,
Год журнала:
2024,
Номер
124(20), С. 11348 - 11434
Опубликована: Окт. 9, 2024
Environmental
catalysis
has
emerged
as
a
scientific
frontier
in
mitigating
water
pollution
and
advancing
circular
chemistry
reaction
microenvironment
significantly
influences
the
catalytic
performance
efficiency.
This
review
delves
into
engineering
within
liquid-phase
environmental
catalysis,
categorizing
microenvironments
four
scales:
atom/molecule-level
modulation,
nano/microscale-confined
structures,
interface
surface
regulation,
external
field
effects.
Each
category
is
analyzed
for
its
unique
characteristics
merits,
emphasizing
potential
to
enhance
efficiency
selectivity.
Following
this
overview,
we
introduced
recent
advancements
advanced
material
system
design
promote
(e.g.,
purification,
transformation
value-added
products,
green
synthesis),
leveraging
state-of-the-art
technologies.
These
discussions
showcase
was
applied
different
reactions
fine-tune
regimes
improve
from
both
thermodynamics
kinetics
perspectives.
Lastly,
discussed
challenges
future
directions
engineering.
underscores
of
intelligent
materials
drive
development
more
effective
sustainable
solutions
decontamination.
