Electrochemical CO2 Reduction on SnO: Insights into C1 Product Dynamic Distribution and Reaction Mechanisms
ACS Catalysis,
Год журнала:
2025,
Номер
unknown, С. 3173 - 3183
Опубликована: Фев. 6, 2025
The
precise
synthesis
of
desirable
products
from
the
electrochemical
CO2
reduction
reaction
(CO2RR)
remains
challenging,
primarily
due
to
unclear
structure–activity
relationships
under
in
situ
conditions.
Recognized
by
their
cost-effectiveness
and
nontoxic
nature,
Sn-based
materials
are
extensively
utilized
CO2RR
produce
valuable
chemicals.
Notably,
our
large-scale
data
mining
experimental
literature
reveals
a
significant
trend:
SnO2-based
electrocatalysts
generate
HCOOH,
while
SnO-based
counterparts
demonstrate
ability
both
HCOOH
CO
comparable
quantities.
Furthermore,
findings
indicate
that
SnO
underexplored
terms
its
surface
speciation
for
compared
materials.
Addressing
these
issues
is
crucial
field
electrocatalysis,
as
understanding
them
will
not
only
clarify
why
uniquely
influences
distribution
C1
but
also
provide
insights
into
how
precisely
control
electrocatalytic
processes
targeted
product
synthesis.
Herein,
we
employed
constant-potential
method
combined
with
coverage
reconstruction
analyses
simulate
energetics
intermediates
elucidate
dynamic
on
resting
typical
Our
analysis
effectively
identifies
active
involved
CO2RR.
comparative
simulations
between
pristine
reconstructed
surfaces
reveal
electrochemistry-induced
oxygen
vacancies
direct
distribution.
By
addressing
critical
issues,
aim
advance
electrocatalysis
contribute
chemical
production
CO2,
stimulating
future
exploration
conditions
other
systems.
Язык: Английский
Active phase discovery in heterogeneous catalysis via topology-guided sampling and machine learning
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
Язык: Английский
Advancing electrocatalyst discovery through the lens of data science: State of the art and perspectives☆
Journal of Catalysis,
Год журнала:
2025,
Номер
unknown, С. 116162 - 116162
Опубликована: Апрель 1, 2025
Язык: Английский
Mechanism-Guided Descriptor for Hydrogen Evolution Reaction in 2D Ordered Double Transition-Metal Carbide MXenes
Chemical Science,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 1, 2025
Selecting
effective
catalysts
for
the
hydrogen
evolution
reaction
(HER)
among
MXenes
remains
a
complex
challenge.
While
machine
learning
(ML)
paired
with
density
functional
theory
(DFT)
can
streamline
this
search,
issues
training
data
quality,
model
accuracy,
and
descriptor
selection
limit
its
effectiveness.
These
hurdles
often
arise
from
an
incomplete
understanding
of
catalytic
mechanisms.
Here,
we
introduce
mechanism-guided
(δ)
HER,
designed
to
enhance
catalyst
screening
ordered
transition
metal
carbide
MXenes.
This
integrates
structural
energetic
characteristics,
derived
in-depth
analysis
orbital
interactions
relationship
between
Gibbs
free
energy
adsorption
(ΔG
H)
features.
The
proposed
H
=
-0.49δ
-
2.18)
not
only
clarifies
structure-activity
links
but
also
supports
efficient,
resource-effective
identification
promising
catalysts.
Our
approach
offers
new
framework
developing
descriptors
advancing
screening.
Язык: Английский
Pulsed Electrocatalysis on SnO2 Electrodes for Boosting Formate Selectivity and Activity during CO2 Electroreduction
Advanced Functional Materials,
Год журнала:
2025,
Номер
unknown
Опубликована: Май 13, 2025
Abstract
Tin
oxide
(SnO
2
)
is
considered
a
candidate
catalyst
for
the
electrocatalytic
CO
reduction
(CO
R)
to
formate
conversion.
However,
self‐reduction
of
SnO
metallic
Sn
at
high
current
densities
leads
an
unavoidable
sharp
decrease
in
selectivity.
Herein,
‐based
(Pul‐SnO
synthesized
via
pulsed
electrocatalysis
precursors.
Due
ability
maintain
oxidation
valence
states
and
promote
formation
oxygen
vacancies,
Pul‐SnO
exhibited
selectivity
90%
density
600
mA
cm
−2
,
significantly
higher
than
that
conventional
Sn‐based
(81%
100
obtained
constant
potential
electrocatalysis.
The
situ
Raman
spectra,
kinetic
isotope
effect,
cyclic
voltammetry,
theoretical
calculations
demonstrated
molecules
activation
vacancies
enhance
water
dissociation,
thereby
accelerating
proton‐coupled
electron
transfer
process
reduce
free
energy
*OCHO
intermediate
generation.
Moreover,
identified
adsorbed
hydroxyls
(*OH)
with
suitable
coverage
during
R
also
further
make
more
energy‐favorable.
As
result,
showed
super
formate,
while
maintaining
excellent
activity
stability.
Язык: Английский
Closed-Loop Framework for Discovering Stable and Low-Cost Bifunctional Metal Oxide Catalysts for Efficient Electrocatalytic Water Splitting in Acid
Journal of the American Chemical Society,
Год журнала:
2025,
Номер
unknown
Опубликована: Май 19, 2025
Electrocatalytic
water
splitting,
comprising
the
oxygen
evolution
reaction
(OER)
and
hydrogen
(HER),
provides
a
sustainable
route
for
production.
While
low-cost
metal
oxides
(MOs)
are
appealing
as
alternatives
to
noble
electrocatalysts,
their
application
in
acidic
media
remains
challenging.
However,
dynamic
nature
of
some
MO
surface
structures
under
electrochemical
conditions
offers
an
opportunity
rational
catalyst
design
achieve
bifunctionality
OER
HER.
Here,
we
present
closed-loop
framework
that
integrates
potential
exploration
(front-end),
synthesis
tests
(mid-end),
advanced
characterizations
(back-end).
This
combines
crucial
steps
electrocatalyst
exploration,
including
data
mining,
state
analysis,
microkinetic
modeling,
proof-of-concept
experiments
identify
stable
cost-effective
catalysts
splitting.
Using
this
approach,
RbSbWO6
is
identified
promising
bifunctional
first
time,
with
experimental
validation
demonstrating
its
exceptional
stability
performance
Notably,
outperforms
many
other
reported
non-noble
stoichiometric
have
not
undergone
major
modifications
These
findings,
derived
from
our
Digital
Catalysis
Platform
(DigCat),
establish
highly
effective
underscore
power
workflow
accelerating
discovery.
begins
DigCat
platform,
concludes
validation,
feeds
into
designing
electrocatalysts
systems
such
nitrides
or
carbides.
study
demonstrates
importance
high
efficiency
data-driven
approaches
new
scientific
discovery
paradigm.
Язык: Английский