Understanding Free-Energy Landscapes in Electrocatalysis: A Case Study on Nitrate Reduction over Au(111)
ACS electrochemistry.,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Feb. 25, 2025
Free-energy
landscapes
are
essential
tools
in
electrocatalysis
for
assessing
catalyst
activity
and
selectivity
of
proton-coupled
electron
transfer
steps.
It
is
a
common
approach
to
focus
on
the
thermodynamic
part
free-energy
landscape
refer
only
reaction
intermediates,
which
turn
leads
results
being
highly
dependent
accuracy
calculated
binding
energies
adsorbed
intermediates.
Since
evaluation
electrocatalytic
processes
solid
surfaces
usually
requires
density
functional
theory
calculations
(DFT)
with
periodic
boundary
conditions,
free
energy
reference
molecules
relevant
binding-energy
determination
subject
an
inherent
error.
For
this
purpose,
gas-phase
error
corrections
have
been
introduced
recent
years,
allow
correction
DFT
error,
based
assessment
formation
enthalpies,
by
assigning
double
or
triple
bonds
molecules.
In
contribution,
we
present
simple
unbiased
errors:
do
not
distinguish
between
bond
order
but
correct
all
single,
double,
referring
atomization
compounds.
We
employ
our
nitrate
reduction
Au(111)
as
case
study,
using
different
levels
exchange–correlation
functionals
generalized
gradient
meta-generalized
approximation.
shown
that
inclusion
well
solvation
ion
significantly
affects
energetics
predictions
descriptor-based
analysis,
highlighting
importance
correcting
DFT-based
gaining
reliable
insights
into
systems.
Language: Английский
Sustainable carbon electrode materials from biomass for redox flow batteries
Biomass and Bioenergy,
Journal Year:
2025,
Volume and Issue:
198, P. 107846 - 107846
Published: April 9, 2025
Language: Английский
Unifying thermochemistry concepts in computational heterogeneous catalysis
Chemical Society Reviews,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Nov. 29, 2024
Thermophysical
properties
of
adsorbates
and
gas-phase
species
define
the
free
energy
landscape
heterogeneously
catalyzed
processes
are
pivotal
for
an
atomistic
understanding
catalyst
performance.
Language: Английский
Unifying thermochemistry concepts in computational heterogeneous catalysis
Published: Aug. 2, 2024
Thermophysical
properties
of
adsorbates
and
gas-phase
species
define
the
free
energy
landscape
heterogeneously
catalyzed
processes
are
pivotal
for
an
atomistic
understanding
catalyst
performance.
These
thermophysical
properties,
such
as
or
enthalpy,
typically
derived
from
density
functional
theory
(DFT)
calculations.
Enthalpies
species-interdependent
that
only
meaningful
when
referenced
to
other
species.
The
widespread
use
DFT
has
led
a
proliferation
new
energetic
data
in
literature
databases.
However,
there
is
lack
consistency
how
associated
enthalpies
energies
stored
reported,
leading
challenges
reproducing
utilizing
results
prior
work.
Additionally,
suffers
exchange-correlation
errors
often
require
corrections
align
with
global
thermochemical
networks,
which
not
always
clearly
documented
explained.
In
this
review,
we
introduce
set
consistent
terminology
definitions,
review
existing
approaches,
unify
techniques
using
framework
linear
algebra.
This
tools
facilitates
correction
alignment
between
different
formats
sources,
promoting
sharing
reuse
ab
initio
data.
Standardization
thermochemistry
concepts
computational
heterogeneous
catalysis
reduces
cost
enhances
fundamental
catalytic
processes,
will
accelerate
design
optimally
performing
catalysts.
Language: Английский
Uncertainty quantification and propagation in atomistic machine learning
Reviews in Chemical Engineering,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Dec. 30, 2024
Abstract
Machine
learning
(ML)
offers
promising
new
approaches
to
tackle
complex
problems
and
has
been
increasingly
adopted
in
chemical
materials
sciences.
In
general,
ML
models
employ
generic
mathematical
functions
attempt
learn
essential
physics
chemistry
from
large
amounts
of
data.
The
reliability
predictions,
however,
is
often
not
guaranteed,
particularly
for
out-of-distribution
data,
due
the
limited
physical
or
principles
functional
form.
Therefore,
it
critical
quantify
uncertainty
predictions
understand
its
propagation
downstream
applications.
This
review
examines
existing
quantification
(UQ)
(UP)
methods
atomistic
under
framework
probabilistic
modeling.
We
first
categorize
UQ
explain
similarities
differences
among
them.
Following
this,
performance
metrics
evaluating
their
accuracy,
precision,
calibration,
efficiency
are
presented,
along
with
techniques
recalibration.
These
then
applied
survey
benchmark
studies
that
use
molecular
datasets.
Furthermore,
we
discuss
UP
propagate
widely
used
simulation
techniques,
such
as
dynamics
microkinetic
conclude
remarks
on
challenges
opportunities
ML.
Language: Английский
Evaluating the Role of Metastable Surfaces in Mechanochemical Reduction of Molybdenum Oxide
JACS Au,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Nov. 19, 2024
Mechanochemistry
and
mechanocatalysis
are
gaining
increasing
attention
as
environmentally
friendly
chemical
processes
because
of
their
solvent-free
nature
scalability.
Significant
effort
has
been
devoted
for
studying
continuum-scale
phenomena
in
mechanochemistry,
such
temperature
pressure
gradients,
but
the
atomic-scale
mechanisms
remain
relatively
unexplored.
In
this
work,
we
focus
on
mechanochemical
reduction
MoO3
a
case
study.
We
use
experimental
techniques
to
determine
conditions
density
functional
theory
(DFT)
simulations
establish
an
atomistic
framework
identifying
metastable
surfaces
that
most
likely
enable
process.
Our
results
show
can
significantly
lower
or
remove
thermodynamic
barriers
surface
kinetic
energy
from
milling
facilitate
formation
have
high
fracture
energies
not
thermally
accessible.
These
findings
indicate
important
aspect
mechanochemistry
along
with
hot
spots
other
phenomena.
Language: Английский