Chemical Society Reviews,
Journal Year:
2024,
Volume and Issue:
53(21), P. 10450 - 10490
Published: Jan. 1, 2024
Supported
metal
catalysts
are
essential
to
a
plethora
of
processes
in
the
chemical
industry.
The
overall
performance
these
depends
strongly
on
interaction
adsorbates
at
atomic
level,
which
can
be
manipulated
and
controlled
by
different
constituents
active
material
(
Advanced Functional Materials,
Journal Year:
2024,
Volume and Issue:
34(34)
Published: April 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.
Nature Communications,
Journal Year:
2025,
Volume and Issue:
16(1)
Published: March 12, 2025
The
modern
view
of
industrial
heterogeneous
catalysis
is
evolving
from
the
traditional
static
paradigm
where
catalyst
merely
provides
active
sites,
to
that
a
functional
material
in
which
dynamics
plays
crucial
role.
Using
machine
learning-driven
molecular
simulations,
we
confirm
this
picture
for
ammonia
synthesis
catalysed
by
BaH2.
Recent
experiments
show
system
acts
as
highly
efficient
catalyst,
but
only
when
exposed
first
N2
and
then
H2
chemical
looping
process.
Our
simulations
reveal
N2,
BaH2
undergoes
profound
change,
transforming
into
superionic
mixed
compound,
BaH2−2x(NH)x,
characterized
high
mobility
both
hydrides
imides.
This
transformation
not
limited
surface
involves
entire
catalyst.
When
compound
second
step
process,
readily
formed
released,
process
greatly
facilitated
ionic
mobility.
Once
all
nitrogen
are
hydrogenated,
reverts
its
initial
state,
ready
next
cycle.
microscopic
analysis
underlines
dynamic
nature
does
serve
platform
reactions,
rather
it
entity
evolves
under
reaction
conditions.
shifting
paradigm.
Here,
authors
reactions
during
synthesis,
Proceedings of the National Academy of Sciences,
Journal Year:
2023,
Volume and Issue:
120(50)
Published: Dec. 7, 2023
Dynamics
has
long
been
recognized
to
play
an
important
role
in
heterogeneous
catalytic
processes.
However,
until
recently,
it
impossible
study
their
dynamical
behavior
at
industry-relevant
temperatures.
Using
a
combination
of
machine
learning
potentials
and
advanced
simulation
techniques,
we
investigate
the
cleavage
N
2
triple
bond
on
Fe(111)
surface.
We
find
that
low
temperatures
our
results
agree
with
well-established
picture.
if
increase
temperature
reach
operando
conditions,
surface
undergoes
global
change
step
structure
is
destabilized.
The
sites,
traditionally
associated
this
surface,
appear
disappear
continuously.
Our
simulations
illuminate
danger
extrapolating
low-temperature
conditions
indicate
activity
can
only
be
inferred
from
calculations
take
dynamics
fully
into
account.
More
than
that,
they
show
transition
highly
fluctuating
interfacial
environment
drives
process.
Journal of Catalysis,
Journal Year:
2024,
Volume and Issue:
433, P. 115482 - 115482
Published: April 8, 2024
The
future
of
computational
heterogeneous
catalysis
is
shaped
by
machine
learning
in
two
different
but
equally
important
areas:
(i)
development
atomistic
potentials
that
closely
approximate
DFT
and
wavefunction
based
ab
initio
methods
(MP2,
CCSD(T)),
are
computationally
more
efficient,
(ii)
finding
structure
reactivity
descriptors
for
predicting
catalytic
materials
reactions.
Machine
Learning
Potentials
will
enable
improved
sampling
the
potential
energy
surface
(PES)
reaction
conditions,
they
not
do
better
than
data
on
which
trained.
Therefore,
this
perspective
focusses
ways
improving
quality
PES
beyond
generalized
gradient
approximation
(GGA)
climbing
Jacob's
ladder
functionals
up
to
RPA
using
such
as
MP2
CCSD(T).
It
problem
solving
close
collaboration
with
experiment
has
made
methodology
relevant
remains
an
aspect
science
catalysis.
ACS Catalysis,
Journal Year:
2024,
Volume and Issue:
14(7), P. 4944 - 4950
Published: March 18, 2024
For
a
catalyst
to
be
efficient
and
durable,
it
is
crucial
that
the
reaction
products
do
not
poison
catalyst.
In
case
of
Haber–Bosch
process,
rate-limiting
step
believed
decomposition
nitrogen
molecules
on
Fe(111)
surface.
This
leads
production
surface
atomic
(N*),
which,
unless
hydrogenated
eventually
released
as
ammonia,
remains
adsorbed
occupies
active
sites.
Thus,
important
ascertain
how
high
N*
coverage
affects
dissociative
chemisorption.
To
answer
this
question,
we
study
properties
at
different
both
room
operando
temperature.
latter
regime,
have
already
found
Fe
atoms
exhibit
mobility,
promoting
formation
adatoms
vacancies,
causing
catalytic
centers
acquire
finite
lifetime
[Bonati
et
al.
Proceedings
National
Academy
Sciences
2023,
120
(50),
e2313023120].
We
discover
reduces
but
does
eliminate
iron
mobility.
Remarkably,
stabilize
triangular
structures
associated
with
which
are
sign
frustrated
drive
toward
more
stable
Fe4N
phase.
As
consequence,
tend
cluster,
reducing
their
poisoning
effect.
At
same
time,
reduction
in
number
counteracted
by
an
increase
lifetime.
The
combined
effect
dissociation
barrier
significantly
altered
range
coverages
studied.
These
results
bring
light
complex
role
dynamics
plays
reactivity
under
conditions.
ACS Catalysis,
Journal Year:
2024,
Volume and Issue:
14(3), P. 1252 - 1256
Published: Jan. 10, 2024
Among
the
many
catalysts
suggested
for
ammonia
decomposition,
Li2NH
has
been
shown
to
be
quite
promising.
In
recent
past,
we
have
performed
extensive
ab
initio-quality
simulations
explain
workings
of
this
unusual
catalyst.
complex
scenario
that
emerged,
surface
dynamics
and
structural
disorder
enhanced
by
interaction
with
reacting
molecules
played
crucial
roles.
Non-stoichiometric
lithium
imide
(Li2–x(NH2)x(NH)1–x)
reported
better
catalytic
performances
than
pure
imide.
Stimulated
these
findings,
follow
up
our
previous
study
simulating
decomposition
on
such
non-stoichiometric
compounds.
We
attribute
reactivity
fact
compositional
further
enhances
fluctuations
in
topmost
layers
catalyst,
strengthening
dynamic
picture
process.
