Coupling Plastic Upgrading and Photocatalysis: Catalytic Mechanisms and Design Principles
Zongyang Ya,
No information about this author
Shengbo Zhang,
No information about this author
Dong Xu
No information about this author
et al.
ACS Catalysis,
Journal Year:
2025,
Volume and Issue:
unknown, P. 5339 - 5369
Published: March 17, 2025
Language: Английский
Reevaluating feature importance in machine learning models for CO2 photoreduction: A statistical perspective
Applied Catalysis B Environment and Energy,
Journal Year:
2025,
Volume and Issue:
368, P. 125145 - 125145
Published: Feb. 12, 2025
Language: Английский
Machine Learning Accelerated Discovery of Covalent Organic Frameworks for Environmental and Energy Applications
Environmental Science & Technology,
Journal Year:
2025,
Volume and Issue:
unknown
Published: March 30, 2025
Covalent
organic
frameworks
(COFs)
are
porous
crystalline
materials
obtained
by
linking
ligands
covalently.
Their
high
surface
area
and
adjustable
pore
sizes
make
them
ideal
for
a
range
of
applications,
including
CO2
capture,
CH4
storage,
gas
separation,
catalysis,
etc.
Traditional
methods
material
research,
which
mainly
rely
on
manual
experimentation,
not
particularly
efficient,
while
with
advancements
in
computer
science,
high-throughput
computational
screening
based
molecular
simulation
have
become
crucial
discovery,
yet
they
face
limitations
terms
resources
time.
Currently,
machine
learning
(ML)
has
emerged
as
transformative
tool
many
fields,
capable
analyzing
large
data
sets,
identifying
underlying
patterns,
predicting
performance
efficiently
accurately.
This
approach,
termed
"materials
genomics",
combines
ML
to
predict
design
high-performance
materials,
significantly
speeding
up
the
discovery
process
compared
traditional
methods.
review
discusses
functions
screening,
design,
prediction
COFs
highlights
their
applications
across
various
domains
like
thereby
providing
new
research
directions
enhancing
understanding
COF
applications.
Language: Английский
Synergistic Effects in the Electrochemical Carbon Dioxide Reduction Reaction for Multi‐Carbon Product Formation
Xiaoqin Xu,
No information about this author
Jingqi Guan
No information about this author
Advanced Functional Materials,
Journal Year:
2025,
Volume and Issue:
unknown
Published: April 1, 2025
Abstract
The
synergistic
effects
in
electrocatalysis
can
significantly
enhance
catalyst
performance
by
improving
catalytic
activity,
selectivity,
and
stability,
optimizing
reaction
mechanisms
electron
transfer
processes.
This
review
summarizes
recent
advancements
the
of
electrochemical
reduction
CO
2
(eCO
RR)
to
multi‐carbon
(C
2+
)
products.
Starting
with
fundamental
principles
eCO
RR
for
C
product
formation,
paper
outlines
producing
,
3
4
5
A
comprehensive
discussion
is
provided
on
critical
impact
structure–performance
relationship
production
Subsequently,
observed
are
classified
various
electrocatalysts
different
properties,
including
single/dual‐atom
catalysts,
multi‐centric
single‐atom
alloys,
metal‐organic
frameworks,
heterojunction
catalysts.
Finally,
challenges
achieving
selective
formation
through
discussed,
along
corresponding
strategies
overcome
obstacles.
Language: Английский