Advanced Energy and Sustainability Research,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Dec. 30, 2024
Metal‐organic
frameworks
(MOFs)
have
emerged
as
key
materials
for
carbon
capture
and
conversion,
particularly
in
photocatalytic
CO
2
reduction.
However,
inconsistent
reporting
of
essential
parameters
the
literature
hinders
informed
decisions
about
material
selection
optimization.
This
perspective
highlights
need
a
user‐friendly,
centralized
database
supported
by
automated
data
extraction
using
natural
language
processing
tools
to
streamline
comparisons
MOF
materials.
By
consolidating
crucial
from
scientific
literature,
such
promotes
efficient
decision‐making
utilization.
Emphasizing
significance
open‐source
initiatives
principles
FAIR
data—ensuring
are
Findable,
Accessible,
Interoperable,
Reusable—a
collaborative
approach
management
sharing
is
advocated
for.
Making
database‐accessible
worldwide
enhances
quality
reliability,
fostering
innovation
progress
conversion
Additionally,
databases
valuable
creating
artificial
intelligence
assist
researchers
discovery
synthesis
conversion.
Nanomaterials,
Journal Year:
2025,
Volume and Issue:
15(8), P. 631 - 631
Published: April 21, 2025
Inorganic
nanomaterials
are
pivotal
foundational
materials
driving
traditional
industries’
transformation
and
emerging
sectors’
evolution.
However,
their
industrial
application
is
hindered
by
the
limitations
of
conventional
synthesis
methods,
including
poor
batch
stability,
scaling
challenges,
complex
quality
control
requirements.
This
review
systematically
examines
strategies
for
constructing
automated
systems
to
enhance
production
efficiency
inorganic
nanomaterials.
Methodologies
encompassing
hardware
architecture
design,
software
algorithm
optimization,
artificial
intelligence
(AI)-enabled
intelligent
process
analyzed.
Case
studies
on
quantum
dots
gold
nanoparticles
demonstrate
enhanced
closed-loop
machine
learning-enabled
autonomous
optimization
parameters.
The
study
highlights
critical
role
automation,
technologies,
human–machine
collaboration
in
elucidating
mechanisms.
Current
challenges
cross-scale
mechanistic
modeling,
high-throughput
experimental
integration,
standardized
database
development
discussed.
Finally,
prospects
AI-driven
envisioned,
emphasizing
potential
accelerate
novel
material
discovery
revolutionize
nanomanufacturing
paradigms
within
framework
AI-plus
initiatives.
RSC Advances,
Journal Year:
2025,
Volume and Issue:
15(18), P. 13924 - 13939
Published: Jan. 1, 2025
Metal-organic
frameworks
(MOFs)
are
an
emerging
class
of
materials
with
exceptional
porosity
and
tunable
structures,
making
them
highly
effective
for
adsorbing
harmful
impurities
from
water.
These
properties
render
MOFs
particularly
suitable
environmental
remediation.
However,
evaluating
all
available
is
impractical
due
to
their
vast
number.
To
address
this,
we
employed
computational
screening
using
Grand
Canonical
Monte
Carlo
(GCMC)
simulations
on
a
database
over
14
000
identify
the
most
promising
candidates
antiparasitic
drug
(ivermectin,
IVM)
adsorption,
delivery,
membrane
filtration.
The
GCMC
identified
584
potential
applications.
Among
them,
147
demonstrated
strong
IVM
adsorption
capabilities,
delivery
remaining
437
exhibited
ideal
filtration,
specifically
reverse
osmosis
nanofiltration
separate
IVM.
loading
capacity
isosteric
heat
at
101.325
kPa
298
K
were
calculated
correlated
various
structural
properties,
including
largest
void
diameter,
pore-limiting
accessible
volume,
density,
helium
fraction.
Molecular
dynamics
performed
understand
mechanism.
Materials Horizons,
Journal Year:
2024,
Volume and Issue:
11(18), P. 4311 - 4320
Published: Jan. 1, 2024
Novel
method
of
screening
large-scale
material
databases
to
discover
novel
heterogeneous
core@metal–organic-framework
photocatalysts
that
are
synthesizable,
utilize
visible
light,
band
aligned,
and
water
stable.
Journal of Agricultural and Food Chemistry,
Journal Year:
2024,
Volume and Issue:
72(42), P. 22985 - 23007
Published: Oct. 9, 2024
Efficient
management
of
crop
diseases
and
yield
enhancement
are
essential
for
addressing
the
increasing
food
demands
due
to
global
population
growth.
Metal-organic
frameworks
(MOFs),
which
have
rapidly
evolved
throughout
21st
century,
notable
their
vast
surface
area,
porosity,
adaptability,
establishing
them
as
highly
effective
vehicles
controlled
drug
delivery.
This
review
methodically
categorizes
common
MOFs
employed
in
disease
details
effectiveness
against
various
pathogens.
Additionally,
by
critically
evaluating
existing
research,
it
outlines
strategic
approaches
design
drug-delivery
explains
mechanisms
through
enhance
resistance.
Finally,
this
paper
identifies
current
challenges
MOF
research
suggests
directions
future
research.
Through
in-depth
review,
seeks
enrich
understanding
applications
offers
valuable
insights
researchers
practitioners.
Chemical Science,
Journal Year:
2024,
Volume and Issue:
15(40), P. 16467 - 16479
Published: Jan. 1, 2024
Digital
discoveries
of
metal-organic
frameworks
(MOFs)
have
been
significantly
advanced
by
the
reverse
topological
approach
(RTA).
The
node-and-linker
assembly
strategy
allows
predictable
reticulations
predefined
Advanced Energy and Sustainability Research,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Dec. 30, 2024
Metal‐organic
frameworks
(MOFs)
have
emerged
as
key
materials
for
carbon
capture
and
conversion,
particularly
in
photocatalytic
CO
2
reduction.
However,
inconsistent
reporting
of
essential
parameters
the
literature
hinders
informed
decisions
about
material
selection
optimization.
This
perspective
highlights
need
a
user‐friendly,
centralized
database
supported
by
automated
data
extraction
using
natural
language
processing
tools
to
streamline
comparisons
MOF
materials.
By
consolidating
crucial
from
scientific
literature,
such
promotes
efficient
decision‐making
utilization.
Emphasizing
significance
open‐source
initiatives
principles
FAIR
data—ensuring
are
Findable,
Accessible,
Interoperable,
Reusable—a
collaborative
approach
management
sharing
is
advocated
for.
Making
database‐accessible
worldwide
enhances
quality
reliability,
fostering
innovation
progress
conversion
Additionally,
databases
valuable
creating
artificial
intelligence
assist
researchers
discovery
synthesis
conversion.
