npj Computational Materials,
Journal Year:
2023,
Volume and Issue:
9(1)
Published: Feb. 6, 2023
Abstract
Computational
modeling
of
physical
processes
in
metal-organic
frameworks
(MOFs)
is
highly
challenging
due
to
the
presence
spatial
heterogeneities
and
complex
operating
conditions
which
affect
their
behavior.
Density
functional
theory
(DFT)
may
describe
interatomic
interactions
at
quantum
mechanical
level,
but
computationally
too
expensive
for
systems
beyond
nanometer
picosecond
range.
Herein,
we
propose
an
incremental
learning
scheme
construct
accurate
data-efficient
machine
potentials
MOFs.
The
builds
on
power
equivariant
neural
network
combination
with
parallelized
enhanced
sampling
on-the-fly
training
simultaneously
explore
learn
phase
space
iterative
manner.
With
only
a
few
hundred
single-point
DFT
evaluations
per
material,
transferable
are
obtained,
even
flexible
multiple
structurally
different
phases.
universally
applicable
pave
way
model
framework
materials
larger
spatiotemporal
windows
higher
accuracy.
eScience,
Journal Year:
2023,
Volume and Issue:
4(2), P. 100208 - 100208
Published: Nov. 3, 2023
Present
photocatalysts
for
the
synchronous
cleanup
of
pharmaceuticals
and
heavy
metals
have
several
drawbacks,
including
inadequate
reactive
sites,
inefficient
electron–hole
disassociation,
insufficient
oxidation
reduction
power.
In
this
research,
we
sought
to
address
these
issues
by
using
a
facile
solvothermal-photoreduction
route
develop
an
innovative
plasmonic
S-scheme
heterojunction,
Au/MIL-101(Fe)/BiOBr.
The
screened-out
Au/MIL-101(Fe)/BiOBr
(AMB-2)
works
in
durable
high-performance
manner
both
Cr(VI)
norfloxacin
(NOR)
eradication
under
visible
light,
manifesting
up
53.3
2
times
greater
NOR
abatement
rates,
respectively,
than
BiOBr.
Remarkably,
AMB-2's
ability
remove
Cr(VI)-NOR
co-existence
system
is
appreciably
better
sole-Cr(VI)
environment;
synergy
among
Cr(VI),
NOR,
AMB-2
results
utilization
photo-induced
carriers,
yielding
desirable
capacity
decontaminating
synchronously.
integration
MOF-based
heterojunctions
effect
contributes
markedly
reinforced
photocatalytic
increasing
number
active
augmenting
visible-light
absorbance,
boosting
efficient
disassociation
redistribution
powerful
photo-carriers,
elevating
generation
substances.
We
provide
details
mechanism,
decomposition
process,
bio-toxicity
intermediates.
This
synergistic
strategy
modifying
with
noble
metal
opens
new
horizons
devising
excellent
photosystems
environment
purification.
Chemical Society Reviews,
Journal Year:
2022,
Volume and Issue:
51(2), P. 464 - 484
Published: Jan. 1, 2022
This
tutorial
review
highlights
the
key
aspects
of
nanotoxicity
and
importance
its
systematic
assessment
for
metal–organic
framework
(MOF)
nanoparticles
to
pave
way
towards
their
potential
applications
in
a
safe
sustainable
manner.
Chemical Society Reviews,
Journal Year:
2022,
Volume and Issue:
51(15), P. 6307 - 6416
Published: Jan. 1, 2022
This
review
highlights
the
recent
advances
of
metalated
covalent
organic
frameworks,
including
synthetic
strategies
and
applications,
discusses
current
challenges
future
directions.
Chemical Society Reviews,
Journal Year:
2022,
Volume and Issue:
51(4), P. 1377 - 1414
Published: Jan. 1, 2022
This
review
summarizes
and
discusses
the
recent
progress
in
porous
organic
polymers
for
diverse
biomedical
applications
such
as
drug
delivery,
biomacromolecule
immobilization,
phototherapy,
biosensing,
bioimaging,
antibacterial
applications.
Advanced Functional Materials,
Journal Year:
2022,
Volume and Issue:
32(51)
Published: Oct. 21, 2022
Abstract
Metal‐organic
frameworks
(MOFs),
an
emerging
class
of
porous
organic‐inorganic
hybrid
materials,
have
shown
great
potential
for
water
and
wastewater
treatment
applications.
However,
pure
MOF
powders
limited
practical
applications
in
due
to
their
insolubility,
poor
processability,
brittleness,
safety
hazard
from
dust
formation,
difficult
separation
aqueous
solutions.
Thus,
exploring
MOFs
composites
with
improved
performance
is
importance.
The
marriage
electrospun
nanofiber
forethought
into
the
final
product's
morphology,
structure,
chemistry
has
opened
up
new
opportunities
efficient
treatment.
present
review
exhaustively
summarizes
strategies
integrate
nanofibers
via
electrospinning
remove
various
pollutants
(i.e.,
organic
dyes,
heavy
metal
ions,
pharmaceuticals,
personal
care
products,
oily
compounds,
solvents,
etc.)
adsorption,
photodegradation,
membrane
filtration.
Besides,
most
recent
advances
current
challenges
future
outlook
are
delineated.
Journal of the American Chemical Society,
Journal Year:
2021,
Volume and Issue:
143(48), P. 20055 - 20058
Published: Nov. 23, 2021
New
membrane
materials
with
excellent
water
permeability
and
high
ion
rejection
are
needed.
Metal-organic
frameworks
(MOFs)
promising
candidates
by
virtue
of
their
diversity
in
chemistry
topology.
In
this
work,
continuous
aluminum
MOF-303
membranes
were
prepared
on
α-Al2O3
substrates
via
an
situ
hydrothermal
synthesis
method.
The
exhibit
satisfying
divalent
ions
(e.g.,
93.5%
for
MgCl2
96.0%
Na2SO4)
the
basis
a
size-sieving
electrostatic-repulsion
mechanism
unprecedented
(3.0
L·m-2·h-1·bar-1·μm).
outperforms
typical
zirconium
MOF,
zeolite,
commercial
polymeric
reverse
osmosis
nanofiltration
membranes.
Additionally,
material
exhibits
good
stability
low
production
costs.
These
merits
recommend
as
next-generation
softening.
Angewandte Chemie International Edition,
Journal Year:
2022,
Volume and Issue:
61(19)
Published: Feb. 1, 2022
Abstract
Despite
rapid
progress
in
the
field
of
metal–organic
frameworks
(MOFs),
potential
using
machine
learning
(ML)
methods
to
predict
MOF
synthesis
parameters
is
still
untapped.
Here,
we
show
how
ML
can
be
used
for
rationalization
and
acceleration
discovery
process
by
directly
predicting
conditions
a
based
on
its
crystal
structure.
Our
approach
on:
i)
establishing
first
database
via
automatic
extraction
from
literature,
ii)
training
optimizing
models
employing
database,
iii)
new
structures.
The
models,
even
at
an
initial
stage,
exhibit
good
prediction
performance,
outperforming
human
expert
predictions,
obtained
through
survey.
automated
available
web‐tool
https://mof‐synthesis.aimat.science
.
