Inorganic Chemistry,
Год журнала:
2024,
Номер
63(7), С. 3317 - 3326
Опубликована: Фев. 8, 2024
A
new
3D
zinc-based
metal–organic
framework
{[Zn7L2(DMF)3(H2O)(OH)2]·5DMF}n
(1)
(H6L
=
5,5′,5″-(methylsilanetriyl)
triisophthalic
acid)
was
constructed
with
an
organosilicon-based
linker,
where
H6L
is
a
tetrahedral
structure
furnished
rich
−COO–
chelating
sites
for
Zn(II)
immobilization.
Compound
1
exhibited
two
types
of
irregular
one-dimensional
channels
and
three-dimensional
skeleton
large
specific
surface
area,
making
it
promising
catalytic
platform.
Moreover,
by
incorporation
the
second
metal
ion
into
inorganic
node
1,
isomorphic
bimetallic
MOF
ZnMg-1
successfully
synthesized.
demonstrated
enhanced
activity
compared
to
under
identical
conditions.
Contrast
experiments
theoretical
calculations
indicate
that
active
play
facilitating
role
in
chemical
fixation
epoxides
CO2.
It
indicated
efficient
CO2
cyclic
carbonates
obtained
over
catalysts
ZnMg-1.
Catalysts,
Год журнала:
2023,
Номер
13(7), С. 1143 - 1143
Опубликована: Июль 23, 2023
The
use
of
metal
oxide
nanomaterials
as
photocatalysts
for
wastewater
treatment
has
received
significant
attention
in
recent
years
due
to
their
unique
physicochemical
properties.
In
this
study,
we
a
polyol-mediated
refluxing
method
synthesize
silver-incorporated
copper
(Ag@CuO
NMs).
tetra
butyl
ammonium
bromide
(TBAB)
capping
agent
and
ethylene
glycol
reducing
Ag+
Ag
is
elaborated
upon.
prepared
Ag@CuO
NMs
were
tested
ability
degrade
water
pollutants,
specifically
methylene
blue
(MB)
dye.
Two
different
contents,
weights
3%
5%,
used
produce
modified
CuO-based
nanomaterials.
crystalline
structures
the
characterized
via
XRD
diffraction,
morphology
materials
was
investigated
using
FE-SEM.
optical
properties
studied
UV-vis
spectroscopy.
photocatalytic
activity
evaluated
by
analyzing
degradation
MB
dye
when
exposed
UV-visible
light.
Our
results
showed
that
5%
weight
NM
sample
exhibited
most
efficient
against
Therefore,
these
hold
potential
applications,
particularly
purification.
RSC Advances,
Год журнала:
2024,
Номер
14(18), С. 12496 - 12512
Опубликована: Янв. 1, 2024
Assessment
of
the
performance
linear
and
nonlinear
regression-based
methods
for
estimating
in
situ
catalytic
CO2
transformations
employing
TiO2/Cu
coupled
with
hydrogen
exfoliation
graphene
(HEG)
has
been
investigated.
The
yield
methanol
was
thoroughly
optimized
predicted
using
response
surface
methodology
(RSM)
artificial
neural
network
(ANN)
model
after
rigorous
experimentation
comparison.
Amongst
different
types
HEG
loading
from
10
to
40
wt%,
30
wt%
HEG-TiO2/Cu
assisted
photosynthetic
catalyst
found
be
successful
providing
highest
conversion
efficiency
CO2.
most
influencing
parameters,
dosing
inflow
rate
CO2,
were
affect
acidic
reaction
regime
(at
pH
3).
According
RSM
ANN,
optimum
yields
36.3
mg
g-1
37.3
catalyst,
respectively.
Through
comparison
performances
least
squared
error
analysis,
ANN
showed
a
better
determination
coefficient
(overall
R2
>
0.985)
than
∼
0.97).
Even
though
both
models
performed
well,
consisting
9
neurons
input
1
hidden
layer,
could
predict
results
closer
terms
agreement
experimental
outcome.
