Processes,
Год журнала:
2024,
Номер
12(9), С. 1826 - 1826
Опубликована: Авг. 28, 2024
A
promising
method
for
converting
greenhouse
gases
such
as
CO2
and
CH4
into
useful
syngas
is
the
dry
reformation
of
methane
(DRM).
5Ni-ZSM-5
2
wt.%
Ce,
Cs,
Sr,
Fe,
Cu-promoted
catalysts
are
investigated
DRM
at
700
°C
under
atmospheric
pressure.
The
characterization,
including
XRD,
TPR,
TPD,
TPO,
N2
adsorption–desorption,
TGA,
TEM,
Raman
spectroscopy,
revealed
that
catalyst’s
active
sites
distributed
throughout
pore
channels
on
surface,
contributing
to
stability
catalyst.
Specifically,
CO2-TPO
followed
by
O2-TPO
experiment
using
spent
confirmed
oxidizing
capacity
during
reaction.
Ce-promoted
catalyst
showed
greatest
increase
in
catalytic
activity
among
other
catalysts.
5Ni+2Ce-ZSM-5
exhibited
twice
concentration
acid
compared
Cs-promoted
counterpart,
even
though
both
achieved
similar
quantities
basic
sites.
Without
compromising
H2
CO
selectivity,
this
finding
underscores
crucial
role
enhancing
conversion.
With
a
GHSV
42,000
mL/(h.gcat),
demonstrated
impressive
conversion
rates
42%
70%
800
°C.
reactants
spend
more
time
over
subsequent
reduction
21,000
resulting
best
performance
with
80%
83%
conversions.
Hydrogenation
saturation
of
phenanthrene
(a
typical
component
coal
tar)
could
not
only
improve
the
combustion
performance
fuel
oil,
but
also
obtain
raw
material
for
preparing
high-energy-density
fuel.
Nickel-based
catalysts
have
been
considered
promising
hydrogenation
due
to
their
appealing
capacity
activate
molecules.
However,
Ni
derivation
precursor
greatly
affects
its
activity.
In
this
work,
NiAl2O4
catalyst
was
obtained
by
sol-gel
method.
Under
experimental
conditions
temperature
300
°C,
pressure
5
MPa,
and
WHSV
0.52
h-1,
conversion
over
can
be
up
99.7
93.9%
perhydrophenanthrene
yield,
while
those
traditional
Ni/Al2O3
are
just
96.8
77.3%,
respectively.
Moreover,
TOF
(3.01
×
10-3
s-1)
surpasses
that
(2.46
s-1),
which
indicates
derived
from
has
stronger
According
relevant
characterizations,
superior
derives
H2
adsorption
dissociation
ability
formation
an
electron-deficient
structure
active
metal
Ni,
contributes
improved
activation
polycyclic
aromatic
hydrocarbons.
Arabian Journal of Chemistry,
Год журнала:
2023,
Номер
17(2), С. 105564 - 105564
Опубликована: Дек. 19, 2023
Carbon
Capture
and
Utilization
(CCU)
technologies
offer
a
promising
avenue
for
transforming
captured
CO2
into
valuable
products,
serving
as
renewable
fuels
or
precursors
high-value
synthesis.
This
study
explores
the
dry
reforming
of
methane
(DRM)
viable
pathway
to
convert
CH4
syngas,
achieving
high
equilibrium
conversion
through
use
suitable
catalysts.
Conventional
nickel-based
catalysts
are
susceptible
carbon
deposition,
necessitating
innovative
approaches
enhance
their
performance.
A
tubular
microreactor
was
employed
conduct
process
at
800
°C,
utilizing
Cs-promoted
Ni
supported
on
90
%
Al2O3
10
ZrO2-based
support
composition.
Catalyst
preparation
involved
impregnation
technique,
subsequent
characterization
N2-physisorption,
XRD,
H2-TPR,
TGA,
TPD,
Raman
spectroscopy.
The
DRM
reaction
systematically
investigated
using
Ni/
ZrO2-
catalysts,
with
specific
focus
catalytic
effects
Cs
promotion.
Observations
revealed
that
incorporation
onto
matrix
led
substantial
increase
in
hydrogen
yield
selectivity
across
all
catalyst
compositions,
accompanied
by
significant
reduction
deposition
surface.
optimal
loading,
determined
be
3
wt%
over
catalyst,
exhibited
conversions
87
%,
respectively,
an
H2/CO
approaching
1
(0.95).
research
underscores
potential
Cs-modified
enhancing
efficiency
CCU
applications,
providing
insights
optimizing
formulations
improved
performance
transformation
processes.
Molecular Catalysis,
Год журнала:
2024,
Номер
562, С. 114216 - 114216
Опубликована: Май 13, 2024
This
study
investigates
the
molecular
dynamics
of
methane
dry
reforming
catalyzed
by
a
novel
nickel-strontium-zirconium-aluminum
(5Ni+3Sr/10Zr+Al)
catalyst,
leveraging
both
Response
Surface
Methodology
(RSM)
and
Radial
Basis
Function
Neural
Network
(RBFNN)
for
predictive
optimization.
Focusing
on
impact
operational
parameters—hourly
space
velocity,
reaction
temperature,
CO2:CH4
mole
ratio—on
conversion
rates
formation
components,
we
aim
to
predict
optimal
conditions
corresponding
process
variables.
Through
comparison
three-layer
Feed
Forward
Network,
optimized
at
3:10:1
topology,
with
traditional
RSM
approaches,
our
findings
highlight
superior
capabilities
ANN
models.
Notably,
demonstrated
exceptional
performance
Radj2and
F_Ratio
values
significantly
surpass
those
RSM,
alongside
lower
statistical
error
terms.
superiority
is
attributed
ANN's
robust
handling
nonlinear
relationships
between
inputs
outputs,
asserting
its
potential
enhancing
accuracy
in
chemical
At
optimum
predicted
like
1
CH4/CO2,750
°C
12000
cm3g−1h−1
NiSrZrAl
outperformed
>
85
%
CH4
CO2
H2/CO
∼1
up
20
h
time
stream.
Our
research
underscores
importance
integrating
advanced
modeling
techniques
efficient
accurate
prediction
catalytic
reactions,
offering
valuable
insights
future
applications
engineering
catalysis.
