Analysis of Response Surface and Artificial Neural Network for Cr(Ⅵ) Removal Column Experiment
Water,
Год журнала:
2025,
Номер
17(8), С. 1211 - 1211
Опубликована: Апрель 18, 2025
In
this
study,
inexpensive,
environmentally
friendly,
and
biodegradable
cellulose
filter
paper
was
used
to
load
nano
zero-valent
iron
(nZVI),
effectively
improving
the
dispersibility
of
nZVI
successfully
preparing
supported
modified
(FP-nZVI).
Subsequently,
capacity
FP-nZVI
remove
Cr(VI)
in
a
flow
system
explored.
characterized
by
scanning
electron
microscopy
(SEM),
Fourier
transform
infrared
spectroscopy
(FTIR),
X-ray
diffraction
(XRD).
Traditional
single-factor
experiments
often
require
large
number
repeated
when
analyzing
interactions
among
multiple
variables,
resulting
long
experimental
cycle
high
consumption
materials.
This
research
Response
Surface
Methodology
(RSM)
based
on
Box-Behnken
Design
(BBD)
Artificial
Neural
Network
(ANN)
optimize
predict
removal
process
Cr(VI).
RSM
investigated
between
response
variable
(Cr(VI)
rate)
independent
variables
concentration,
pH
value,
rate).
A
highly
significant
quadratic
regression
model
constructed,
which
proven
F
value
(93.92),
an
extremely
low
p-value
(<0.0001),
determination
coefficient
(R2
=
0.9918).
An
ANN
established
forecast
correlation
rate
Both
models
demonstrate
remarkable
consistency
with
data;
however,
from
perspective
statistical
parameters,
has
more
advantages;
R2
reaches
0.9937,
is
higher
than
that
(0.9918);
values
indicators
such
as
MSE,
RMSE,
MAE,
MAPE,
AAD,
SEP
are
all
smaller
those
RSM.
The
exhibits
greater
excellence
prediction
error,
fluctuation,
closeness
actual
excellent
ability.
experiment
for
treating
optimized,
achieving
good
results.
Meanwhile,
it
also
provides
valuable
reference
similar
studies.
Язык: Английский
Extraction Process Research and Characterization of Microcrystalline Cellulose Derived from Bamboo (Phyllostachys edulis (Carrière) J. Houz.) Fibers
Polymers,
Год журнала:
2025,
Номер
17(9), С. 1143 - 1143
Опубликована: Апрель 23, 2025
Microcrystalline
cellulose
(MCC)
possesses
important
attributes,
including
high
crystallinity,
a
large
surface
area,
excellent
mechanical
strength,
chemical
stability,
and
biodegradability.
This
study
aims
to
research
MCC
extraction
from
bamboo
(Phyllostachys
edulis
(Carrière)
J.
Houz.)
fiber
by
assessing
the
impact
of
key
processing
variables
such
as
acid
concentration,
temperature,
hydrolysis
duration.
Experimental
results
indicate
that
time
hydrochloric
(HCl)
concentration
significantly
influence
yield.
After
evaluating
effects
various
conditions,
optimal
parameters
were
determined
be
2.0
M
HCl
90
°C,
10
min
reaction
time.
The
produced
under
conditions
displayed
improved
crystallinity
(77.2%)
while
retaining
functional
groups
similar
those
found
in
raw
bamboo.
Morphological
analysis
revealed
an
irregular
rod-like
shape
with
rough
surfaces.
optimized
process
offers
viable
approach
for
production
holds
potential
precursor
developing
environmentally
friendly
biodegradable
materials.
Язык: Английский