Nanomaterials,
Journal Year:
2024,
Volume and Issue:
14(22), P. 1789 - 1789
Published: Nov. 7, 2024
Functionalized
nanomaterials
with
surface-active
groups
have
garnered
significant
research
interest
due
to
their
wide-ranging
applications,
particularly
in
water
treatment
for
removing
various
contaminants.
This
study
focuses
on
developing
a
novel,
multi-functional
nanobiosorbent
by
synthesizing
nanosized
biochar
from
artichoke
leaves
(NBAL)
and
molybdic
acid
(MA).
The
resulting
nanobiosorbent,
MA@NBAL,
is
produced
through
microwave-irradiation
process,
offering
promising
material
enhanced
environmental
remediation.
characteristics
of
assembled
MA@NBAL
were
evaluated
SEM-EDX,
XPS,
TGA,
FT-IR,
zeta
potential
detection.
size
particles
ranged
18.7
23.7
nm.
At
the
same
time,
EDX
analysis
denoted
existence
several
major
elements
related
percentage
values
carbon
(52.9%),
oxygen
(27.6%),
molybdenum
(8.8%),
nitrogen
(4.5%)
nanobiosorbent.
effectiveness
Hg(II)
ions
was
monitored
via
batch
method.
optimized
maximum
removal
capacity
onto
established
at
pH
6.0,
30.0
min
equilibrium
20
mg
providing
1444.25
mg/g
10.0
mmol/L
concentration
Hg(II).
Kinetic
studies
revealed
that
adsorption
process
followed
pseudo-second-order
model,
R
Energies,
Journal Year:
2024,
Volume and Issue:
17(21), P. 5254 - 5254
Published: Oct. 22, 2024
Hydrothermal
liquefaction
(HTL)
is
an
effective
biomass
thermochemical
conversion
technology
that
can
convert
organic
waste
into
energy
products.
However,
the
HTL
process
influenced
by
various
complex
factors
such
as
operating
conditions,
feedstock
properties,
and
reaction
pathways.
Machine
learning
(ML)
methods
utilize
existing
data
to
develop
accurate
models
for
predicting
product
yields
which
be
used
optimize
operation
conditions.
This
paper
presents
a
bibliometric
review
on
ML
applications
in
from
2020
2024.
CiteSpace,
VOSviewer,
Bibexcel
were
analyze
seven
key
attributes:
annual
publication
output,
author
co-authorship
networks,
country
co-citation
of
references,
journals,
collaborating
institutions,
keyword
co-occurrence
well
time
zone
maps
timelines,
identify
development
research.
Through
detailed
analysis
co-occurring
keywords,
this
study
aims
frontiers,
research
gaps,
trends
field
ML-aided
HTL.
