Applied Sciences,
Journal Year:
2024,
Volume and Issue:
14(23), P. 10992 - 10992
Published: Nov. 26, 2024
In
this
work,
a
novel
method
of
viscosity
measurement
is
proposed
using
device
comprising
compliant
mechanism,
vibration
source,
and
piezoelectric
sensor.
The
source
creates
linear
harmonic
vibrations
in
the
mechanism
suspended
liquid,
acceleration
response
measured
located
central
mass
which
designed
to
have
necessary
directional
stiffness.
As
vibrates,
links
undergo
damping
due
shearing
action
fluid
because
its
viscosity.
A
series
measurements
are
carried
out
with
use
water–glycerol
solutions
such
that
influenced
by
fluid’s
During
working
device,
immersed
liquid
whose
be
measured.
recorded
as
time
domain
data
NI
Lab
View
hardware
software,
used
train
machine
learning
model.
Later,
regression-based
model
for
estimation
dynamic
given
input.
Experiments
performed
prototype
solution
within
ranging
from
10
cP
60
cP.
sensor
can
in-line
or
handheld
instrument
quick
measurements.
achieved
high
level
accuracy,
evidenced
an
R-squared
value
0.99,
indicating
it
explains
99%
variance
data.
Polymers,
Journal Year:
2025,
Volume and Issue:
17(4), P. 499 - 499
Published: Feb. 14, 2025
The
increasing
complexity
of
polymer
systems
in
both
experimental
and
computational
studies
has
led
to
an
expanding
interest
machine
learning
(ML)
methods
aid
data
analysis,
material
design,
predictive
modeling.
Among
the
various
ML
approaches,
boosting
methods,
including
AdaBoost,
Gradient
Boosting,
XGBoost,
CatBoost
LightGBM,
have
emerged
as
powerful
tools
for
tackling
high-dimensional
complex
problems
science.
This
paper
provides
overview
applications
science,
highlighting
their
contributions
areas
such
structure-property
relationships,
synthesis,
performance
prediction,
characterization.
By
examining
recent
case
on
techniques
this
review
aims
highlight
potential
advancing
characterization,
optimization
materials.
Scientific Reports,
Journal Year:
2024,
Volume and Issue:
14(1)
Published: Nov. 27, 2024
Abstract
Optimization
of
thermophysical
properties
(TPPs)
MXene-based
nanofluids
is
essential
to
increase
the
performance
hybrid
solar
photovoltaic
and
thermal
(PV/T)
systems.
This
study
proposes
a
approach
optimize
TPPs
Ionanofluids.
The
input
variables
are
MXene
mass
fraction
(MF)
temperature.
optimization
objectives
include
three
TPPs:
specific
heat
capacity
(SHC),
dynamic
viscosity
(DV),
conductivity
(TC).
In
proposed
approach,
powerful
group
method
data
handling
(GMDH)-type
ANN
technique
used
model
in
terms
variables.
obtained
models
integrated
into
multi-objective
particle
swarm
(MOPSO)
exchange
(MOTEO)
algorithms,
forming
three-objective
problem.
final
step,
TOPSIS
technique,
one
well-known
multi-criteria
decision-making
(MCDM)
approaches,
employed
identify
desirable
Pareto
points.
Modeling
results
showed
that
developed
for
TC,
DV,
SHC
demonstrate
strong
by
R-values
0.9984,
0.9985,
0.9987,
respectively.
outputs
MOPSO
revealed
points
dispersed
broad
range
MFs
(0-0.4%).
However,
temperature
these
optimal
was
found
be
constrained
within
narrow
near
maximum
value
(75
°C).
scenarios
where
TC
precedes
other
objectives,
recommended
utilizing
an
MF
over
0.2%.
Alternatively,
when
DV
holds
greater
importance,
decision-makers
can
opt
ranging
from
0.15
0.17%.
Also,
becomes
primary
concern,
advised
base
fluid
without
any
additive.
Cureus,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Oct. 5, 2024
Background
Environmental
contamination
resulting
from
the
release
of
untreated
industrial
wastewater
has
emerged
as
a
critical
worldwide
issue.
These
effluents
frequently
have
high
levels
heavy
metals
and
antibiotics,
which
are
bad
for
aquatic
ecosystems
human
health.
Oftentimes,
conventional
treatment
techniques
fall
short
effectively
eliminating
these
pollutants.
Innovative
materials
that
may
efficiently
absorb
or
break
down
contaminants
contaminated
water
sources
are,
therefore,
desperately
needed.
Hydrothermally
produced
MXene
cadmium
sulfide
(CdS)
composites
shown
great
promise
an
adsorbent
material
because
their
special
qualities,
include
surface
area,
chemical
stability,
customizable
functions
improve
adsorption
capacity
antibiotics
alike.
Aim
The
aim
this
study
is
to
produce
MXene-CdS
nanoparticles
in
cost-effective
method
simultaneous
removal
aqueous
pollution
control.
Methods
MXenes
were
synthesized
by
selectively
etching
Ti