IOP Conference Series Earth and Environmental Science,
Journal Year:
2023,
Volume and Issue:
1281(1), P. 012038 - 012038
Published: Dec. 1, 2023
Abstract
Phase
change
materials
(PCMs)
stores
and
releases
thermal
energy
in
the
form
of
latent
heat
during
phase
transition.
Though
PCMs
are
durable
nature,
they
suffer
commercial
application
owing
to
low
conductivity.
Inclusion
metal
carbon
based
nanoparticles
typically
adopted
overcome
complication
poor
conducting
nature
organic
PCMs.
In
this
experimental
research
we
develop
a
bio
nanoparticle
using
coconut
shell
an
environmental
friendly
manner
enhance
conductivity
PCM
polyethylene
glycol
1000.
Bio
(BNP)
improves
developed
nanocomposite
by
73.1%
with
0.9
wt%
BNP
hence
evaluate
thermodynamic
kinetics
parameter
sample
biochar
nanoparticle.
addition
authors
have
analysed
decomposition
optimized
composite
Coats
Redfern
method
exhibit
reaction
mechanism,
kinetic
parameter.
AIMS environmental science,
Journal Year:
2025,
Volume and Issue:
12(1), P. 16 - 52
Published: Jan. 1, 2025
<p>The
extraction
and
utilization
of
crude
oil
are
fundamental
to
global
energy
production,
driving
economies
fueling
countless
industries.
However,
wax
deposition
in
pipelines
equipment
creates
several
challenges,
causing
issues
during
the
transportation,
refining
waxy
oil.
On
other
hand,
conventional
chemicals
such
as
alkylphenol
ethoxylates
(APEs)
volatile
organic
compounds
(VOCs)
used
treatment
have
negative
environmental
human
health
effects.
Nanocomposites
polymers
emerged
promising
solutions
mitigate
damage.
They
represent
a
revolutionary
class
nanocomposite
hybridized
polymer
matrices.
Moreover,
our
knowledge,
there
has
been
lack
comprehensive
reviews
researchers
who
combined
evaluated
effectiveness
these
methods
over
last
decade.
To
gain
understanding
current
state
knowledge
recognize
emerging
research
trends,
this
systematic
review,
we
critically
published
on
role
nanocomposites
environmentally
friendly
management
systems.
This
review
covers
numerous
topics,
including
(1)
spatiotemporal
distribution
nanocomposites,
(2)
synthesis
routes
millennium
(3)
reaction
mechanisms
for
improvement,
(4)
common
trends
applications,
(5)
diverse
candidates
nanomaterials,
(6)
trending
nanoparticle
polymerization,
(7)
future
perspectives.
further
progress
effects
is
hindered
by
comparative
studies
their
toxicity.
despite
limitations,
continue
show
great
promise
addressing
challenges
related
oil.</p>
Heliyon,
Journal Year:
2024,
Volume and Issue:
10(17), P. e36519 - e36519
Published: Aug. 19, 2024
Highlights•A
novel
method
for
optimal
design
and
operation
of
an
energy
hub
in
the
forest
industry.•The
study
examines
system
robustness,
reliability,
cost
efficiency.•Analyzed
link
between
reliability.•Time-series
models
predict
daily
market
electricity
prices
TES
operations.AbstractThermal
storage
(TES)
offers
a
practical
solution
reducing
industrial
costs
by
load-shifting
heat
demands
within
processes.
In
integrated
Thermomechanical
pulping
process,
systems
Energy
Hub
can
provide
paper
machine,
aiming
to
minimize
during
peak
hours.
This
strategic
use
technology
ensures
more
cost-effective
efficient
consumption
management,
leading
overall
operational
savings.
research
presents
optimizing
with
industry.
The
proposed
approach
involves
comprehensive
analysis
dynamic
efficiency,
availability
components.
comprises
conversion
technologies
such
as
electric
boiler
steam
generator
pump.
how
reliability
affects
analyzes
impact
maximum
capacities
its
components
on
reliability.
identifies
point
maximizing
benefits.
To
optimize
system's
charging/discharging
schedule,
advanced
predictive
using
time
series
prediction
models,
including
LSTM
(Long
Short-Term
Memory)
GRU
(Gated
Recurrent
Unit),
has
been
developed
forecast
average
prices.
results
highlight
significant
benefits
from
Hubs,
demonstrating
4.5–6
percent
reduction
depending
reference
year.
Optimizing
improves
availability,
due
unsupplied
demand
penalty
costs.
reach
98
%,
pump
capacity
2
MW
3.4
MW.
showed
superior
accuracy
predicting
compared
LSTM,
indicating
potential
reliable
price
predictor
system.