Heliyon,
Journal Year:
2024,
Volume and Issue:
10(5), P. e26395 - e26395
Published: Feb. 19, 2024
It
is
precarious
to
scrutinize
the
impacts
of
operational
parameters
on
corrosion
when
choosing
materials
for
green
diesel
and
automotive
industries.
This
was
original
study
showcase
an
optimization
stratagem
abating
rates
(CRs)
parts
(APs)
explicitly
copper
brass
in
a
biodiesel
environment,
adopting
novel
Response
Surface
Methodology
(RSM)
Adaptive
Neuro-Fuzzy
Inference
System
(ANFIS).To
model
CRs,
RSM
ANFIS
were
utilized.
The
mechanical
properties
APs
inspected,
their
hardness
number
tensile
strength,
as
well
outward
morphologies.
optimal
CRs
0.01656
mpy
0.008189
at
B
3.91
biodiesel/diesel
blend
240.9-h
exposure.
had
higher
coefficient
determination
lower
values
root
mean
squared
errors
(RMSE),
average
error
(MAE),
absolute
deviation
(AAD)
compared
model;
this
authenticates
model's
superiority
predicting
brass.
strength
greater
than
that
copper,
while
latter
number.
information,
model,
correlations
can
assist
APS
mitigating
slaving
over
corrosiveness
utilizing
diesel.
Fermentation,
Journal Year:
2023,
Volume and Issue:
9(2), P. 120 - 120
Published: Jan. 26, 2023
In
this
work,
sugarcane
vinasse
combined
with
organic
waste
(food
and
wasted
tea)
was
demonstrated
to
be
an
excellent
source
of
biomethane
synthesis
from
carbon-rich
biowaste.
The
discarded
tea
trash
might
successfully
used
generate
bioenergy.
uncertainties
costs
associated
experimental
testing
were
recommended
decreased
by
the
effective
use
contemporary
machine
learning
methods
such
as
Gaussian
process
regression.
training
hyperparameters
are
crucial
in
construction
a
robust
ML-based
model.
To
make
autoregressive,
fine-tuned
employing
Bayesian
approach.
value
R2
found
greater
during
model
test
phase
0.72%,
assisting
avoidance
overtraining.
mean
squared
error
36.243
21.145
phase.
absolute
percentage
under
0.1%,
which
0.085%
throughout
model’s
research
that
combination
trash,
food
may
viable
for
generation.
methodology
approach
tuning
regression
is
efficient
method
prediction
despite
low
correlation
across
data
columns.
It
possible
enhance
sustainability
paradigm
direction
energy
security
via
usage
agroforestry
waste.
ACS Omega,
Journal Year:
2023,
Volume and Issue:
8(46), P. 43771 - 43791
Published: Nov. 8, 2023
There
is
a
lack
of
information
about
the
detailed
characterization
biomass
Nigerian
origin.
This
study
presents
comprehensive
six
biomass,
groundnut
shells,
corncob,
cashew
leaves,
Ixora
coccinea
(flame
woods),
sawdust,
and
lemongrass,
to
aid
appropriate
selection
for
bio-oil
production.
The
proximate,
ultimate,
calorific
value
compositional
analyses
were
carried
out
following
American
Standard
Testing
Materials
(ASTM)
standards.
Fourier
transform
infrared
spectroscopy,
thermogravimetric
analysis,
scanning
electron
microscopy
with
energy-dispersive
X-ray
fluorescence
employed
in
this
functional
group
analyses,
thermal
stability,
structural
analyses.
H/C
O/C
atomic
ratios,
fuel
ratio,
ignitability
index,
combustibility
index
samples
evaluated.
Groundnut
lemongrass
identified
as
promising
feedstocks
production
based
on
their
values
(>20
MJ/kg).
Sawdust
exhibited
favorable
characteristics
indicated
by
its
higher
volatile
matter
(79.28%),
low
ash
content
(1.53%),
moisture
(6.18%),
high
fixed
carbon
(13.01%).
Also,
all
showed
ignition
flammability
properties.
nitrogen
(<0.12%)
sulfur
(<0.04%)
contents
make
them
environmentally
benign
fuels
lower
percentage
NOx
SOx
will
be
released
during
bio-oil.
These
results
are
contributions
advancement
sustainable
efficient
carbon-neutral
energy
mix,
promoting
resource
utilization
generation
energy.
Environmental Science and Pollution Research,
Journal Year:
2024,
Volume and Issue:
31(6), P. 9392 - 9407
Published: Jan. 8, 2024
Abstract
Post-pandemic
inflationist
pressures,
climate
changes
and
extremes,
regional
conflicts,
soaring
food
prices
caused
the
crisis
to
increase
rapidly
worldwide.
This
global
problem
directs
producers
researchers
use
oils
used
as
feedstock
in
biodiesel
production
effectively.
In
this
context,
it
is
important
assay
transesterification
parameters
conduct
new
optimization
studies
yield.
study,
methyl
ester
was
produced
from
hemp
oil
by
using
sodium
hydroxide
(NaOH).
Next,
classical
study
carried
out
determine
effects
of
catalyst
amount,
alcohol:oil
molar
ratio,
reaction
temperature,
time
variables
on
Secondly,
cubic
spline
mathematical
model
(CSMM)
polynomial
regression
(PRMM)
were
applied
first
data
optimization.
Among
these
methods,
utmost
yield
registered
96.115%
at
seed
(HSO):methanol
ratio
5.59:1,
concentration
0.531
wt%,
temperature
42.5
°C,
62.1
min,
agitation
intensity
600
rpm
PRMM.
Some
vital
fuel
properties
obtained
HSO
biodiesels
a
result
three
optimizations
satisfied
EN
14214
standard.
The
results
illustrated
that
optimal
yields
CSMM
PRMM
are
0.765%
1.065%
higher,
respectively,
according
maximum
efficiency
outcomes
showed
cost-effective,
easy
handle,
promising
approaches.
Energy Reports,
Journal Year:
2024,
Volume and Issue:
11, P. 1580 - 1589
Published: Jan. 21, 2024
This
paper
aims
to
prepare
and
evaluate
the
physicochemical
energetic
properties
of
briquette
fuel
made
from
cocoa
pod
husk.
For
preparation,
husk
was
dried,
carbonised,
crushed,
mixed
using
binder,
compacted,
finally
briquettes
obtained
were
dried.
The
produced
characterised
by
proximate
analysis,
ultimate
infrared
spectroscopy,
thermogravimetric
analysis
American
Society
for
Testing
Materials
(ASTM)
European
Committee
Standardisation
(CEN)
standards.
results
proximal
(10.5%),
(6.5%),
(34.7%),
(58.8%),
respectively,
moisture
content,
ash
volatile
matter,
fixed
carbon,
are
satisfactory
values.
found
53.2%,
5.2%,
34.4%,
hydrogen,
oxygen
while
H/C
O/C
gave
1.17
0.48,
respectively.
Higher
Heating
Value
(17.941
MJ/kg)
proved
high
thermal
stability,
with
highest
mass
loss
32.50%
at
361°C
due
extractive
content
aromatic
structure
polymer.
presence
C-O,
CC,
CHx,
OH
groups
noticed,
value
index
(FVI)
impact
resistance
(IRI)
showed
1104%
125%,
These
indicated
that
abundance
these
residues
in
landfills
could
serve
as
an
alternative
energy
source
environmental
friendly
features
contribute
economic
growth
country.
JOIV International Journal on Informatics Visualization,
Journal Year:
2024,
Volume and Issue:
8(1), P. 55 - 55
Published: March 16, 2024
Integrating
machine
learning
(ML)
and
artificial
intelligence
(AI)
with
renewable
energy
sources,
including
biomass,
biofuels,
engines,
solar
power,
can
revolutionize
the
industry.
Biomass
biofuels
have
benefited
significantly
from
implementing
AI
ML
algorithms
that
optimize
feedstock,
enhance
resource
management,
facilitate
biofuel
production.
By
applying
insight
derived
data
analysis,
stakeholders
improve
entire
supply
chain
-
biomass
conversion,
fuel
synthesis,
agricultural
growth,
harvesting
to
mitigate
environmental
impacts
accelerate
transition
a
low-carbon
economy.
Furthermore,
in
combustion
systems
engines
has
yielded
substantial
improvements
efficiency,
emissions
reduction,
overall
performance.
Enhancing
engine
design
control
techniques
produces
cleaner,
more
efficient
minimal
impact.
This
contributes
sustainability
of
power
generation
transportation.
are
employed
analyze
vast
quantities
photovoltaic
systems'
design,
operation,
maintenance.
The
ultimate
goal
is
increase
output
system
efficiency.
Collaboration
among
academia,
industry,
policymakers
imperative
expedite
sustainable
future
harness
potential
energy.
these
technologies,
it
possible
establish
ecosystem,
which
would
benefit
generations.
