Multiscale and Multidisciplinary Modeling Experiments and Design,
Journal Year:
2024,
Volume and Issue:
7(4), P. 3153 - 3172
Published: May 27, 2024
Abstract
The
urgent
need
for
sustainable
energy
solutions
in
light
of
escalating
global
demands
and
environmental
concerns
has
brought
hydrogen
to
the
forefront
as
a
promising
renewable
resource.
This
study
provides
comprehensive
analysis
technologies
essential
production
operation
fuel
cell
vehicles,
which
are
emerging
viable
alternative
traditional
combustion
engine
vehicles.
It
examines
various
types,
storage
methods,
refueling
logistics,
role
batteries
paper
also
explores
potential
impact
advancements
artificial
intelligence
quantum
computing
on
development
A
assessment
reveals
that
South
Korea
(19,270)
United
States
(12,283)
leading
adoption
fuel-cell
particularly
passenger
car
segment
(82%),
followed
by
buses
(9.2%)
trucks
(8.7%).
highlights
challenges
hindering
vehicle
implementation,
such
consistent
investment
collaboration
among
industry
stakeholders
promote
transportation
systems.
underscores
practicality
exemplified
models
like
Toyota
Mirai
Hyundai
Nexo,
offer
significant
driving
ranges
demonstrate
integration
advanced
technologies.
discusses
benefits
including
their
ability
operate
with
zero
emissions
when
paired
sources.
Graphical
Advanced Functional Materials,
Journal Year:
2024,
Volume and Issue:
unknown
Published: July 23, 2024
Abstract
Mg‐based
hydrogen
storage
materials
have
drawn
considerable
attention
as
the
solution
for
and
transportation
due
to
their
high
density,
low
cost,
safety
characteristics.
However,
practical
applications
are
hindered
by
dehydrogenation
temperatures,
equilibrium
pressure,
sluggish
hydrogenation
(de/hydrogenation)
rates.
These
functionalities
typically
determined
thermodynamic
kinetic
properties
of
de/hydrogenation
reactions.
This
review
comprehensively
discusses
how
compositeization,
catalysts,
alloying,
nanofabrication
strategies
can
improve
performances
materials.
Since
introduction
various
additives
leads
samples
being
a
multiple‐phases
elements
system,
prediction
methods
simultaneously
introduced.
In
last
part
this
review,
advantages
disadvantages
each
approach
discussed
summary
emergence
new
potential
realizing
lower‐cost
preparation,
lower
operation
temperature,
long‐cycle
is
provided.
Energies,
Journal Year:
2024,
Volume and Issue:
17(16), P. 4070 - 4070
Published: Aug. 16, 2024
This
review
aims
to
summarize
the
recent
advancements
and
prevailing
challenges
within
realm
of
hydrogen
storage
transportation,
thereby
providing
guidance
impetus
for
future
research
practical
applications
in
this
domain.
Through
a
systematic
selection
analysis
latest
literature,
study
highlights
strengths,
limitations,
technological
progress
various
methods,
including
compressed
gaseous
hydrogen,
cryogenic
liquid
organic
solid
material
storage,
as
well
feasibility,
efficiency,
infrastructure
requirements
different
transportation
modes
such
pipeline,
road,
seaborne
transportation.
The
findings
reveal
that
low
density,
high
costs,
inadequate
persist
despite
high-pressure
liquefaction.
also
underscores
potential
emerging
technologies
innovative
concepts,
metal–organic
frameworks,
nanomaterials,
underground
along
with
synergies
renewable
energy
integration
production
facilities.
In
conclusion,
interdisciplinary
collaboration,
policy
support,
ongoing
are
essential
harnessing
hydrogen’s
full
clean
carrier.
concludes
is
vital
global
transformation
climate
change
mitigation.
International Journal of Hydrogen Energy,
Journal Year:
2024,
Volume and Issue:
58, P. 485 - 494
Published: Jan. 25, 2024
Underground
hydrogen
storage
(UHS)
offers
a
promising
approach
for
the
of
significant
volumes
gas
(H2)
within
deep
geological
formations,
which
can
later
be
utilized
energy
generation
when
necessary.
Interfacial
tension
(IFT)
between
H2
and
formation
brine
plays
vital
role
in
influencing
distribution
at
pore
scale
and,
ultimately,
capacity.
In
this
research,
we
developed
four
intelligent
models:
Decision
Trees
(DT),
Random
Forests
(RF),
Support
Vector
Machines
(SVM),
Multi-Layer
Perceptron
(MLP).
These
models
were
designed
to
predict
IFT
utilizing
pressure,
temperature,
molality.
Additionally,
fine-tuned
three
explicit
correlations
previously
our
research.
To
assess
influence
each
parameter
on
IFT,
conducted
comprehensive
analysis
raw
data
exclude
doubtful
samples.
This
was
followed
by
rigorous
model
development,
including
hyperparameter
tuning,
finally,
an
examination
using
testing
data.
The
results
clearly
demonstrate
superiority
RF
model,
achieving
high
accuracy
reliability
with
coefficients
determination
(R2),
root
mean
square
error
(RMSE),
average
absolute
relative
deviation
(AARD)
values
0.96,
1.50,
1.84
%,
respectively.
exemplary
performance
attributed
its
inherent
characteristics.
ensemble
excels
capturing
complex
relationships,
thereby
enhancing
predictive
solidifying
over
other
study.
Furthermore,
feature
importance
revealed
that
temperature
has
most
influence,
molality
pressure.
Moreover,
assessed
these
through
external
not
used
initial
training
stages.
Our
study
highlights
exceptional
power
emphasizing
practical
selecting
enhanced
reliability.
proposed
method
shows
potential
industrial
applications,
especially
optimizing
underground
storage.
