Energies,
Год журнала:
2024,
Номер
17(17), С. 4396 - 4396
Опубликована: Сен. 2, 2024
The
integration
of
renewable
energy
sources
into
an
grid
introduces
volatility,
challenging
stability
and
reliability.
To
address
these
challenges,
this
work
proposes
a
two-stage
optimization
approach
for
the
operation
electrolyzers
used
in
green
hydrogen
production.
This
method
combines
site-wide
real-time
to
manage
fluctuating
supply
effectively.
By
leveraging
dual
use
existing
model,
it
is
applied
both
optimization,
enhancing
consistency
efficiency
control
strategy.
Site-wide
generates
long-term
operational
plans
based
on
forecasts,
while
adjusts
response
immediate
fluctuations
availability.
validated
through
case
study
showing
that
can
accommodate
forecast
deviations
up
15%,
resulting
production
6.5%
higher
than
initially
planned
during
periods
increased
framework
not
only
optimizes
electrolyzer
operations
but
also
be
other
flexible
resources,
supporting
sustainable
economically
viable
management.
Advanced Science,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 19, 2025
Abstract
Seawater
electrolysis
holds
great
promise
for
sustainable,
green
hydrogen
production
but
faces
challenges
of
high
overpotentials
and
competing
chlorine
evolution
reaction
(CER).
Replacing
the
oxygen
with
methanol
oxidation
(MOR)
presents
a
compelling
alternative
due
to
its
lower
anodic
potential
which
mitigates
risk
CER.
While
NiOOH
is
known
MOR
activity,
performance
limited
by
sluggish
non‐electrochemical
kinetics
Cl‐induced
degradation.
Herein,
MoO
4
2−
‐modified
electrocatalyst
reported
that
significantly
enhances
MOR‐assisted
seawater
splitting
efficiency.
In
situ
leached
from
heterojunction
optimizes
adsorption
facilitates
proton
migration,
thereby
accelerating
steps
in
MOR.
Additionally,
adsorbed
effectively
repels
Cl
−
,
protecting
electrodes
‐induced
corrosion.
The
electrolyzer
using
NiMo||Ni(OH)
2
/NiMoO₄
requires
only
1.312
V
achieve
10
mA
cm
−2
substantially
than
conventional
alkaline
(1.576
V).
Furthermore,
it
demonstrates
remarkable
stability,
sustaining
current
densities
(up
1.0
A
)
over
130
h.
This
work
promising
strategy
designing
high‐performance
electrocatalysts
efficient
sustainable
seawater.
Deleted Journal,
Год журнала:
2024,
Номер
1(3), С. 100029 - 100029
Опубликована: Июль 19, 2024
Electrocatalytic
conversion
of
CO2
into
valuable
products
is
a
promising
approach
toward
mitigating
climate
change
and
energy
crisis.
However,
the
product
diversity
multi-electron
transfer
pathways
drive
development
numerous
strategies
for
catalyst
component
active
site
modifications,
leading
to
long
journey
rational
electrocatalyst
design.
The
integration
machine
learning
(ML)
with
experimental
workload
provides
an
opportunity
speed
up
materials
discovery
by
automatically
exploiting
trends
patterns
from
database.
This
review
focuses
on
interpretability
ML
models
in
design,
demonstrates
reliable
workflow
based
adequate
catalytic
data
refined
descriptors,
satisfactory
configuration
model
appropriate
human
intervention.
Moreover,
combination
data-driven
techs
cutting-edge
methodologies
also
discussed,
which
can
serve
as
bridge
between
contemporary
catalysis
quantum
chemistry.
may
provoke
more
ML-based
innovations
rationalization
design
novel
net-zero
industries.
