Advanced Materials,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Aug. 28, 2024
Protonic
ceramic
electrochemical
cells
(PCECs)
have
received
considerable
attention
as
they
can
directly
generate
electricity
and/or
produce
chemicals.
Development
of
the
electrodes
with
trifunctionalities
oxygen
reduction/evolution
and
nonoxidative
ethane
dehydrogenation
is
yet
challenging.
Here
these
findings
are
reported
in
design
trifunctional
for
PCECs
a
detailed
composition
Mn
Journal of Materials Chemistry A,
Journal Year:
2024,
Volume and Issue:
12(29), P. 18175 - 18181
Published: Jan. 1, 2024
The
Zn-doped
BCF36
cathode
boosts
proton
conductivity,
lowers
hydration
energy
and
achieves
a
peak
power
density
of
998.6
mW
cm
−2
at
600
°C
with
polarization
resistance
0.151
Ω
2
for
single
cell
the
BCFZ10
cathode.
Advanced Science,
Journal Year:
2023,
Volume and Issue:
11(2)
Published: Nov. 20, 2023
Abstract
Perovskite
oxides
have
emerged
as
alternative
anode
materials
for
hydrocarbon‐fueled
solid
oxide
fuel
cells
(SOFCs).
Nevertheless,
the
sluggish
kinetics
hydrocarbon
conversion
hinder
their
commercial
applications.
Herein,
a
novel
dual‐exsolved
self‐assembled
CH
4
‐fueled
SOFCs
is
developed.
The
designed
Ru@Ru‐Sr
2
Fe
1.5
Mo
0.5
O
6‐δ
(SFM)/Ru‐Gd
0.1
Ce
0.9
2‐δ
(GDC)
exhibits
unique
hierarchical
structure
of
nano‐heterointerfaces
exsolved
on
submicron
skeletons.
As
result,
Ru@Ru‐SFM/Ru‐GDC
anode‐based
single
cell
achieves
high
peak
power
densities
1.03
and
0.63
W
cm
−2
at
800
°C
under
humidified
H
,
surpassing
most
reported
perovskite‐based
anodes.
Moreover,
this
demonstrates
negligible
degradation
over
200
h
in
indicating
resistance
to
carbon
deposition.
Density
functional
theory
calculations
reveal
that
created
metal‐oxide
heterointerfaces
Ru@Ru‐SFM
Ru@Ru‐GDC
higher
intrinsic
activities
compared
pristine
SFM.
These
findings
highlight
viable
design
efficient
robust
SOFCs.
Energy Reviews,
Journal Year:
2024,
Volume and Issue:
4(1), P. 100106 - 100106
Published: Aug. 10, 2024
Energy
drives
the
development
of
human
civilization,
and
hydrogen
energy
is
an
inevitable
choice
under
goal
"global
transition".
As
technology
continues
to
advance,
solid-state
storage
materials
have
attracted
significant
attention
as
efficient
solution
for
storage.
However,
existing
research
methods,
such
experimental
preparation
theoretical
calculations,
are
inefficient
costly.
Here,
we
summarize
latest
advancements
high-throughput
screening
(HTS)
machine
learning
(ML)
materials.
It
elaborates
on
advantages
HTS
ML
in
rapid
material
screening,
performance
assessment
prediction,
so
on.
We
place
particular
emphasis
exploration
analysis
progress
involving
application
various
types
Additionally,
discuss
integrating
ML,
emphasizing
this
comprehensive
strategy
field
In
realm
storage,
artificial
intelligence
plays
a
dual
role.
not
only
enhances
efficiency
but
also
offers
novel
tools
future
design
development.
This
will
aid
discovery
new-type
high-performance
materials,
facilitate
their
commercialization
practical
application.