Progress in Energy,
Journal Year:
2024,
Volume and Issue:
6(4), P. 042005 - 042005
Published: Aug. 21, 2024
Abstract
The
development
and
design
of
energy
materials
are
essential
for
improving
the
efficiency,
sustainability,
durability
systems
to
address
climate
change
issues.
However,
optimizing
developing
can
be
challenging
due
large
complex
search
spaces.
With
advancements
in
computational
power
algorithms
over
past
decade,
machine
learning
(ML)
techniques
being
widely
applied
various
industrial
research
areas
different
purposes.
material
community
has
increasingly
leveraged
ML
accelerate
property
predictions
processes.
This
article
aims
provide
a
comprehensive
review
fields
that
employ
techniques.
It
begins
with
foundational
concepts
broad
overview
applications
research,
followed
by
examples
successful
design.
We
also
discuss
current
challenges
our
perspectives.
Our
viewpoint
is
will
an
integral
component
but
data
scarcity,
lack
tailored
algorithms,
experimentally
realizing
ML-predicted
candidates
major
barriers
still
need
overcome.
Advanced Materials,
Journal Year:
2024,
Volume and Issue:
36(13)
Published: Jan. 4, 2024
Searching
for
new
high-performance
thermoelectric
(TE)
materials
that
are
economical
and
environmentally
friendly
is
an
urgent
task
TE
society,
but
the
advancements
greatly
limited
by
time-consuming
high
cost
of
traditional
trial-and-error
method.
The
significant
progress
achieved
in
computing
hardware,
efficient
methods,
advance
artificial
intelligence
algorithms,
rapidly
growing
material
data
have
brought
a
paradigm
shift
investigation
materials.
Many
electrical
thermal
performance
descriptors
proposed
high-throughput
(HTP)
calculation
methods
developed
with
purpose
to
quickly
screen
potential
from
databases.
Some
HTP
experiment
also
which
can
increase
density
information
obtained
single
less
time
lower
cost.
In
addition,
machine
learning
(ML)
introduced
thermoelectrics.
this
review,
strategies
discovery
systematically
summarized.
applications
descriptor,
calculation,
experiment,
ML
reviewed.
challenges
possible
directions
future
research
discussed.
Bulletin of the Korean Chemical Society,
Journal Year:
2024,
Volume and Issue:
45(3), P. 186 - 199
Published: Jan. 29, 2024
Abstract
Thermoelectric
materials
can
generate
electric
power
from
dissipating
heat
without
releasing
any
undesirable
chemicals.
They
thus
increase
global
energy
efficiency
and
reduce
the
use
of
fossil
fuels
that
are
a
major
resource
for
generating
energy,
thereby
concurrently
addressing
environmental
crises
seriously
threatening
humanity.
Increasing
thermoelectric
figure
merit,
ZT,
has
been
prime
goal
in
thermoelectrics
because
an
generation
low
until
very
recently.
The
recent
development
ultrahigh
performance
polycrystalline
SnSe‐based
is
one
most
prominent
breakthroughs
history
thermoelectrics.
show
exceptionally
high
ZT
~3.1
at
783
K
average
~2.0
400
to
K,
which
highest
bulk
systems.
Here
we
review
advances
SnSe
thermoelectrics,
greatly
changing
paradigm
studies
applications
technology.
Crystals,
Journal Year:
2024,
Volume and Issue:
14(5), P. 432 - 432
Published: April 30, 2024
Thermoelectric
(TE)
materials
play
a
crucial
role
in
converting
energy
between
heat
and
electricity,
essentially
for
environmentally
friendly
renewable
conversion
technologies
aimed
at
addressing
the
global
crisis.
Significant
advances
TE
performance
have
been
achieved
over
past
decades
various
through
key
approaches,
such
as
nanostructuring,
band
engineering,
high-entropy
engineering.
Among
them,
design
of
has
recently
emerged
forefront
strategy
to
achieve
significantly
low
thermal
conductivity,
attributed
severe
lattice
distortion
microstructure
effects,
thereby
enhancing
materials’
figure
merit
(zT).
This
review
reveals
progress
developed
decade.
It
discusses
high-entropy-driven
structural
stabilization
maintain
favorable
electrical
transport
properties,
achieving
impact
high
entropy
on
mechanical
properties.
Furthermore,
explores
theoretical
development
material
potential
strategies
future
advancements
this
field
interactions
among
experimental
studies.
Acta Materialia,
Journal Year:
2024,
Volume and Issue:
281, P. 120342 - 120342
Published: Aug. 29, 2024
The
thermal
process
parameters
are
crucial
in
metal-sulfides
ceramics
as
they
affect
significantly
the
resulting
physico-chemical
properties.In
present
work,
we
investigated
sintering
effect
kesterite
Cu
2.125
Zn
0.875
SnS
4
on
its
structural,
microstructural,
and
thermoelectric
(TE)
properties
to
highlight
nonnegligible
contribution
of
often
ignored
metal-sulfide
ceramics.For
this
purpose,
developed
an
approach
combining
data
science
with
conventional
material
experiment/theory
which
can
be
used
a
tool
shortcut
time-consuming
steps
TE
optimization.We
confirmed
that
optimization
control
densification
is
critical
unravelling
highest
potential
metal
sulfide
non-negligible
increase
zT
up
60
%.We
propose
scientific
tool,
synergic
combination
active
machine
learning
chemistry/theory
approaches,
either
identify
most
proficient
well
avoid
degradation
ceramic
thus
shorten
number
experiments.This
extended
not
only
other
metalsulfide
for
thermoelectricity
but
also
research
fields.
