Analytical Chemistry,
Год журнала:
2024,
Номер
unknown
Опубликована: Июль 15, 2024
Deep
learning
(DL)
is
becoming
more
popular
as
a
useful
tool
in
various
scientific
domains,
especially
chemistry
applications.
In
the
infrared
spectroscopy
field,
where
identifying
functional
groups
unknown
compounds
poses
significant
challenge,
there
growing
need
for
innovative
approaches
to
streamline
and
enhance
analysis
processes.
This
study
introduces
transformative
approach
leveraging
DL
methodology
based
on
transformer
attention
models.
With
data
set
containing
approximately
8677
spectra,
our
model
utilizes
self-attention
mechanisms
capture
complex
spectral
features
precisely
predict
17
groups,
outperforming
conventional
architectures
both
group
prediction
accuracy
compound-level
precision.
The
success
of
underscores
potential
transformer-based
methodologies
enhancing
techniques.
Advanced Energy Materials,
Год журнала:
2024,
Номер
14(34)
Опубликована: Июнь 26, 2024
Abstract
The
unsustainable
nature
of
energy‐intensive
and
environmentally
unfriendly
traditional
air
conditioning
systems,
compacted
with
recent
climate
change
effects,
show
an
urgent
need
for
more
sustainable
efficient
thermoregulation
solutions.
Innovations
in
passive
daytime
radiative
coolers
(PDRCs)
selective
solar
absorbers
(SSAs),
which
utilize
natural
resources,
the
“cold”
outer
space
“hot”
sun
from
sky,
offer
friendly
cost‐effective
alternative.
However,
various
factors
significantly
impede
commercial
viability
these
technologies,
such
as
lack
emphasis
on
advancements
practical
application,
challenge
reversible
functionality
between
PDRCs
SSAs,
inconsistent
performance
evaluation,
absence
effective
mass
production
strategies.
Here
current
challenges
future
development
trends
PDRC
SSA‐aided
innovation
are
discussed.
Specifically,
opportunities
relating
to
application
conditions,
evaluation
parameter
standardization,
strategies
considered
large‐scale
production,
all
critical
realizing
full
potential
SSAs.
Radiative
cooling
and
evaporative
are
sustainable
techniques
without
additional
energy
input.
However,
radiative
lacks
dynamic
ability,
while
demands
external
water
replenishment,
hindering
their
applications.
Herein,
a
smart
radiative/evaporative
bilayer
combining
polydimethylsiloxane
(PDMS)
upper
layer
with
hydrogel
lower
is
presented
for
efficient
all‐day
passive
cooling.
The
PDMS
high
solar
reflectivity
(0.930)
emissivity
(0.952)
provides
excellent
protects
the
from
exposure,
demonstrates
remarkable
evaporation
absorption,
achieving
Thus,
synergy
of
two
layers
significantly
enhances
overall
performance.
Specifically,
can
achieve
peak
power
values
424.4
650.6
W
m
−2
as
well
maximum
subambient
temperatures
10.4
3.7
°C
during
sunny
cloudy
mid‐days,
respectively.
Moreover,
obtains
3.2
warmer
temperature
compared
alone
cold
nighttime,
structures
exhibit
comparable
performance
hot
indicating
self‐adaptive
property
bilayer.
In
addition,
good
even
under
continuous
days,
offering
promising
strategy
Next Energy,
Год журнала:
2024,
Номер
4, С. 100146 - 100146
Опубликована: Июнь 1, 2024
Passive
thermoelectric
devices
that
utilize
radiative
cooling
and
solar
heating
have
witnessed
significant
advancements
in
power
generation.
However,
their
applications
promotions
are
limited
due
to
the
low
unsustainable
output.
In
this
study,
we
propose
a
compact
passive
device
(TED)
consisting
of
generator
(TEG)
equipped
with
cooler
(RCer)
absorber
(SAer)
for
24-h
electricity
The
RCer
is
made
high-scattering
porous
cellulose
film
thickness
100
μm.
It
coated
onto
TEG's
sky-facing
terminal
which
serves
as
cold
end.
SAer
an
aluminum
substrate
black
paint.
attached
opposite
TEG
hot
By
compactly
integrating
SAer,
proposed
TED
can
harvest
energy
from
space
continuous
electric
generation
manageable
implementations.
Outdoor
experiments
shown
during
clear
daytime,
maximum
temperature
difference
between
ends
reached
7.7
°C,
average
2.8
°C.
During
nighttime,
could
reach
1.7
0.9
outputs
daytime
nighttime
351.6
mW·m−2
31.0
mW·m−2,
respectively.
This
study
introduces
conceptual
design
lays
foundation
practical
powering
outdoor
microdevices.
Atmosphere,
Год журнала:
2025,
Номер
16(1), С. 95 - 95
Опубликована: Янв. 16, 2025
Passive
daytime
radiative
cooling
(PDRC)
has
emerged
as
a
promising,
electricity-free
approach
that
reflects
sunlight
while
radiating
heat
through
the
atmospheric
transparent
window.
However,
design
and
optimization
of
PDRC
materials
remain
challenging,
requiring
significant
time
resources
for
experimental
numerical
modeling
efforts.
In
this
work,
we
developed
machine
learning
(ML)-driven
to
predict
scattering
efficiency
in
wavelength
0.3–2.5
μm,
with
aim
eventually
optimizing
microstructural
materials.
By
employing
ML
models
such
linear
regression,
neural
networks,
random
forests,
aimed
optimize
across
different
pore
sizes
mixed-pore-size
configurations.
As
result,
forest
model
demonstrated
superior
prediction
performance
minimal
error,
effectively
capturing
complex,
non-linear
interactions
between
material
features.
We
also
leveraged
data
transformation
techniques
one-hot
encoding
generative
predictions
The
presented
ML-driven
platform
serves
valuable
open
resource
researchers,
facilitating
rapid
cost-effective
accelerating
development
sustainable
technologies.
Nano-Micro Letters,
Год журнала:
2025,
Номер
17(1)
Опубликована: Март 19, 2025
Abstract
Radiative
cooling
fabric
creates
a
thermally
comfortable
environment
without
energy
input,
providing
sustainable
approach
to
personal
thermal
management.
However,
most
currently
reported
fabrics
mainly
focus
on
outdoor
cooling,
ignoring
achieve
simultaneous
both
indoors
and
outdoors,
thereby
weakening
the
overall
performance.
Herein,
full-scale
structure
with
selective
emission
properties
is
constructed
for
indoor
cooling.
The
achieves
94%
reflectance
performance
in
sunlight
band
(0.3–2.5
µm)
6%
mid-infrared
(2.5–25
µm),
effectively
minimizing
heat
absorption
radiation
release
obstruction.
It
also
demonstrates
81%
radiative
atmospheric
window
(8–13
25%
transmission
μm),
60
26
W
m
−2
net
power
outdoors
indoors.
In
practical
applications,
excellent
human
temperatures
1.4–5.5
°C
lower
than
typical
polydimethylsiloxane
film.
This
work
proposes
novel
design
advanced
fabric,
offering
significant
potential
realize
