Nature Communications,
Journal Year:
2024,
Volume and Issue:
15(1)
Published: June 1, 2024
Abstract
Designing
ultralight
conductive
aerogels
with
tailored
electrical
and
mechanical
properties
is
critical
for
various
applications.
Conventional
approaches
rely
on
iterative,
time-consuming
experiments
across
a
vast
parameter
space.
Herein,
an
integrated
workflow
developed
to
combine
collaborative
robotics
machine
learning
accelerate
the
design
of
programmable
properties.
An
automated
pipetting
robot
operated
prepare
264
mixtures
Ti
3
C
2
T
x
MXene,
cellulose,
gelatin,
glutaraldehyde
at
different
ratios/loadings.
After
freeze-drying,
aerogels’
structural
integrity
evaluated
train
support
vector
classifier.
Through
8
active
cycles
data
augmentation,
162
unique
are
fabricated/characterized
via
robotics-automated
platforms,
enabling
construction
artificial
neural
network
prediction
model.
The
model
conducts
two-way
tasks:
(1)
predicting
physicochemical
from
fabrication
parameters
(2)
automating
inverse
specific
property
requirements.
combined
use
interpretation
finite
element
simulations
validates
pronounced
correlation
between
aerogel
density
compressive
strength.
model-suggested
high
conductivity,
customized
strength,
pressure
insensitivity
allow
compression-stable
Joule
heating
wearable
thermal
management.
Polymer Composites,
Journal Year:
2023,
Volume and Issue:
45(1), P. 43 - 76
Published: Sept. 22, 2023
Abstract
The
proliferation
of
electronic
devices
and
wireless
communication
in
our
daily
lives
has
led
to
a
significant
increase
electromagnetic
pollution.
This
issue
poses
serious
threat
the
proper
functioning
equipment
as
well
human
health.
Therefore,
investigation
materials
with
superior
interference
(EMI)
shielding
capabilities
garnered
growing
interest.
In
this
paper,
mechanisms
EMI
were
first
introduced
briefly.
It
was
noted
that
development
advanced
involved
adhering
principles
such
minimizing
reflection
loss,
enhancing
absorption
incorporating
multiple
internal
reflections.
construction
properties
traditional
introduced.
Unlike
metal
high
densities
lightweight
conductive
polymer
composites
(CPCs)
have
been
most
promising
materials.
Meanwhile,
carbon‐based
nanofillers
carbon
nanotubes
graphene
nanosheets,
along
two‐dimensional
transition
carbonitrides
MXenes
Ti
3
C
2
T
x
,
emerged
versatile
for
CPCs.
performance
loss
mechanism
CPCs
homogeneous
structure,
segregated
laminated
porous
structure
detail.
could
be
significantly
improved
by
structures
into
same
CPCs,
rational
combination
structures.
Finally,
challenges
trends
applications
discussed.
Highlights
Mechanisms
from
aspect
energy
dissipation.
Structure–property
described.
different
summarized.
Future
Absorption‐dominated
design
emphasized.
Nature Communications,
Journal Year:
2024,
Volume and Issue:
15(1)
Published: June 1, 2024
Abstract
Designing
ultralight
conductive
aerogels
with
tailored
electrical
and
mechanical
properties
is
critical
for
various
applications.
Conventional
approaches
rely
on
iterative,
time-consuming
experiments
across
a
vast
parameter
space.
Herein,
an
integrated
workflow
developed
to
combine
collaborative
robotics
machine
learning
accelerate
the
design
of
programmable
properties.
An
automated
pipetting
robot
operated
prepare
264
mixtures
Ti
3
C
2
T
x
MXene,
cellulose,
gelatin,
glutaraldehyde
at
different
ratios/loadings.
After
freeze-drying,
aerogels’
structural
integrity
evaluated
train
support
vector
classifier.
Through
8
active
cycles
data
augmentation,
162
unique
are
fabricated/characterized
via
robotics-automated
platforms,
enabling
construction
artificial
neural
network
prediction
model.
The
model
conducts
two-way
tasks:
(1)
predicting
physicochemical
from
fabrication
parameters
(2)
automating
inverse
specific
property
requirements.
combined
use
interpretation
finite
element
simulations
validates
pronounced
correlation
between
aerogel
density
compressive
strength.
model-suggested
high
conductivity,
customized
strength,
pressure
insensitivity
allow
compression-stable
Joule
heating
wearable
thermal
management.
