Photonics,
Journal Year:
2024,
Volume and Issue:
11(5), P. 442 - 442
Published: May 9, 2024
The
interplay
between
two
paradigms,
artificial
intelligence
(AI)
and
optical
metasurfaces,
nowadays
appears
obvious
unavoidable.
AI
is
permeating
literally
all
facets
of
human
activity,
from
science
arts
to
everyday
life.
On
the
other
hand,
metasurfaces
offer
diverse
sophisticated
multifunctionalities,
many
which
appeared
impossible
only
a
short
time
ago.
use
for
optimization
general
approach
that
has
become
ubiquitous.
However,
here
we
are
witnessing
two-way
process—AI
improving
but
some
also
AI.
helps
design,
analyze
utilize
while
ensure
creation
all-optical
chips.
This
ensures
positive
feedback
where
each
enhances
one:
this
may
well
be
revolution
in
making.
A
vast
number
publications
already
cover
either
first
or
second
direction;
modest
includes
both.
an
attempt
make
reader-friendly
critical
overview
emerging
synergy.
It
succinctly
reviews
research
trends,
stressing
most
recent
findings.
Then,
it
considers
possible
future
developments
challenges.
author
hopes
broad
interdisciplinary
will
useful
both
dedicated
experts
scholarly
audience.
Chemical Reviews,
Journal Year:
2024,
Volume and Issue:
124(7), P. 4258 - 4331
Published: March 28, 2024
Artificial
Intelligence
(AI)
has
advanced
material
research
that
were
previously
intractable,
for
example,
the
machine
learning
(ML)
been
able
to
predict
some
unprecedented
thermal
properties.
In
this
review,
we
first
elucidate
methodologies
underpinning
discriminative
and
generative
models,
as
well
paradigm
of
optimization
approaches.
Then,
present
a
series
case
studies
showcasing
application
in
metamaterial
design.
Finally,
give
brief
discussion
on
challenges
opportunities
fast
developing
field.
particular,
review
provides:
(1)
Optimization
metamaterials
using
algorithms
achieve
specific
target
(2)
Integration
models
with
enhance
computational
efficiency.
(3)
Generative
structural
design
metamaterials.
Materials & Design,
Journal Year:
2024,
Volume and Issue:
238, P. 112659 - 112659
Published: Jan. 14, 2024
Traditional
materials
or
advanced
artificially
engineered
metamaterials
are
incapable
of
effectively
addressing
the
simultaneous
challenges
impact
energy
hazards
and
low-frequency
noise.
There
is
an
urgent
need
for
multifunctional
that
can
address
this
multi-physics
field
coupling
problem.
Herein,
a
hierarchical
chiral
metamaterial
(HMCM)
proposed
damage-resistance
broadband
sound-absorption
capabilities
fabricated
by
means
laser
powder
bed
fusion
technology.
Cavity
resonators
with
internally
extended
tubes
configuration
were
selected
as
primary
units.
The
performance
HMCM
was
investigated
systematically
through
experimental,
numerical,
theoretical
methods.
Crashworthiness
design
optimization
on
implemented
to
explore
effect
geometrical
parameters
including
distance
ratio
wall
thickness
distribution
crushing
resistance.
It
determined
specific
configurations
in
these
significantly
enhance
mechanism
dissipating
HMCM.
Furthermore,
designed
has
been
experimentally,
numerically,
theoretically
proven
possess
quasi-perfect
sound
absorption
target
range
425
Hz
553
average
coefficient
exceeding
0.9.
Overall,
work
not
only
offers
promising
solution
designing
but
also
highlights
potential
additive
manufacturing
techniques
development
such
sophisticated
materials.
Thin-Walled Structures,
Journal Year:
2024,
Volume and Issue:
197, P. 111663 - 111663
Published: Feb. 1, 2024
This
paper
investigates
the
free
and
forced
vibration
behaviours
of
functionally
graded
graphene
origami-enabled
auxetic
metamaterial
(FG-GOEAM)
beams
submerged
in
Newtonian
fluids,
with
a
particular
focus
on
understanding
influence
negative
Poisson's
ratio
(NPR)
natural
frequencies
dynamic
responses
beam.
To
this
end,
novel
accurate
efficient
machine
learning-assisted
model
based
genetic
programming
(GP)
algorithm
theoretical
formulations
is
proposed.
The
deformation
beam
governed
by
first-order
shear
theory,
numerical
solutions
are
obtained
using
differential
quadrature
method
(DQM)
together
Newmark-β
method.
fluid-structure
interaction
(FSI)
described
simplified
Navier-Stokes
equation
for
fluid
momentum.
results
from
showcase
its
high
accuracy
efficiency
predicting
FG-GOEAM
beams.
Extensive
parametric
studies
reveal
that
incorporation
origami
(GOri)
reinforcement
superior
NPR
characteristics
compared
to
their
metallic
counterparts,
leading
significantly
increased
fundamental
improved
resistance
deflections.
study
demonstrates
effectiveness
learning
analysing
optimising
composite
structures.
Materials Horizons,
Journal Year:
2024,
Volume and Issue:
11(11), P. 2615 - 2627
Published: Jan. 1, 2024
We
introduce
a
novel
deep
learning-based
inverse
design
framework
with
data
augmentation
for
chiral
mechanical
metamaterials
Bézier
curve-shaped
bi-material
rib
realizing
wide
range
of
negative
thermal
expansion
and
Poisson's
ratio.
Nature Communications,
Journal Year:
2024,
Volume and Issue:
15(1)
Published: July 15, 2024
Fourier's
law
dictates
that
heat
flows
from
warm
to
cold.
Nevertheless,
devices
can
be
tailored
cloak
obstacles
or
even
reverse
the
flow.
Mathematical
transformation
yields
closed-form
equations
for
graded,
highly
anisotropic
thermal
metamaterial
distributions
needed
obtaining
such
functionalities.
For
simple
geometries,
realized
by
regular
conductor
distributions;
however,
complex
physical
realizations
have
so
far
been
challenging,
and
sub-optimal
solutions
obtained
expensive
numerical
approaches.
Here
we
suggest
a
straightforward
efficient
analytical
de-homogenization
approach
uses
optimal
multi-rank
laminates
provide
any
imaginable
manipulation
device.
We
create
cloaks,
rotators,
concentrators
in
domains
with
close-to-optimal
performance
esthetic
elegance.
The
are
fabricated
using
metal
3D
printing,
their
omnidirectional
functionalities
investigated
numerically
validated
experimentally.
enables
next-generation
free-form
meta-devices
synthesis,
near-optimal
performance,
concise
patterns.
