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.
Opto-Electronic Advances,
Journal Year:
2024,
Volume and Issue:
7(9), P. 240045 - 240045
Published: Jan. 1, 2024
Reprogrammable
metasurfaces,
which
establish
a
fascinating
bridge
between
physical
and
information
domains,
can
dynamically
control
electromagnetic
(EM)
waves
in
real
time
thus
have
attracted
great
attentions
from
researchers
around
the
world.
To
EM
with
an
arbitrary
polarization
state,
it
is
desirable
that
complete
set
of
basis
states
be
controlled
independently
since
incident
state
decomposed
as
linear
sum
these
states.
In
this
work,
we
present
concept
complete-basis-reprogrammable
coding
metasurface
(CBR-CM)
reflective
manners,
achieve
dynamic
controls
over
reflection
phases
while
maintaining
same
amplitude
for
left-handed
circularly
polarized
(LCP)
right-handed
(RCP)
waves.
Since
LCP
RCP
together
constitute
planar
waves,
dynamically-controlled
holograms
generated
under
arbitrarily
wave
incidence.
The
reconfigurable
meta-particle
implemented
to
demonstrate
CBR-CM's
robust
capability
controlling
longitudinal
transverse
positions
independently.
It's
expected
proposed
CBR-CM
opens
up
ways
realizing
more
sophisticated
advanced
devices
multiple
independent
channels,
may
provide
technical
assistance
digital
environment
reproduction.
Acoustic
metamaterials
are
artificial
structures
that
possess
distinctive
acoustic
characteristics,
allowing
for
modulation
effects
challenging
to
achieve
in
the
natural
world.
Nevertheless,
design
of
is
a
process
due
intricate
relationship
between
their
structural
parameters
and
nonlinear
performance.
In
view
limitations
conventional
methodologies,
which
rely
on
priori
knowledge
experts
often
hindered
by
prolonged
computation
times
necessity
iterative
trials
objectives,
this
paper
introduces
deep
learning-based
method
performance
prediction
inverse
Cylindrical
Plate-type
Metamaterials
(CPAMs).
The
creation
dataset
initiated
generating
large
number
samples
using
parametric
model,
with
bandgap
characteristics
calculated
through
finite
element
method.
A
forward-design
learning
model
then
developed,
predicting
upper
lower
limits
based
input
parameters.
Additionally,
an
constructed,
enabling
rapid
generation
desired
results
validated
simulation
experimentation,
confirming
accuracy
reliability
model.
This
study
demonstrates
potential
efficiently
designing
complex
metamaterials,
offering
promising
solution
CPAMs
development.
