Bioelectronic Medicine,
Год журнала:
2023,
Номер
9(1)
Опубликована: Авг. 2, 2023
The
fourth
industrial
revolution
has
led
to
the
development
and
application
of
health
monitoring
sensors
that
are
characterized
by
digitalization
intelligence.
These
have
extensive
applications
in
medical
care,
personal
management,
elderly
sports,
other
fields,
providing
people
with
more
convenient
real-time
services.
However,
these
face
limitations
such
as
noise
drift,
difficulty
extracting
useful
information
from
large
amounts
data,
lack
feedback
or
control
signals.
artificial
intelligence
provided
powerful
tools
algorithms
for
data
processing
analysis,
enabling
intelligent
monitoring,
achieving
high-precision
predictions
decisions.
By
integrating
Internet
Things,
intelligence,
sensors,
it
becomes
possible
realize
a
closed-loop
system
functions
collection,
online
diagnosis,
treatment
recommendations.
This
review
focuses
on
healthcare
enhanced
technologies
aspects
materials,
device
structure,
integration,
scenarios.
Specifically,
this
first
introduces
great
advances
wearable
respiration
rate,
heart
pulse,
sweat,
tears;
implantable
cardiovascular
nerve
signal
acquisition,
neurotransmitter
monitoring;
soft
electronics
precise
therapy.
Then,
recent
volatile
organic
compound
detection
highlighted.
Next,
current
developments
human-machine
interfaces,
AI-enhanced
multimode
self-sustainable
systems
reviewed.
Last,
perspective
future
directions
further
research
is
also
provided.
In
summary,
fusion
will
provide
intelligent,
convenient,
secure
services
next-generation
biomedical
applications.
Advanced Optical Materials,
Год журнала:
2023,
Номер
11(20)
Опубликована: Сен. 10, 2023
Abstract
In
recent
years,
with
the
further
ministration
of
semiconductor
device
in
integrated
circuits,
power
consumption
and
data
transmission
bandwidth
have
become
insurmountable
obstacles.
As
an
technology,
photonic
circuits
(PICs)
a
promising
potential
post‐Moore
era
more
advantages
processing,
communication,
diversified
sensing
applications
for
their
ultra‐high
process
speed
low
consumption.
Silicon
photonics
is
believed
to
be
encouraging
solution
realize
PICs
because
mature
CMOS
process.
The
past
decades
witnessed
huge
growth
silicon
PICs.
However,
there
still
demand
development
enable
powerful
chip‐scale
systems
new
functionalities.
this
paper,
review
components,
functional
blocks,
emerging
offered.
common
components
are
classified
into
several
sections,
including
on‐chip
light
sources,
fiber‐to‐chip
couplers,
resonators,
waveguide‐based
sensors,
photodetectors,
modulators.
blocks
mentioned
memories
neural
networks.
Finally,
paper
concludes
study.
Machine‐learning‐enhanced
nanosensors
are
rapidly
emerging
as
a
promising
solution
in
the
field
of
sensor
technology,
traditional
sensors
encounter
limitations
data
analysis
their
development.
Since
inception
machine‐learning
algorithms
being
applied
to
enhance
nanosensors,
they
have
gained
significant
attention
due
adaptive
and
predictive
capabilities,
which
promise
dramatically
improve
efficiency
collection
processing
applications.
Herein,
comprehensive
overview
technological
innovation
is
provided
by
reviewing
latest
developments
cloud
computing,
edge
burgeoning
realm
neuromorphic
computing.
Cloud
computing
has
emerged
powerhouse,
harnessing
formidable
computational
capabilities
process
vast
volumes
high‐dimensional
data.
Then,
research
directions
for
various
applications
these
artificial
intelligence
(AI)‐enhanced
outlined.
Moreover,
integration
AI
nanosensor
technology
into
chip‐level
although
promising,
still
faces
challenges
such
energy‐efficient
hardware
development,
algorithm
optimization,
scalability
mass
production.
Finally,
forward‐looking
perspective
on
future
machine‐learning‐enhanced
provided,
delineating
opportunities
further
this
exciting
field.
Abstract
On‐chip
nanophotonic
waveguide
sensor
is
a
promising
solution
for
miniaturization
and
label‐free
detection
of
gas
mixtures
utilizing
the
absorption
fingerprints
in
mid‐infrared
(MIR)
region.
However,
quantitative
analysis
organic
still
challenging
less
reported
due
to
overlapping
spectrum.
Here,an
Artificial‐Intelligence
(AI)
assisted
“Photonic
nose”
presented
as
an
augmented
sensing
platform
mixture
MIR.
With
subwavelength
grating
cladding
supported
design
help
machine
learning
algorithms,
MIR
spectrum
binary
distinguished
from
arbitrary
mixing
ratio
decomposed
single‐component
spectra
concentration
prediction.
As
result,
classification
93.57%
19
ratios
realized.
In
addition,
decomposition
prediction
show
average
root‐mean‐square
error
2.44
vol%.
The
work
proves
potential
broader
analytical
capabilities
multiple
components
toward
on‐chip
spectroscopy.
ACS Applied Materials & Interfaces,
Год журнала:
2024,
Номер
16(14), С. 17965 - 17972
Опубликована: Март 27, 2024
Metastructures,
artificial
arrangements
of
micro/macrostructures,
possess
unique
properties
and
are
significant
interest
in
aerospace,
stealth
technology,
various
other
applications.
Recent
studies
have
focused
on
quasi-zero
stiffness
metastructures,
providing
an
outstanding
vibration
isolation
capability.
However,
existing
methods
constrained
to
low
preloads
lack
the
consideration
structural
analysis,
despite
their
intended
use
practical
structures.
This
study
introduces
metastructures
with
characteristics
under
high
by
inducing
local
buckling.
An
optimization
framework
combining
deep
reinforcement
learning
finite-element
analysis
is
employed
derive
optimal
model
that
considers
both
safety
characteristics.
To
validate
results,
fabricated
via
3D
printing,
compression
experiments
conducted.
The
exhibit
a
target
preload
along
reduction
performance,
even
low-frequency
range.
Surface
plasmons
have
proven
their
ability
to
boost
the
sensitivity
of
mid-infrared
hyperspectral
imaging
by
enhancing
light-matter
interactions.
phonons,
a
counterpart
technology
plasmons,
present
unclear
contributions
imaging.
Here,
we
investigate
this
developing
plasmon-phonon
system
that
uses
asymmetric
cross-shaped
nanoantennas
composed
stacked
materials.
The
phonon
modes
within
system,
controlled
light
polarization,
capture
molecular
refractive
index
intensity
and
lineshape
features,
distinct
from
those
observed
with
enabling
more
precise
sensitive
molecule
identification.
In
deep
learning-assisted
demonstration
severe
acute
respiratory
syndrome
coronavirus
(SARS-CoV),
phonons
exhibit
enhanced
identification
capabilities
(230,400
spectra/s),
facilitating
de-overlapping
observation
spatial
distribution
two
mixed
SARS-CoV
spike
proteins.
addition,
demonstrates
increased
accuracy
(93%),
heightened
sensitivity,
detection
limits
(down
monolayers).
These
findings
extend
polaritonics
imaging,
promising
applications
in
imaging-guided
screening
pharmaceutical
analysis.
Volatile
organic
compounds
(VOCs)
are
a
class
of
with
high
vapor
pressure
and
low
boiling
points,
widely
present
in
both
natural
environments
human
activities.
VOCs
released
from
various
sources
not
only
contribute
to
environmental
pollution
but
also
pose
threats
ecosystems
health.
Moreover,
some
considered
biomarkers
exhaled
breath
can
be
utilized
identify
diseases.
Therefore,
monitoring
controlling
VOC
emissions
concentrations
crucial
for
safeguarding
the
environment
In
recent
years,
significant
advancements
have
been
achieved
micro‐electromechanical
system
(MEMS)‐based
sensing
optical
technologies,
offering
new
avenues
detection.
This
article
provides
comprehensive
overview
research
progress
MEMS
sensors,
focusing
on
their
mechanisms
classifications.
It
then
discusses
role
artificial
intelligence
enhancing
identification
quantification,
as
well
trends
toward
sensor
miniaturization
intelligence.
Furthermore,
highlights
diverse
applications
sensors
medical
diagnostics,
agricultural
food
testing,
Internet
Things.
Finally,
it
emphasizes
opportunities
challenges
associated
providing
valuable
insights
practical
applications.
Advanced Optical Materials,
Год журнала:
2023,
Номер
11(9)
Опубликована: Фев. 26, 2023
Abstract
Graphene
has
attracted
great
interest
for
integrated
photonic
platforms
in
the
long‐wave
infrared
(LWIR)
spectroscopic
and
polarimetric
sensing
due
to
capability
of
on‐chip
integration,
fast
response,
broadband
operation.
However,
graphene
suffers
from
low
photoresponsivity
thus
poor
performance
weak
absorption.
Polarization
detection
using
is
hindered
by
its
small
in‐plane
anisotropy.
Here,
nanoantenna‐mediated
photodetectors
(NMGPDs)
are
proposed
enhance
responsivity
tailoring
nanoantenna
near‐field
distribution
generate
a
strong
photoresponse.
The
devices
demonstrate
high
6.3
V
W
−1
under
zero
bias
at
room
temperature
with
noise‐equivalent
power
1.6
nW
Hz
−1/2
.
Furthermore,
polarization
enabled
artificial
anisotropy
double
L‐shaped
nanoantennas.
LWIR
NMGPDs
achieve
subtle
polarization‐angle
down
0.05°
thanks
unusual
negative
ratio
−1.
To
advances
molecule
detection,
acetone
chosen
as
an
analyte
sensing.
show
limit
115
ppm,
dynamic
gas
response
6
s
real‐time
monitoring.
These
results
reveal
potential
device
multi‐functional
miniaturized
optoelectronic
platform
toward
environmental
monitoring
biomedical
screening.
