Chemosensors,
Год журнала:
2024,
Номер
12(9), С. 179 - 179
Опубликована: Сен. 4, 2024
Benzene,
as
a
typical
toxic
gas
and
carcinogen,
is
an
important
detection
object
in
the
field
of
environmental
monitoring.
However,
it
remains
challenging
for
conventional
resistance-type
sensor
to
effectively
detect
low-concentration
(ppb-level)
benzene
molecules,
owing
their
insufficient
reaction
activation
energy,
especially
when
operating
at
room
temperature.
Herein,
field-effect
transistor
(FET)-type
using
carbon
nanotubes
channel
material
proposed
efficient
trace
benzene,
where
(CNTs)
with
high
semiconductor
purity
act
main
material,
ZnO/WS2
nanocomposites
serve
gate
sensitive
material.
On
basis
remarkable
amplification
effect
CNTs-based
FET,
manifests
desirable
ability
limit
low
500
ppb
even
working
temperature,
also
exhibits
fast
response
speed
(90
s),
consistency
deviation
less
than
5%,
long-term
stability
up
30
days.
Furthermore,
utilizing
Tenax
TA
screening
unit,
as-proposed
can
achieve
feasible
selective
benzene.
These
experimental
results
demonstrate
that
strategy
here
provide
significant
guidance
development
high-performance
sensors
Biosensors,
Год журнала:
2024,
Номер
14(7), С. 356 - 356
Опубликована: Июль 22, 2024
The
steady
progress
in
consumer
electronics,
together
with
improvement
microflow
techniques,
nanotechnology,
and
data
processing,
has
led
to
implementation
of
cost-effective,
user-friendly
portable
devices,
which
play
the
role
not
only
gadgets
but
also
diagnostic
tools.
Moreover,
numerous
smart
devices
monitor
patients'
health,
some
them
are
applied
point-of-care
(PoC)
tests
as
a
reliable
source
evaluation
patient's
condition.
Current
practices
still
based
on
laboratory
tests,
preceded
by
collection
biological
samples,
then
tested
clinical
conditions
trained
personnel
specialistic
equipment.
In
practice,
collecting
passive/active
physiological
behavioral
from
patients
real
time
feeding
artificial
intelligence
(AI)
models
can
significantly
improve
decision
process
regarding
diagnosis
treatment
procedures
via
omission
conventional
sampling
while
excluding
pathologists.
A
combination
novel
methods
digital
traditional
biomarker
detection
portable,
autonomous,
miniaturized
revolutionize
medical
diagnostics
coming
years.
This
article
focuses
comparison
modern
techniques
AI
machine
learning
(ML).
presented
technologies
will
bypass
laboratories
start
being
commercialized,
should
lead
or
substitution
current
Their
application
PoC
settings
technology
accessible
every
patient
appears
be
possibility.
Research
this
field
is
expected
intensify
Technological
advancements
sensors
biosensors
anticipated
enable
continuous
real-time
analysis
various
omics
fields,
fostering
early
disease
intervention
strategies.
integration
health
platforms
would
predictive
personalized
healthcare,
emphasizing
importance
interdisciplinary
collaboration
related
scientific
fields.
Breath
sensors
represent
a
frontier
in
noninvasive
diagnostics,
leveraging
the
detection
of
volatile
organic
compounds
(VOCs)
exhaled
breath
for
real-time
health
monitoring.
This
review
highlights
recent
advancements
breath-sensing
technologies,
with
focus
on
innovative
materials
driving
their
enhanced
sensitivity
and
selectivity.
Polymers,
carbon-based
like
graphene
carbon
nanotubes,
metal
oxides
such
as
ZnO
SnO2
have
demonstrated
significant
potential
detecting
biomarkers
related
to
diseases
including
diabetes,
liver/kidney
dysfunction,
asthma,
gut
health.
The
structural
operational
principles
these
are
examined,
revealing
how
unique
properties
contribute
key
respiratory
gases
acetone,
ammonia
(NH3),
hydrogen
sulfide,
nitric
oxide.
complexity
samples
is
addressed
through
integration
machine
learning
(ML)
algorithms,
convolutional
neural
networks
(CNNs)
support
vector
machines
(SVMs),
which
optimize
data
interpretation
diagnostic
accuracy.
In
addition
sensing
VOCs,
devices
capable
monitoring
parameters
airflow,
temperature,
humidity,
essential
comprehensive
analysis.
also
explores
expanding
role
artificial
intelligence
(AI)
transforming
wearable
into
sophisticated
tools
personalized
enabling
disease
Together,
advances
sensor
ML-based
analytics
present
promising
platform
future
individualized,
healthcare.
Advanced Electronic Materials,
Год журнала:
2025,
Номер
unknown
Опубликована: Март 30, 2025
Abstract
Stretchable
organic
field‐effect
transistors
(OFETs)
based
gas
sensors
have
attracted
significant
attention
due
to
their
inherent
merits
such
as
excellent
mechanical
compatibility,
flexibility,
and
signal
amplification
capabilities.
However,
achieving
low‐voltage
operation
remains
challenging,
which
limits
practical
application.
Herein,
a
tri‐layer
dielectric
design
is
developed
achieve
low‐voltage,
high‐mobility
stretchable
for
sensors.
The
dielectric,
consisting
of
high‐κ
polymer
film,
non‐polar
layer,
cross‐linking
allows
the
operate
at
−5
V.
transistor‐based
exhibit
high
sensitivity
detection
capability.
Thus,
on
dielectrics
offer
promising
strategy
advancing
wearable
Nano-Micro Letters,
Год журнала:
2025,
Номер
17(1)
Опубликована: Май 3, 2025
Abstract
Over
recent
decades,
carbon-based
chemical
sensor
technologies
have
advanced
significantly.
Nevertheless,
significant
opportunities
persist
for
enhancing
analyte
recognition
capabilities,
particularly
in
complex
environments.
Conventional
monovariable
sensors
exhibit
inherent
limitations,
such
as
susceptibility
to
interference
from
coexisting
analytes,
which
results
response
overlap.
Although
arrays,
through
modification
of
multiple
sensing
materials,
offer
a
potential
solution
recognition,
their
practical
applications
are
constrained
by
intricate
material
processes.
In
this
context,
multivariable
emerged
promising
alternative,
enabling
the
generation
outputs
construct
comprehensive
space
while
utilizing
single
material.
Among
various
carbon
nanotubes
(CNTs)
and
graphene
ideal
candidates
constructing
high-performance
sensors,
owing
well-established
batch
fabrication
processes,
superior
electrical
properties,
outstanding
capabilities.
This
review
examines
progress
focusing
on
CNTs/graphene
materials
field-effect
transistors
transducers
recognition.
The
discussion
encompasses
fundamental
aspects
these
including
architectures,
performance
metrics,
pattern
algorithms,
mechanism.
Furthermore,
highlights
innovative
extraction
schemes
when
integrated
with
algorithms.
