Copper Nanoclusters Anchored on Crumpled N-Doped MXene for Ultra-Sensitive Electrochemical Sensing
Sensors,
Год журнала:
2025,
Номер
25(8), С. 2508 - 2508
Опубликована: Апрель 16, 2025
Simultaneous
detection
of
dopamine
(DA)
and
uric
acid
(UA)
is
essential
for
diagnosing
neurological
metabolic
diseases
but
hindered
by
overlapping
electrochemical
signals.
We
present
an
ultrasensitive
sensor
using
copper
nanoclusters
anchored
on
nitrogen-doped
crumpled
Ti3C2Tx
MXene
(Cu-N/Ti3C2Tx).
The
engineered
3D
architecture
prevents
restacking,
exposes
active
sites,
enhances
ion
transport,
while
Cu
boost
electrocatalytic
activity
via
accelerated
electron
transfer.
Structural
analyses
confirm
uniform
dispersion
(3.0
wt%),
Ti-N
bonding,
strain-induced
wrinkles,
synergistically
improving
conductivity.
achieves
exceptional
sensitivity
(1958.3
1152.7
μA·mM−1·cm−2
DA/UA),
ultralow
limits
(0.058
0.099
μM
rapid
response
(<1.5
s),
interference
resistance
(e.g.,
ascorbic
acid).
Differential
pulse
voltammetry
enables
independent
linear
ranges
(DA:
2–60
μM;
UA:
5–100
μM)
in
biofluids,
with
94.4%
stability
retention
over
7
days.
designed
exhibits
excellent
capabilities
DA
UA
detection.
This
work
provides
a
novel
design
strategy
developing
high-performance
sensors.
Язык: Английский
Spatiotemporal E-Nose with Laser Tailoring and Chromatography Inspiration
ACS Sensors,
Год журнала:
2025,
Номер
unknown
Опубликована: Апрель 29, 2025
The
study
introduces
a
spatiotemporal
chromatography-mimicking
(SCM)
e-nose
that
integrates
laser-tailored
graphene
paper
with
microchamber
for
precise
volatile
organic
compound
(VOC)
discrimination.
SCM
overcomes
traditional
array
limitations
single
multifunctional
component
capable
of
accurate
VOC
differentiation
via
chromatography-mimic
features.
Advanced
laser-engraving
techniques
fabricate
gas-permeable
interdigitated
electrode
from
as
the
sieving
framework.
Key
achievements
include
its
component,
economical
and
scalable
design,
distinct
response
patterns
different
VOCs,
remarkable
ability
to
discriminate
mixed
versatility
diverse
applications
including
real-time
on-site
analysis,
ease
integration
electronic
systems.
represents
significant
advancement
in
nose
technology,
offering
compact,
cost-effective
solution
detection
analysis.
Язык: Английский
Robust Odor Detection in Electronic Nose Using Transfer-Learning Powered Scentformer Model
ACS Sensors,
Год журнала:
2025,
Номер
unknown
Опубликована: Май 15, 2025
Mimicking
the
olfactory
system
of
humans,
use
electronic
noses
(E-noses)
for
detection
odors
in
nature
has
become
a
hot
research
topic.
This
study
presents
novel
E-nose
based
on
deep
learning
architecture
called
Scentformer,
which
addresses
limitations
current
like
narrow
range
and
limited
generalizability
across
different
scenarios.
Armed
with
self-adaptive
data
down-sampling
method,
is
capable
detecting
55
natural
classification
accuracy
99.94%,
model
embedded
analyzed
using
Shapley
Additive
exPlanations
analysis,
providing
quantitative
interpretation
performance.
Furthermore,
leveraging
Scentformer's
transfer
ability,
efficiently
adapts
to
new
gases.
Rather
than
retraining
all
layers
odor
set,
only
fully
connected
need
be
trained
pretrained
model.
Using
1‰
retrained
model,
model-based
can
also
achieve
accuracies
99.14%
various
gas
concentrations.
provides
robust
approach
diverse
direct
signals
real-world
applications.
Язык: Английский
Smart portable electronic nose system in combination with machine learning algorithms for the intelligence discrimination of fire debris
Chemometrics and Intelligent Laboratory Systems,
Год журнала:
2025,
Номер
unknown, С. 105459 - 105459
Опубликована: Июнь 1, 2025
Язык: Английский