Analytical Chemistry,
Год журнала:
2025,
Номер
unknown
Опубликована: Апрель 10, 2025
The
efficiency
of
sensor
arrays
in
parallel
discrimination
multianalytes
is
fundamentally
influenced
by
the
quantity
and
performance
elements.
advent
combinational
design
has
notably
accelerated
generation
chemical
libraries,
offering
numerous
candidates
for
development
robust
arrays.
However,
screening
elements
with
superior
cross-responsiveness
remains
challenging,
impeding
high-performance
Herein,
we
propose
a
new
deep
learning-assisted,
two-step
strategy
to
identify
optimal
combination
minimal
elements,
using
designed
volatile
organic
compounds
(VOCs)-targeted
library.
400
sensing
constructed
pairing
20
ionizable
cationic
anionic
dyes
library
were
employed
various
VOCs,
generating
plentiful
color
variation
data.
By
employing
feedforward
neural
network─random
forest-recursive
feature
elimination
(FRR)
algorithm,
effectively
screened,
resulting
rapidly
producing
8-element
10-element
two
VOC
models,
both
achieving
100%
accuracy.
Furthermore,
smartphone-based
point-of-care
testing
(POCT)
platform
achieved
cancer
simulated
model,
image-based
learning,
demonstrating
rationality
practicality
learning
assembly
platforms.
Rare
earth-doped
upconversion
nanoparticles
(UCNPs)
have
achieved
a
wide
range
of
applications
in
the
sensing
field
due
to
their
unique
anti-Stokes
luminescence
property,
minimized
background
interference,
excellent
biocompatibility,
and
stable
physicochemical
properties.
However,
UCNPs-based
platforms
still
face
several
challenges,
including
inherent
limitations
from
UCNPs
such
as
low
quantum
yields
narrow
absorption
cross-sections,
well
constraints
related
energy
transfer
efficiencies
systems.
Therefore,
construction
high-performance
is
an
important
cornerstone
for
conducting
relevant
research.
This
work
begins
by
providing
brief
overview
mechanism
UCNPs.
Subsequently,
it
offers
comprehensive
summary
sensors'
types,
design
principles,
optimized
strategies
platforms.
More
cost-effective
promising
point-of-care
testing
implemented
based
on
systems
are
also
summarized.
Finally,
this
addresses
future
challenges
prospects
ACS Sensors,
Год журнала:
2024,
Номер
9(4), С. 1656 - 1665
Опубликована: Апрель 10, 2024
Arrays
of
cross-reactive
sensors,
combined
with
statistical
or
machine
learning
analysis
their
multivariate
outputs,
have
enabled
the
holistic
complex
samples
in
biomedicine,
environmental
science,
and
consumer
products.
Comparisons
are
frequently
made
to
mammalian
nose
tongue
this
perspective
examines
role
sensing
arrays
analyzing
food
beverages
for
quality,
veracity,
safety.
I
focus
on
optical
sensor
as
low-cost,
easy-to-measure
tools
use
field,
factory
floor,
even
by
consumer.
Novel
materials
approaches
highlighted
challenges
research
field
discussed,
including
sample
processing/handling
access
significant
sets
train
test
tackle
real
issues
industry.
Finally,
examine
whether
comparison
noses
tongues
is
helpful
an
industry
defined
human
taste.
ACS Applied Nano Materials,
Год журнала:
2024,
Номер
7(17), С. 19821 - 19853
Опубликована: Авг. 16, 2024
Food
safety,
particularly
concerning
foods
contaminated
by
toxic
chemicals,
has
emerged
as
a
pervasive
societal
concern.
The
prevalence
of
food
contaminants
spurred
both
scientific
communities
and
industries
to
develop
highly
sensitive
selective
sensors
for
rapid
precise
authentication.
Noble
metal
nanoparticles
(NPs)
have
garnered
significant
attention
in
this
regard
due
their
exceptional
properties,
including
high
sensitivity,
selectivity,
stability,
target
binding
affinity,
versatility
modification
detect
specific
contaminants.
Moreover,
the
readout
such
is
relatively
straightforward,
resulting
color
change
can
be
observed
with
naked
eye.
This
Review
aims
delve
into
current
strategies
involving
various
noble
NPs
colorimetric
nanosensors
safety
monitoring
applications.
It
begins
elucidating
working
principles,
encompassing
localized
surface
plasmon
resonance
(LSPR),
enzyme-based
approaches,
other
methodologies.
Subsequently,
material
properties
commonly
utilized
NPs,
those
gold,
silver,
palladium,
platinum,
copper,
are
meticulously
examined,
providing
comprehensive
overviews
benefits
drawbacks
associated
each
material.
Furthermore,
summarizes
latest
use
cases
diverse
applications,
ranging
from
detection
heavy
veterinary
pesticide
drug
residues
foodborne
pathogens.
Lastly,
it
addresses
remaining
challenges
field
proposes
feasible
solutions,
offering
insights
future
research
directions.
Journal of Agriculture and Food Research,
Год журнала:
2022,
Номер
11, С. 100485 - 100485
Опубликована: Дек. 20, 2022
Climate
change
is
considered
primarily
as
a
human-created
phenomenon
that
changing
the
way
humans
live.
Nowhere
are
impacts
of
climate
more
evident
than
in
food
ecosphere.
Climate-induced
changes
temperature,
precipitation,
and
rain
patterns,
well
extreme
weather
events
have
already
started
impacting
yield,
quality,
safety
food.
Food
availability
fundamental
aspect
ensuring
security
an
adequate
standard
living.
With
change,
there
been
increasing
instances
observed
food,
particularly
from
microbiological
standpoint,
its
quality
yield.
Thus,
urgent
need
for
implementation
advanced
methods
to
predict
implications
(i.e.,
future
issues)
holistic
perspective
(overall
system).
Artificial
Intelligence
(AI)
other
such
technologies
have,
over
years,
permeated
many
facets
chain,
spanning
both
farm-
(or
ocean-)
to-fork
production,
testing
prediction.
As
result,
these
perfectly
positioned
develop
novel
models
change-induced
risks.
This
article
provides
roundup
latest
research
on
use
AI
industry,
impact
social,
ethical,
legal
limitations
same.
Particularly,
this
review
stresses
importance
approach
prediction
encompassing
diverse
data
streams
help
stakeholders
make
most
informed
decisions.
