Journal of Agricultural and Food Chemistry,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 18, 2024
This
study
explores
the
development
and
application
of
gold
4-mercaptopyridine
(MPY)
perovskite-engineered
robust
nanofibers
(GLAMPER-NFs)
for
ultrasensitive
detection
Abscisic
acid
(ABA)
under
Raman
spectroscopy,
a
crucial
plant
hormone.
The
GLAMPER-NFs
composite
material,
consisting
MAPbCl
The
enhancement
of
hot-spot
intensity
for
surface-enhanced
Raman
scattering
(SERS)
detection
can
be
achieved
through
the
utilization
hierarchical
structures
comprised
surface-accessible
plasmonic
gold
and
silver
nanoparticles.
A
facile
synthesis
platform
for
the
formation
of
stable
single
crystalline
Ag
dendrites
is
demonstrated.
Using
a
porous
electrospun
polyacrylonitrile
nanofiber
network
on
Al
foil
as
template
facilitates
more
uniform
dendritic
growth
in
presence
D‐glucose.
In
contrast,
denser
polymer
restricts
nucleation
site
availability
foil,
highlighting
critical
role
substrate.
The
silver
reduced
solution
when
two
simultaneous
processes
occur:
electroreduction
+
D‐glucose
and
galvanic
displacement
driven
by
interaction
with
aluminum
High‐resolution
transmission
electron
microscopy
analysis
shows
nature
grown
from
substrate,
revealing
atomic
structures
closely
packed
layers
forming
highly
faulted
face‐centered
cubic
hexagonal
close‐packed
structures.
remarkable
long‐term
stability
primarily
attributed
to
their
structure,
additional
contributions
capping
D‐gluconic
acid,
confirmed
Raman
analysis.
This
novel
approach
generation
has
significant
potential
applications
such
surface‐enhanced
scattering,
which
date
been
considered
be
very
sensitive
environmental
effects.
Analytical Methods,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 1, 2025
An
integrated
sensing
platform
was
developed
for
the
rapid
and
quantitative
detection
of
pesticide
residues
in
fruits.
This
utilizes
a
thin,
shape-adaptable,
flexible
SERS
substrate
conjunction
with
1D
CNN
model.
ACS Applied Materials & Interfaces,
Год журнала:
2024,
Номер
16(40), С. 54496 - 54507
Опубликована: Сен. 26, 2024
Continuous
and
reliable
monitoring
of
gait
is
crucial
for
health
monitoring,
such
as
postoperative
recovery
bone
joint
surgery
early
diagnosis
disease.
However,
existing
analysis
systems
often
suffer
from
large
volumes
the
requirement
special
space
setting
motion
capture
systems,
limiting
their
application
in
daily
life.
Here,
we
develop
an
intelligent
prediction
system
based
on
flexible
piezoelectric
sensors
deep
learning
neural
networks
with
high
sensitivity
(241.29
mV/N),
quick
response
(66
ms
loading,
87
recovery),
excellent
stability
(