ACS Sensors,
Journal Year:
2024,
Volume and Issue:
9(9), P. 4662 - 4670
Published: Aug. 12, 2024
The
accumulation
of
micro/nanoplastics
(MNPs)
in
ecosystems
poses
tremendous
environmental
risks
for
terrestrial
and
aquatic
organisms.
Designing
rapid,
field-deployable,
sensitive
devices
assessing
the
potential
MNPs
pollution
is
critical.
However,
current
techniques
detection
have
limited
effectiveness.
Here,
we
design
a
wireless
portable
device
that
allows
sensitive,
on-site
MNPs,
followed
by
remote
data
processing
via
machine
learning
algorithms
quantitative
fluorescence
imaging.
We
utilized
supramolecular
labeling
strategy,
employing
luminescent
metal-phenolic
networks
composed
zirconium
ions,
tannic
acid,
rhodamine
B,
to
efficiently
label
various
sizes
(e.g.,
50
nm-10
μm).
Results
showed
our
can
quantify
as
low
330
microplastics
3.08
×
10
Scientific Reports,
Journal Year:
2023,
Volume and Issue:
13(1)
Published: July 7, 2023
Abstract
Marine
microplastics
are
emerging
as
a
growing
environmental
concern
due
to
their
potential
harm
marine
biota.
The
substantial
variations
in
physical
and
chemical
properties
pose
significant
challenge
when
it
comes
sampling
characterizing
small-sized
microplastics.
In
this
study,
we
introduce
novel
microfluidic
approach
that
simplifies
the
trapping
identification
process
of
surface
seawater,
eliminating
need
for
labeling.
We
examine
various
models,
including
support
vector
machine,
random
forest,
convolutional
neural
network
(CNN),
residual
(ResNet34),
assess
performance
identifying
11
common
plastics.
Our
findings
reveal
CNN
method
outperforms
other
achieving
an
impressive
accuracy
93%
mean
area
under
curve
98
±
0.02%.
Furthermore,
demonstrate
miniaturized
devices
can
effectively
trap
identify
smaller
than
50
µm.
Overall,
proposed
facilitates
efficient
microplastics,
potentially
contributing
crucial
long-term
monitoring
treatment
efforts.
Analytical Chemistry,
Journal Year:
2024,
Volume and Issue:
96(26), P. 10772 - 10779
Published: June 21, 2024
A
simple,
sustainable,
and
sensitive
monitoring
approach
of
micro/nanoplastics
(MNPs)
in
aqueous
samples
is
crucial
since
it
helps
assessing
the
extent
contamination
understanding
potential
risks
associated
with
their
presence
without
causing
additional
stress
to
environment.
In
this
study,
a
novel
strategy
for
qualitative
quantitative
determination
MNPs
water
by
direct
solid-phase
microextraction
(SPME)
coupled
gas
chromatography–mass
spectrometry
(GC-MS)
was
proposed
first
time.
Spherical
poly(methyl
methacrylate)
(PMMA)
irregularly
shaped
polyvinyl
dichloride
(PVDC)
were
used
evaluate
feasibility
performance
method.
The
results
demonstrated
that
both
PMMA
PVDC
efficiently
extracted
homemade
SPME
coating
nitrogen-doped
porous
carbons
(N-SPCs)
exhibited
sufficient
thermal
decomposition
GC-MS
injection
port.
Excellent
extraction
performances
N-SPCs
are
attributed
hydrophobic
cross-linking,
electrostatic
forcing,
hydrogen
bonding,
pore
trapping.
Methyl
methacrylate
identified
as
marker
PMMA,
while
1,3-dichlorobenzene
1,3,5-trichlorobenzene
indicators
PVDC.
Under
optimal
conditions,
method
ultrahigh
sensitivity,
limit
detection
0.0041
μg/L
0.0054
Notably,
programmed
temperature
injector
developed
discriminate
eliminate
interferences
intrinsic
indicator
compounds.
Owing
integration
sampling,
extraction,
injection,
into
one
step
SPME,
demonstrates
exceptional
eliminating
necessity
complex
sample
pretreatment
procedures
use
organic
solvents.
Finally,
successfully
applied
real
samples.
Environmental Science & Technology,
Journal Year:
2024,
Volume and Issue:
58(20), P. 8919 - 8931
Published: May 6, 2024
For
the
first
time,
we
present
a
much-needed
technology
for
in
situ
and
real-time
detection
of
nanoplastics
aquatic
systems.
We
show
an
artificial
intelligence-assisted
nanodigital
in-line
holographic
microscopy
(AI-assisted
nano-DIHM)
that
automatically
classifies
nano-
microplastics
simultaneously
from
nonplastic
particles
within
milliseconds
stationary
dynamic
natural
waters,
without
sample
preparation.
AI-assisted
nano-DIHM
identifies
2
1%
waterborne
as
nano/microplastics
Lake
Ontario
Saint
Lawrence
River,
respectively.
Nano-DIHM
provides
physicochemical
properties
single
or
clusters
nano/microplastics,
including
size,
shape,
optical
phase,
perimeter,
surface
area,
roughness,
edge
gradient.
It
distinguishes
mixtures
organics,
inorganics,
biological
particles,
coated
heterogeneous
clusters.
This
allows
4D
tracking
3D
structural
spatial
study
nano/microplastics.
Independent
transmission
electron
microscopy,
mass
spectrometry,
nanoparticle
analysis
validates
data.
Complementary
modeling
demonstrates
have
significantly
distinct
distribution
patterns
water,
which
affect
their
transport
fate,
rendering
powerful
tool
accurate
nano/microplastic
life-cycle
hotspot
remediation.
Chemical Communications,
Journal Year:
2024,
Volume and Issue:
60(67), P. 8840 - 8843
Published: Jan. 1, 2024
Au@Ag
core-shell
composites
were
successfully
fabricated
on
urchin-like
covalent
organic
frameworks
(COFs),
providing
a
platform
with
numerous
hot
spots
for
the
detection
of
two
categories
emerging
contaminants:
sulfonamide
antibiotics
and
nanoplastics,
using
surface-enhanced
Raman
spectroscopy
(SERS).
Au
seeds
(∼10
nm)
generated
COFs,
leveraging
reducing
properties
vinyl
imino
groups
within
framework.
This
ensured
growth
dense
uniformly
distributed
Ag
nanoparticles.
The
COFs
exceptionally
large
surface
area
(2324
m
ACS Sensors,
Journal Year:
2024,
Volume and Issue:
9(9), P. 4662 - 4670
Published: Aug. 12, 2024
The
accumulation
of
micro/nanoplastics
(MNPs)
in
ecosystems
poses
tremendous
environmental
risks
for
terrestrial
and
aquatic
organisms.
Designing
rapid,
field-deployable,
sensitive
devices
assessing
the
potential
MNPs
pollution
is
critical.
However,
current
techniques
detection
have
limited
effectiveness.
Here,
we
design
a
wireless
portable
device
that
allows
sensitive,
on-site
MNPs,
followed
by
remote
data
processing
via
machine
learning
algorithms
quantitative
fluorescence
imaging.
We
utilized
supramolecular
labeling
strategy,
employing
luminescent
metal-phenolic
networks
composed
zirconium
ions,
tannic
acid,
rhodamine
B,
to
efficiently
label
various
sizes
(e.g.,
50
nm-10
μm).
Results
showed
our
can
quantify
as
low
330
microplastics
3.08
×
10
