Polymers,
Год журнала:
2024,
Номер
16(18), С. 2616 - 2616
Опубликована: Сен. 15, 2024
Composite
track-etched
membranes
(CTeMs)
emerged
as
a
versatile
and
high-performance
class
of
materials,
combining
the
precise
pore
structures
traditional
(TeMs)
with
enhanced
functionalities
integrated
nanomaterials.
This
review
provides
comprehensive
overview
synthesis,
functionalization,
applications
CTeMs.
By
incorporating
functional
phases
such
metal
nanoparticles
conductive
nanostructures,
CTeMs
exhibit
improved
performance
in
various
domains.
In
environmental
remediation,
effectively
capture
decompose
pollutants,
offering
both
separation
detoxification.
sensor
technology,
they
have
potential
to
provide
high
sensitivity
selectivity,
essential
for
accurate
detection
medical
applications.
For
energy
storage,
may
be
promising
enhancing
ion
transport,
flexibility,
mechanical
stability,
addressing
key
issues
battery
supercapacitor
performance.
Biomedical
benefit
from
versality
CTeMs,
potentially
supporting
advanced
drug
delivery
systems
tissue
engineering
scaffolds.
Despite
their
numerous
advantages,
challenges
remain
fabrication
scalability
requiring
sophisticated
techniques
meticulous
optimization.
Future
research
directions
include
development
cost-effective
production
methods
exploration
new
materials
further
enhance
capabilities
underscores
transformative
across
highlights
need
continued
innovation
fully
realize
benefits.
Environmental Science & Technology,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 16, 2024
Polymeric
membranes
have
been
widely
used
for
liquid
and
gas
separation
in
various
industrial
applications
over
the
past
few
decades
because
of
their
exceptional
versatility
high
tunability.
Traditional
trial-and-error
methods
material
synthesis
are
inadequate
to
meet
growing
demands
high-performance
membranes.
Machine
learning
(ML)
has
demonstrated
huge
potential
accelerate
design
discovery
membrane
materials.
In
this
review,
we
cover
strengths
weaknesses
traditional
methods,
followed
by
a
discussion
on
emergence
ML
developing
advanced
polymeric
We
describe
methodologies
data
collection,
preparation,
commonly
models,
explainable
artificial
intelligence
(XAI)
tools
implemented
research.
Furthermore,
explain
experimental
computational
validation
steps
verify
results
provided
these
models.
Subsequently,
showcase
successful
case
studies
emphasize
inverse
methodology
within
ML-driven
structured
framework.
Finally,
conclude
highlighting
recent
progress,
challenges,
future
research
directions
advance
next
generation
With
aim
provide
comprehensive
guideline
researchers,
scientists,
engineers
assisting
implementation
process.
Polymers,
Год журнала:
2024,
Номер
16(18), С. 2616 - 2616
Опубликована: Сен. 15, 2024
Composite
track-etched
membranes
(CTeMs)
emerged
as
a
versatile
and
high-performance
class
of
materials,
combining
the
precise
pore
structures
traditional
(TeMs)
with
enhanced
functionalities
integrated
nanomaterials.
This
review
provides
comprehensive
overview
synthesis,
functionalization,
applications
CTeMs.
By
incorporating
functional
phases
such
metal
nanoparticles
conductive
nanostructures,
CTeMs
exhibit
improved
performance
in
various
domains.
In
environmental
remediation,
effectively
capture
decompose
pollutants,
offering
both
separation
detoxification.
sensor
technology,
they
have
potential
to
provide
high
sensitivity
selectivity,
essential
for
accurate
detection
medical
applications.
For
energy
storage,
may
be
promising
enhancing
ion
transport,
flexibility,
mechanical
stability,
addressing
key
issues
battery
supercapacitor
performance.
Biomedical
benefit
from
versality
CTeMs,
potentially
supporting
advanced
drug
delivery
systems
tissue
engineering
scaffolds.
Despite
their
numerous
advantages,
challenges
remain
fabrication
scalability
requiring
sophisticated
techniques
meticulous
optimization.
Future
research
directions
include
development
cost-effective
production
methods
exploration
new
materials
further
enhance
capabilities
underscores
transformative
across
highlights
need
continued
innovation
fully
realize
benefits.
