Advanced Theory and Simulations,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Oct. 30, 2024
Abstract
Artificial
Intelligence
(AI)
is
pivotal
in
advancing
science,
including
nanomaterial
studies.
This
review
explores
AI‐based
image
processing
nanoscience,
focusing
on
algorithms
to
enhance
characterization
results
from
instruments
like
scanning
electron
microscopy,
transmission
X‐ray
diffraction,
atomic
force
microscopy
etc.
It
addresses
the
significance
of
AI
challenges
for
nano
material
characterization,
and
AI's
role
structural
analysis,
property
prediction,
deriving
structure‐property
relations,
dataset
augmentation,
improving
model
robustness.
Key
techniques
such
as
Graph
Neural
Networks,
adversarial
training,
transfer
learning,
generative
models,
attention
mechanisms,
federated
learning
are
highlighted
their
contributions
science
The
concludes
by
outlining
persisting
thrust
areas
future
research,
aiming
propel
nanoscience
with
AI.
comprehensive
analysis
underscores
importance
AI‐powered
offering
valuable
insights
researchers.
Nano Select,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Jan. 30, 2025
ABSTRACT
The
applications
of
nanoparticles
(NPs)
have
shown
tremendous
growth
during
the
last
decade
in
field
biomedicine.
Although
chemical
and
physical
methods
dominate
large‐scale
NP
synthesis,
such
are
also
known
for
their
adverse
impact
on
environment
health.
In
contrast,
use
biological
systems
provides
a
sustainable
alternative
producing
functional
NPs
by
biomineralization
process.
transformative
power
artificial
intelligence
(AI)
has
been
proven
prudent
diagnosis,
drug
development,
therapy,
clinical
decision‐making.
AI
can
be
utilized
tailored
design,
scale‐up
biomedical
applications.
present
review
an
overview
process
its
advantages
over
other
eco‐friendly
synthesis
opportunities.
Specific
emphasis
is
provided
application
cancer
therapy
how
biologically
compatible
improve
management.
Finally,
to
best
our
knowledge,
potential
integrating
comprehensively
analyzed
first
time.
Additionally,
help
surpass
conventionally
synthesized
toxicity
toxicology
material
science
provided.
Machine
learning
(ML),
as
an
advanced
data
analysis
tool,
simulates
the
process
of
human
brain,
enabling
extraction
features,
discovery
patterns,
and
making
accurate
predictions
or
decisions
from
complex
data.
In
field
nanomaterial
design,
application
ML
technology
not
only
accelerates
performance
optimization
nanomaterials
but
also
promotes
innovation
materials
science
research
methods.
Bibliometrics,
a
method
based
on
quantitative
analysis,
provides
us
with
macro
perspective
to
observe
understand
in
design
by
statistically
analyzing
various
indicators
scientific
literature.
This
paper
quantitatively
analyzes
literature
related
ML-driven
seven
dimensions,
revealing
importance
necessity
design.
It
systematically
diversified
applications
combination
suitable
algorithms
being
key
enhancing
nanomaterials.
addition,
this
discusses
current
challenges
future
development
directions,
including
quality
set
construction,
algorithm
optimization,
deepening
interdisciplinary
cooperation.
review
researchers
state
trends
ideas
suggestions
for
research.
is
significant
value
promoting
progress
fostering
in-depth
research,
accelerating
innovative
material
technologies.
Molecules,
Journal Year:
2025,
Volume and Issue:
30(4), P. 829 - 829
Published: Feb. 11, 2025
In
recent
years,
the
field
of
chiral
gold
nanomaterials
has
witnessed
significant
advancements
driven
by
their
unique
properties
and
diverse
applications
in
various
scientific
domains.
This
review
provides
an
in-depth
examination
synthesis
methodologies
evolving
nanomaterials,
which
have
emerged
as
vital
tools
areas
such
antibacterial
therapies,
biosensing,
catalysis,
nanomedicine.
We
start
discussing
techniques,
focused
on
seed-mediated
growth
circularly
polarized
light-assisted
methods,
each
contributing
to
controlled
nanostructures
with
tailored
optical
activities.
further
delves
into
these
showcasing
potential
combating
antibiotic-resistant
bacteria,
improving
cancer
immunotherapy,
promoting
tissue
regeneration,
enabling
precise
biosensing
through
enhanced
sensitivity
selectivity.
highlight
fundamental
principles
chirality
its
critical
role
biological
systems,
emphasizing
importance
enhancing
signals
facilitating
molecular
interactions.
By
consolidating
findings
methodologies,
this
endeavors
illuminate
promising
future
addressing
contemporary
challenges.
Chemical Physics Reviews,
Journal Year:
2025,
Volume and Issue:
6(1)
Published: March 1, 2025
Surfaces
and
interfaces
play
key
roles
in
chemical
material
science.
Understanding
physical
processes
at
complex
surfaces
is
a
challenging
task.
Machine
learning
provides
powerful
tool
to
help
analyze
accelerate
simulations.
This
comprehensive
review
affords
an
overview
of
the
applications
machine
study
systems
materials.
We
categorize
into
following
broad
categories:
solid–solid
interface,
solid–liquid
liquid–liquid
surface
solid,
liquid,
three-phase
interfaces.
High-throughput
screening,
combined
first-principles
calculations,
force
field
accelerated
molecular
dynamics
simulations
are
used
rational
design
such
as
all-solid-state
batteries,
solar
cells,
heterogeneous
catalysis.
detailed
information
on
for
The Journal of Physical Chemistry C,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Feb. 6, 2025
Handedness
classification
plays
a
crucial
role
in
the
synthesis
and
application
of
chiral
nanomaterials,
while
currently,
it
usually
relies
on
manual
detection
identification.
Artificial
intelligence
is
increasingly
being
integrated
into
scientific
discovery
to
achieve
goals
that
might
not
have
been
possible
using
traditional
methods
alone.
Here,
we
introduce
novel
framework
automatically
recognize
classify
nanoparticles
based
their
asymmetric
morphology
scanning
electron
microscope
images.
By
combining
image
segmentation
models
with
convolutional
neural
networks,
create
workflow
high
accuracy
real
SEM
images
minimal
labeling.
The
approach
has
successfully
applied
two
demonstrating
its
robustness
potential
for
integration
high-throughput
analysis
workflows
further
studies
materials.
Inorganics,
Journal Year:
2025,
Volume and Issue:
13(3), P. 72 - 72
Published: Feb. 27, 2025
Chiral
gold
nanomaterials
have
promising
applications
in
biomedicine,
catalysis,
optics
and
other
fields.
However,
the
complexity
of
their
chiral
sources
has
led
to
many
challenges
terms
functional
design
controlled
synthesis.
In
this
paper,
we
systematically
review
development
history
Au
nanomaterials;
deeply
analyze
synthesis
strategy,
construction
mechanism,
performance
optimization
pathway;
discuss
formation
mechanism
light
progress
cutting-edge
research
look
into
future
direction
development.
The
aim
is
provide
theoretical
methodological
support
for
controllable
nanomaterials.
