Chemical Engineering Journal,
Journal Year:
2024,
Volume and Issue:
481, P. 148465 - 148465
Published: Jan. 2, 2024
In
the
field
of
chemical
engineering,
understanding
dynamics
and
probability
drop
coalescence
is
not
just
an
academic
pursuit,
but
a
critical
requirement
for
advancing
process
design
by
applying
energy
only
where
it
needed
to
build
necessary
interfacial
structures,
increasing
efficiency
towards
Net
Zero
manufacture.
This
research
applies
machine
learning
predictive
models
unravel
sophisticated
relationships
embedded
in
experimental
data
on
microfluidics
device.
Through
deployment
SHapley
Additive
exPlanations
values,
features
relevant
processes
are
consistently
identified.
Comprehensive
feature
ablation
tests
further
delineate
robustness
susceptibility
each
model.
Furthermore,
incorporation
Local
Interpretable
Model-agnostic
Explanations
local
interpretability
offers
elucidative
perspective,
clarifying
intricate
decision-making
mechanisms
inherent
model's
predictions.
As
result,
this
provides
relative
importance
outcome
interactions.
It
also
underscores
pivotal
role
model
reinforcing
confidence
predictions
complex
physical
phenomena
that
central
engineering
applications.
Biosensors,
Journal Year:
2023,
Volume and Issue:
13(6), P. 584 - 584
Published: May 27, 2023
Conventional
diagnostic
techniques
are
based
on
the
utilization
of
analyte
sampling,
sensing
and
signaling
separate
platforms
for
detection
purposes,
which
must
be
integrated
to
a
single
step
procedure
in
point
care
(POC)
testing
devices.
Due
expeditious
nature
microfluidic
platforms,
trend
has
been
shifted
toward
implementation
these
systems
analytes
biochemical,
clinical
food
technology.
Microfluidic
molded
with
substances
such
as
polymers
or
glass
offer
specific
sensitive
infectious
noninfectious
diseases
by
providing
innumerable
benefits,
including
less
cost,
good
biological
affinity,
strong
capillary
action
simple
process
fabrication.
In
case
nanosensors
nucleic
acid
detection,
some
challenges
need
addressed,
cellular
lysis,
isolation
amplification
before
its
detection.
To
avoid
laborious
steps
executing
processes,
advances
have
deployed
this
perspective
on-chip
sample
preparation,
introduction
an
emerging
field
modular
microfluidics
that
multiple
advantages
over
microfluidics.
This
review
emphasizes
significance
technology
non-infectious
diseases.
The
isothermal
conjunction
lateral
flow
assay
greatly
increases
binding
efficiency
nanoparticles
biomolecules
improves
limit
sensitivity.
Most
importantly,
deployment
paper-based
material
made
cellulose
reduces
overall
cost.
discussed
explicating
applications
different
fields.
Next-generation
methods
can
improved
using
CRISPR/Cas
systems.
concludes
comparison
future
prospects
various
systems,
plasma
separation
used
Micromachines,
Journal Year:
2023,
Volume and Issue:
14(4), P. 826 - 826
Published: April 8, 2023
Microfluidics
is
a
rapidly
growing
discipline
that
involves
studying
and
manipulating
fluids
at
reduced
length
scale
volume,
typically
on
the
of
micro-
or
nanoliters.
Under
larger
surface-to-volume
ratio,
advantages
low
reagent
consumption,
faster
reaction
kinetics,
more
compact
systems
are
evident
in
microfluidics.
However,
miniaturization
microfluidic
chips
introduces
challenges
stricter
tolerances
designing
controlling
them
for
interdisciplinary
applications.
Recent
advances
artificial
intelligence
(AI)
have
brought
innovation
to
microfluidics
from
design,
simulation,
automation,
optimization
bioanalysis
data
analytics.
In
microfluidics,
Navier-Stokes
equations,
which
partial
differential
equations
describing
viscous
fluid
motion
complete
form
known
not
general
analytical
solution,
can
be
simplified
fair
performance
through
numerical
approximation
due
inertia
laminar
flow.
Approximation
using
neural
networks
trained
by
rules
physical
knowledge
new
possibility
predict
physicochemical
nature.
The
combination
automation
produce
large
amounts
data,
where
features
patterns
difficult
discern
human
extracted
machine
learning.
Therefore,
integration
with
AI
potential
revolutionize
workflow
enabling
precision
control
analysis.
Deployment
smart
may
tremendously
beneficial
various
applications
future,
including
high-throughput
drug
discovery,
rapid
point-of-care-testing
(POCT),
personalized
medicine.
this
review,
we
summarize
key
integrated
discuss
outlook
possibilities
combining
Chemical Engineering Journal,
Journal Year:
2024,
Volume and Issue:
481, P. 148465 - 148465
Published: Jan. 2, 2024
In
the
field
of
chemical
engineering,
understanding
dynamics
and
probability
drop
coalescence
is
not
just
an
academic
pursuit,
but
a
critical
requirement
for
advancing
process
design
by
applying
energy
only
where
it
needed
to
build
necessary
interfacial
structures,
increasing
efficiency
towards
Net
Zero
manufacture.
This
research
applies
machine
learning
predictive
models
unravel
sophisticated
relationships
embedded
in
experimental
data
on
microfluidics
device.
Through
deployment
SHapley
Additive
exPlanations
values,
features
relevant
processes
are
consistently
identified.
Comprehensive
feature
ablation
tests
further
delineate
robustness
susceptibility
each
model.
Furthermore,
incorporation
Local
Interpretable
Model-agnostic
Explanations
local
interpretability
offers
elucidative
perspective,
clarifying
intricate
decision-making
mechanisms
inherent
model's
predictions.
As
result,
this
provides
relative
importance
outcome
interactions.
It
also
underscores
pivotal
role
model
reinforcing
confidence
predictions
complex
physical
phenomena
that
central
engineering
applications.
