Triggering nanoconfinement effect in advanced oxidation processes (AOPs) for boosted degradation of organic contaminants: A review
Chemical Engineering Journal,
Год журнала:
2024,
Номер
503, С. 158428 - 158428
Опубликована: Дек. 9, 2024
Язык: Английский
Piecewise Response Surface Methodology for Enhanced Modeling and Optimization of Complex Systems
Korean Journal of Chemical Engineering,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 3, 2025
Язык: Английский
Deep eutectic solvent-modified polyvinyl alcohol/chitosan thin film membrane for dye adsorption: Machine learning modeling, experimental, and density functional theory calculations
International Journal of Biological Macromolecules,
Год журнала:
2025,
Номер
294, С. 139479 - 139479
Опубликована: Янв. 5, 2025
Язык: Английский
Application of machine learning for environmentally friendly advancement: exploring biomass-derived materials in wastewater treatment and agricultural sector − a review
Journal of Environmental Science and Health Part A,
Год журнала:
2025,
Номер
unknown, С. 1 - 16
Опубликована: Фев. 2, 2025
There
are
several
uses
for
biomass-derived
materials
(BDMs)
in
the
irrigation
and
farming
industries.
To
solve
problems
with
material,
process,
supply
chain
design,
BDM
systems
have
started
to
use
machine
learning
(ML),
a
new
technique
approach.
This
study
examined
articles
published
since
2015
understand
better
current
status,
future
possibilities,
capabilities
of
ML
supporting
environmentally
friendly
development
applications.
Previous
applications
were
classified
into
three
categories
according
their
objectives:
material
process
performance
prediction
sustainability
evaluation.
helps
optimize
BDMs
systems,
predict
properties
performance,
reverse
engineering,
data
difficulties
evaluations.
Ensemble
models
cutting-edge
Neural
Networks
operate
satisfactorily
on
these
datasets
easily
generalized.
neural
network
poor
interpretability,
there
not
been
any
studies
assessment
that
consider
geo-temporal
dynamics;
thus,
building
methods
is
currently
practical.
Future
research
should
follow
workflow.
Investigating
potential
system
optimization,
evaluation
sustainable
requires
further
investigation.
Язык: Английский
Applications of machine learning in surfaces and interfaces
Chemical Physics Reviews,
Год журнала:
2025,
Номер
6(1)
Опубликована: Март 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
Язык: Английский
Prediction of Cr6+ removal on the biosorbent from pine cone residue with machine learning simulations
Joaquim G.G.S. Bento,
Luidy F. Senra,
Lana S. Maia
и другие.
Surfaces and Interfaces,
Год журнала:
2025,
Номер
unknown, С. 106460 - 106460
Опубликована: Апрель 1, 2025
Язык: Английский
Selective acid gas separation from diatomic nonmetal gas via ZIF-8 membrane: Taguchi analysis and neural network modeling
Results in Engineering,
Год журнала:
2024,
Номер
24, С. 103102 - 103102
Опубликована: Окт. 10, 2024
Язык: Английский
Citric acid modification in fabrication of composite aerogels from cigarette butts and chitosan for enhancing dye removal efficiency
Tram Tran Ngoc Nghiem,
V. Thieu,
Nguyen Song Thao Nguyen
и другие.
Clean Technologies and Environmental Policy,
Год журнала:
2024,
Номер
unknown
Опубликована: Окт. 10, 2024
Язык: Английский
Particle Size Distribution in Holby–Morgan Degradation Model of Platinum on Carbon Catalyst in Fuel Cell: Normal Distribution
Technologies,
Год журнала:
2024,
Номер
12(10), С. 202 - 202
Опубликована: Окт. 17, 2024
The
influence
of
particle
size
distribution
in
platinum
catalysts
on
the
aging
PEM
fuel
cells
described
by
Holby–Morgan
electrochemical
degradation
model
is
under
investigation.
non-diffusive
simulates
mechanisms
drop
Pt
dissolution
and
growth
through
ion
deposition.
Without
spatial
dependence,
number
differential
equations
can
be
reduced
using
first
integral
system.
For
an
accelerated
stress
test,
a
non-symmetric
square-wave
potential
profile
applied
according
to
European
harmonized
protocol.
normal
determined
two
probability
parameters
expectation
standard
deviation
represented
within
finite
groups.
Numerical
solution
nonlinear
diffusion
equation
justifies
dispersion
for
small
narrowing
large
means,
decrease
or
increase
amplitude,
movement
diameters
towards
sizes,
which
faster
particles.
Язык: Английский