Artificial intelligence-incorporated membrane fouling prediction for membrane-based processes in the past 20 years: A critical review
Membrane fouling is one of major obstacles in the application of membrane technologies.
Accurately predicting or simulating membrane fouling behaviours is of great significance to …
Accurately predicting or simulating membrane fouling behaviours is of great significance to …
Artificial neural network modeling of wastewater treatment and desalination using membrane processes: A review
The freshwater scarcity is causing a major challenge due to the growing global population.
The brackish water and seawater are the biggest sources of water on the planet. Therefore …
The brackish water and seawater are the biggest sources of water on the planet. Therefore …
Predicting micropollutant removal by reverse osmosis and nanofiltration membranes: is machine learning viable?
Predictive models for micropollutant removal by membrane separation are highly desirable
for the design and selection of appropriate membranes. While machine learning (ML) …
for the design and selection of appropriate membranes. While machine learning (ML) …
Prediction of organic contaminant rejection by nanofiltration and reverse osmosis membranes using interpretable machine learning models
T Zhu, Y Zhang, C Tao, W Chen, H Cheng - Science of The Total …, 2023 - Elsevier
Efficiency improvement in contaminant removal by nanofiltration (NF) and reverse osmosis
(RO) membranes is a multidimensional process involving membrane material selection and …
(RO) membranes is a multidimensional process involving membrane material selection and …
A review on membrane fouling prediction using artificial neural networks (ANNs)
Membrane fouling is a major hurdle to effective pressure-driven membrane processes, such
as microfiltration (MF), ultrafiltration (UF), nanofiltration (NF), and reverse osmosis (RO) …
as microfiltration (MF), ultrafiltration (UF), nanofiltration (NF), and reverse osmosis (RO) …
Elucidating governing factors of PFAS removal by polyamide membranes using machine learning and molecular simulations
Per-and polyfluoroalkyl substances (PFASs) have recently garnered considerable concerns
regarding their impacts on human and ecological health. Despite the important roles of …
regarding their impacts on human and ecological health. Despite the important roles of …
Exploring the knowledge attained by machine learning on ion transport across polyamide membranes using explainable artificial intelligence
Recent studies have increasingly applied machine learning (ML) to aid in performance and
material design associated with membrane separation. However, whether the knowledge …
material design associated with membrane separation. However, whether the knowledge …
Quantification and modelling of organic micropollutant removal by reverse osmosis (RO) drinking water treatment
Reverse osmosis (RO) is the most promising membrane technology in organic
micropollutants (MPs) removal of drinking water treatment. For 78 MPs, passage and …
micropollutants (MPs) removal of drinking water treatment. For 78 MPs, passage and …
Experiments and machine learning-based modeling for haloacetic acids rejection by nanofiltration: Influence of solute properties and operating conditions
F Wang, W Wang, H Wang, Z Zhao, T Zhou… - Science of the Total …, 2023 - Elsevier
Because of potential risks to public health, the presence of haloacetic acids (HAAs) in
drinking water is a major concern. Nanofiltration (NF) has shown potential for HAAs …
drinking water is a major concern. Nanofiltration (NF) has shown potential for HAAs …
QSPR estimation models of normal boiling point and relative liquid density of pure hydrocarbons using MLR and MLP-ANN methods
This work aimed to predict the normal boiling point temperature (Tb) and relative liquid
density (d20) of petroleum fractions and pure hydrocarbons, through a multi-layer …
density (d20) of petroleum fractions and pure hydrocarbons, through a multi-layer …