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) …
Artificial neural network modeling for the prediction, estimation, and treatment of diverse wastewaters: a comprehensive review and future perspective
The application of artificial neural networks (ANNs) in the treatment of wastewater has
achieved increasing attention, as it enhances the efficiency and sustainability of wastewater …
achieved increasing attention, as it enhances the efficiency and sustainability of wastewater …
Enhanced performance of a hybrid adsorption desalination system integrated with solar PV/T collectors: Experimental investigation and machine learning modeling …
This study explores the performance augmentation of a solar adsorption desalination system
(SADS) powered by a hybrid solar thermal system with evacuated tubes and photovoltaic …
(SADS) powered by a hybrid solar thermal system with evacuated tubes and photovoltaic …
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) …
A review on state-of-the-art applications of data-driven methods in desalination systems
The substitution of conventional mathematical models with fast and accurate modeling tools
can result in the further development of desalination technologies and tackling the need for …
can result in the further development of desalination technologies and tackling the need for …
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 …