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 …
Pore model for nanofiltration: History, theoretical framework, key predictions, limitations, and prospects
This review introduces the development history of the widely used NF model, ie, the Donnan-
Steric Pore Model with Dielectric Exclusion (DSPM-DE), from the emergence of its …
Steric Pore Model with Dielectric Exclusion (DSPM-DE), from the emergence of its …
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) …
Can machine language and artificial intelligence revolutionize process automation for water treatment and desalination?
Artificial intelligence (AI) is a powerful tool that is commonly applied in engineering multi-
disciplines owing to its functionality to resolve real-world problems where deterministic …
disciplines owing to its functionality to resolve real-world problems where deterministic …
Artificial neural network modeling and response surface methodology of desalination by reverse osmosis
Response surface methodology (RSM) and artificial neural network (ANN) have been used
to develop predictive models for simulation and optimization of reverse osmosis (RO) …
to develop predictive models for simulation and optimization of reverse osmosis (RO) …
Physics-informed deep learning for multi-species membrane separations
D Rehman, JH Lienhard - Chemical Engineering Journal, 2024 - Elsevier
Conventional continuum models for ion transport across polyamide membranes require
solving partial differential equations (PDEs). These models typically introduce a host of …
solving partial differential equations (PDEs). These models typically introduce a host of …
Modeling of forward osmosis process using artificial neural networks (ANN) to predict the permeate flux
Artificial neural networks (ANN) are black box models that are becoming more popular than
transport-based models due to their high accuracy and less computational time in …
transport-based models due to their high accuracy and less computational time in …
Experimental investigation, modeling and optimization of membrane separation using artificial neural network and multi-objective optimization using genetic algorithm
In this work, treatment of oily wastewaters with commercial polyacrylonitrile (PAN)
ultrafiltration (UF) membranes was investigated. In order to do these experiments, the outlet …
ultrafiltration (UF) membranes was investigated. In order to do these experiments, the outlet …
Revealing key structural and operating features on water/salts selectivity of polyamide nanofiltration membranes by ensemble machine learning
X Ma, D Lu, J Lu, Y Qian, S Zhang, Z Yao, L Liang… - Desalination, 2023 - Elsevier
Nanofiltration (NF) plays an increasingly central role in water/salts separation, which puts
forward tailored requirements on NF membranes in a variety of application scenarios …
forward tailored requirements on NF membranes in a variety of application scenarios …