Predicting micropollutant removal through nanopore-sized membranes using several machine-learning approaches based on feature engineering

Yogarathinam, Lukka Thuyavan; Abba, Sani I.; Usman, Jamilu; Lawal, Dahiru U.; Aljundi, Isam H.

doi:10.1039/d4ra02475c

RSC Adv.

2024

DOI: 10.1039/d4ra02475c

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Predicting micropollutant removal through nanopore-sized membranes using several machine-learning approaches based on feature engineering

Lukka Thuyavan Yogarathinam,

Sani I. Abba,

Jamilu Usman

et al.

Abstract: Predicting the efficacy of micropollutant separation through self-fabricated membranes is an arduous endeavor.

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Utilising Artificial Intelligence to Predict Membrane Behaviour in Water Purification and Desalination

Shahouni,

Abbasi,

Dibaj

et al. 2024

Water

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Water scarcity is a critical global issue, necessitating efficient water purification and desalination methods. Membrane separation methods are environmentally friendly and consume less energy, making them more economical compared to other desalination and purification methods. This survey explores the application of artificial intelligence (AI) to predict membrane behaviour in water purification and desalination processes. Various AI platforms, including machine learning (ML) and artificial neural networks (ANNs), were utilised to model water flux, predict fouling behaviour, simulate micropollutant dynamics and optimise operational parameters. Specifically, models such as convolutional neural networks (CNNs), recurrent neural networks (RNNs) and support vector machines (SVMs) have demonstrated superior predictive capabilities in these applications. This review studies recent advancements, emphasising the superior predictive capabilities of AI models compared to traditional methods. Key findings include the development of AI models for various membrane separation techniques and the integration of AI concepts such as ML and ANNs to simulate membrane fouling, water flux and micropollutant behaviour, aiming to enhance wastewater treatment and optimise treatment and desalination processes. In conclusion, this review summarised the applications of AI in predicting the behaviour of membranes as well as their strengths, weaknesses and future directions of AI in membranes for water purification and desalination processes.

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Utilising Artificial Intelligence to Predict Membrane Behaviour in Water Purification and Desalination

Shahouni,

Abbasi,

Dibaj

et al. 2024

Water

View full text Add to dashboard Cite

show abstract

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Predicting micropollutant removal through nanopore-sized membranes using several machine-learning approaches based on feature engineering

Abstract: Predicting the efficacy of micropollutant separation through self-fabricated membranes is an arduous endeavor.

Cited by 1 publication

References 51 publications

Utilising Artificial Intelligence to Predict Membrane Behaviour in Water Purification and Desalination

Utilising Artificial Intelligence to Predict Membrane Behaviour in Water Purification and Desalination

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