Artificial Intelligence Model for Forecasting of Membrane Fouling in Wastewater Treatment by Membrane Technology

Do, Khac‐Uan; Schmitt, F. G.

doi:10.1002/9781119536260.ch9

Cited by 2 publications

(1 citation statement)

References 63 publications

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“…The design, production, selection and operation of ultrafiltration or microfiltration systems need process modeling. Extensive studies on the modeling of membrane filtration can be found in literature (Khac-Uan & Félix, 2020 ; Krippla et al, 2020 ; Yusuf et al, 2016 ). Here, some models widely accepted are described.…”

Section: Scientific Basis Of Membrane Filtration To Remove Microorgan...mentioning

confidence: 99%

Application of Membrane Filtration to Cold Sterilization of Drinks and Establishment of Aseptic Workshop

2023

Food Environ Virol

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Aseptic packaging of high quality beverage is necessary and its cold-pasteurization or sterilization is vital. Studies on application of ultrafiltration or microfiltration membrane to cold- pasteurization or sterilization for the aseptic packaging of beverages have been reviewed. Designing and manufacturing ultrafiltration or microfiltration membrane systems for cold-pasteurization or sterilization of beverage are based on the understanding of size of microorganisms and theoretical achievement of filtration. It is concluded that adaptability of membrane filtration, especially its combination with other safe cold method, to cold- pasteurization and sterilization for the aseptic packaging of beverages should be assured without a shadow of doubt in future.

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Section: Scientific Basis Of Membrane Filtration To Remove Microorgan...mentioning

confidence: 99%

Application of Membrane Filtration to Cold Sterilization of Drinks and Establishment of Aseptic Workshop

2023

Food Environ Virol

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Materials discovery of ion-selective membranes using artificial intelligence

et al. 2022

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Significant attempts have been made to improve the production of ion-selective membranes (ISMs) with higher efficiency and lower prices, while the traditional methods have drawbacks of limitations, high cost of experiments, and time-consuming computations. One of the best approaches to remove the experimental limitations is artificial intelligence (AI). This review discusses the role of AI in materials discovery and ISMs engineering. The AI can minimize the need for experimental tests by data analysis to accelerate computational methods based on models using the results of ISMs simulations. The coupling with computational chemistry makes it possible for the AI to consider atomic features in the output models since AI acts as a bridge between the experimental data and computational chemistry to develop models that can use experimental data and atomic properties. This hybrid method can be used in materials discovery of the membranes for ion extraction to investigate capabilities, challenges, and future perspectives of the AI-based materials discovery, which can pave the path for ISMs engineering.

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Artificial Intelligence Model for Forecasting of Membrane Fouling in Wastewater Treatment by Membrane Technology

Cited by 2 publications

References 63 publications

Application of Membrane Filtration to Cold Sterilization of Drinks and Establishment of Aseptic Workshop

Application of Membrane Filtration to Cold Sterilization of Drinks and Establishment of Aseptic Workshop

Materials discovery of ion-selective membranes using artificial intelligence

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