Performance assessment and optimization of forward osmosis–low pressure ultrafiltration hybrid system using machine learning for rhodamine B removal-Reference-Cited by-同舟云学术

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Performance assessment and optimization of forward osmosis–low pressure ultrafiltration hybrid system using machine learning for rhodamine B removal

Published:2022-12 Issue: Volume:543 Page:116102
ISSN:0011-9164
Container-title:Desalination
language:en
Short-container-title:Desalination

Author:

Nam Seong-Nam,Kim Sewoon,Her Namguk,Choong Choe Earn,Jang Min,Park Chang Min,Heo Jiyong,Yoon Yeomin

Funder

Ministry of Science and Technology

National Research Foundation of Korea

Ministry of Science, ICT and Future Planning

Publisher

Elsevier BV

Subject

Mechanical Engineering,Water Science and Technology,General Materials Science,General Chemical Engineering,General Chemistry

Reference52 articles.

1. A critical review on the treatment of dye-containing wastewater: ecotoxicological and health concerns of textile dyes and possible remediation approaches for environmental safety;Al-Tohamy;Ecotoxicol. Environ. Saf.,2022

2. Treatment of highly concentrated dye solution by coagulation/flocculation–sand filtration and nanofiltration;Zahrim;Water Resour. Ind.,2013

3. Treatment of an azo dye effluent by peroxi-coagulation and its comparison to traditional electrochemical advanced processes;do Vale-Júnior;Chemosphere,2018

4. Adsorption of rhodamine B dye from aqueous solution onto acid treated banana peel: response surface methodology, kinetics and isotherm studies;Oyekanmi;PLoS One,2019

5. Liquid phase adsorptions of rhodamine B dye onto raw and chitosan supported mesoporous adsorbents: isotherms and kinetics studies;Inyinbor;Appl Water Sci,2017

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1. Bibliometric analysis of artificial intelligence in wastewater treatment: Current status, research progress, and future prospects;Journal of Environmental Chemical Engineering;2024-08

2. In-Situ Hydrothermal Fabrication of ZnO-Loaded GAC Nanocomposite for Efficient Rhodamine B Dye Removal via Synergistic Photocatalytic and Adsorptive Performance;Nanomaterials;2024-07-22

3. Artificial intelligence applications in forward osmosis for water treatment: Recent developments and research directions;Desalination and Water Treatment;2024-07

4. Accurate Prediction of Reverse Solute Flux in Forward Osmosis Systems Using Comparative Machine Learning Models;Arabian Journal for Science and Engineering;2024-07-01

5. Artificial neural network and response surface methodology for modeling reverse osmosis process in wastewater treatment;Journal of Industrial and Engineering Chemistry;2024-05

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