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Machine learning-driven multi-objective optimization of electrospun nanofibrous membranes design for membrane distillation.

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Title: Machine learning-driven multi-objective optimization of electrospun nanofibrous membranes design for membrane distillation.
Authors: Li X; School of Energy and Environment, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong SAR, China., Yan KQ; Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, China., Wei X; School of Energy and Environment, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong SAR, China., Li M; Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, China., Sun J; Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, China., Bi Y; Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, China., Shao L; MIIT Key Laboratory of Critical Materials Technology for New Energy Conversion and Storage, State Key Laboratory of Urban-Rural Water Resource and Environment, School of Chemistry and Chemical Engineering, Harbin Institute of Technology, Harbin, 150001, China., Gao H; Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, China. Electronic address: hanyugao@ust.hk., An AK; Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, China. Electronic address: alicia.kjan@ust.hk.
Source: Water research [Water Res] 2026 Aug 15; Vol. 301, pp. 126093. Date of Electronic Publication: 2026 May 09.
Publication Type: Journal Article
Journal Info: Publisher: Pergamon Press Country of Publication: England NLM ID: 0105072 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-2448 (Electronic) Linking ISSN: 00431354 NLM ISO Abbreviation: Water Res Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Machine learning-driven multi-objective optimization of electrospun nanofibrous membranes design for membrane distillation.
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  Data: <searchLink fieldCode="AU" term="%22Li+X%22">Li X</searchLink>; School of Energy and Environment, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong SAR, China.<br /><searchLink fieldCode="AU" term="%22Yan+KQ%22">Yan KQ</searchLink>; Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, China.<br /><searchLink fieldCode="AU" term="%22Wei+X%22">Wei X</searchLink>; School of Energy and Environment, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong SAR, China.<br /><searchLink fieldCode="AU" term="%22Li+M%22">Li M</searchLink>; Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, China.<br /><searchLink fieldCode="AU" term="%22Sun+J%22">Sun J</searchLink>; Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, China.<br /><searchLink fieldCode="AU" term="%22Bi+Y%22">Bi Y</searchLink>; Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, China.<br /><searchLink fieldCode="AU" term="%22Shao+L%22">Shao L</searchLink>; MIIT Key Laboratory of Critical Materials Technology for New Energy Conversion and Storage, State Key Laboratory of Urban-Rural Water Resource and Environment, School of Chemistry and Chemical Engineering, Harbin Institute of Technology, Harbin, 150001, China.<br /><searchLink fieldCode="AU" term="%22Gao+H%22">Gao H</searchLink>; Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, China. Electronic address: hanyugao@ust.hk.<br /><searchLink fieldCode="AU" term="%22An+AK%22">An AK</searchLink>; Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, China. Electronic address: alicia.kjan@ust.hk.
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  Data: <searchLink fieldCode="JN" term="%220105072%22">Water research</searchLink> [Water Res] 2026 Aug 15; Vol. 301, pp. 126093. <i>Date of Electronic Publication: </i>2026 May 09.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Pergamon+Press%22">Pergamon Press </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>0105072 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1879-2448 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2200431354%22">00431354 </searchLink><i>NLM ISO Abbreviation: </i>Water Res <i>Subsets: </i>MEDLINE
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        Value: 10.1016/j.watres.2026.126093
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        Text: English
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              Text: 2026 Aug 15
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