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Practical Prediction of Gas Separation Performance in Polymeric Membranes Using Machine Learning.

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Title: Practical Prediction of Gas Separation Performance in Polymeric Membranes Using Machine Learning.
Authors: Zentou H; Interdisciplinary Research Center for Hydrogen Technologies and Carbon Management (IRC-HTCM), King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia., Issa MA; Department of Oil and Gas Economics, College of Administrative and Financial Sciences, Imam Ja'afar Al-Sadiq University, Baghdad, Iraq., Alshareef BS; Advanced Membranes & Porous Materials (AMPM) Centre, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia., Abdelnaby MM; Interdisciplinary Research Center for Hydrogen Technologies and Carbon Management (IRC-HTCM), King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia.
Source: Chemistry, an Asian journal [Chem Asian J] 2026 Feb; Vol. 21 (4), pp. e70645.
Publication Type: Journal Article
Journal Info: Publisher: Wiley-VCH Country of Publication: Germany NLM ID: 101294643 Publication Model: Print Cited Medium: Internet ISSN: 1861-471X (Electronic) Linking ISSN: 1861471X NLM ISO Abbreviation: Chem Asian J Subsets: MEDLINE; PubMed not MEDLINE
Database: MEDLINE Ultimate
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PubType: Academic Journal
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  Data: Practical Prediction of Gas Separation Performance in Polymeric Membranes Using Machine Learning.
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  Data: <searchLink fieldCode="AU" term="%22Zentou+H%22">Zentou H</searchLink>; Interdisciplinary Research Center for Hydrogen Technologies and Carbon Management (IRC-HTCM), King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia.<br /><searchLink fieldCode="AU" term="%22Issa+MA%22">Issa MA</searchLink>; Department of Oil and Gas Economics, College of Administrative and Financial Sciences, Imam Ja'afar Al-Sadiq University, Baghdad, Iraq.<br /><searchLink fieldCode="AU" term="%22Alshareef+BS%22">Alshareef BS</searchLink>; Advanced Membranes & Porous Materials (AMPM) Centre, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.<br /><searchLink fieldCode="AU" term="%22Abdelnaby+MM%22">Abdelnaby MM</searchLink>; Interdisciplinary Research Center for Hydrogen Technologies and Carbon Management (IRC-HTCM), King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Wiley-VCH%22">Wiley-VCH </searchLink><i>Country of Publication: </i>Germany <i>NLM ID: </i>101294643 <i>Publication Model: </i>Print <i>Cited Medium: </i>Internet <i>ISSN: </i>1861-471X (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%221861471X%22">1861471X </searchLink><i>NLM ISO Abbreviation: </i>Chem Asian J <i>Subsets: </i>MEDLINE; PubMed not MEDLINE
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        Value: 10.1002/asia.70645
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      – Code: eng
        Text: English
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        StartPage: e70645
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      – TitleFull: Practical Prediction of Gas Separation Performance in Polymeric Membranes Using Machine Learning.
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            NameFull: Zentou H
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            NameFull: Issa MA
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            NameFull: Alshareef BS
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            – D: 01
              M: 02
              Text: 2026 Feb
              Type: published
              Y: 2026
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            – TitleFull: Chemistry, an Asian journal
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