An Iterative Method for the Simulation of Rice Straw-Based Polyol Hydroxyl Moieties
Bio-derived polyol products have gained global interest as a green and sustainable substitute for fossil-based polyols in a diverse range of polyurethane (PU) applications. According to previous studies, PU properties are highly influenced by the reaction kinetics during their formation. One major f...
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creator | Dingcong, Roger G. Radjac, Daryl B. Alfeche, Fortia Louise Adeliene M. Dizon, Arniel Ching O. Tejas, Kassandra Jayza Gift D. Malaluan, Roberto M. Al-Moameri, Harith H. Dumancas, Gerard G. Alguno, Arnold C. Lubguban, Arnold A. |
description | Bio-derived polyol products have gained global interest as a green and sustainable substitute for fossil-based polyols in a diverse range of polyurethane (PU) applications. According to previous studies, PU properties are highly influenced by the reaction kinetics during their formation. One major factor affecting this is the reactivity of their polyol’s functional hydroxyl moieties that are classified as primary, secondary, and hindered-secondary. However, experimental quantitative characterization of these polyol hydroxyl moieties remains a challenge in the field due to various factors affecting them, including extensive time requirements, the need for substantial and expensive resources, large potential errors, and the generation of wastes, as well as health and safety considerations. In this study, the molar fraction of primary, secondary, and hindered-secondary hydroxyl moieties of a petroleum-based polyol (V490) and a rice straw-based polyol were determined via an iterative computational method. The method employed a MATLAB script that can simultaneously solve multiple differential equations involving PU gelling reaction kinetics and thermodynamics. In this manner, numerical combinations of the fraction of each type of hydroxyl moiety are generated by looping together the respective numerical fractions for each moiety. The best-fit combinations of the fractions of the mixed polyol’s hydroxyl moieties were successfully found via curve fitting of the simulated and experimental gelling temperature profile with an average numerical deviation of less than 1%. Thus, the method presented in this study offers a faster and more reliable characterization of the polymeric reaction kinetics than the experimental and conventional computational methods for product property enhancement and development in the field. |
doi_str_mv | 10.3390/su151512082 |
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According to previous studies, PU properties are highly influenced by the reaction kinetics during their formation. One major factor affecting this is the reactivity of their polyol’s functional hydroxyl moieties that are classified as primary, secondary, and hindered-secondary. However, experimental quantitative characterization of these polyol hydroxyl moieties remains a challenge in the field due to various factors affecting them, including extensive time requirements, the need for substantial and expensive resources, large potential errors, and the generation of wastes, as well as health and safety considerations. In this study, the molar fraction of primary, secondary, and hindered-secondary hydroxyl moieties of a petroleum-based polyol (V490) and a rice straw-based polyol were determined via an iterative computational method. The method employed a MATLAB script that can simultaneously solve multiple differential equations involving PU gelling reaction kinetics and thermodynamics. In this manner, numerical combinations of the fraction of each type of hydroxyl moiety are generated by looping together the respective numerical fractions for each moiety. The best-fit combinations of the fractions of the mixed polyol’s hydroxyl moieties were successfully found via curve fitting of the simulated and experimental gelling temperature profile with an average numerical deviation of less than 1%. Thus, the method presented in this study offers a faster and more reliable characterization of the polymeric reaction kinetics than the experimental and conventional computational methods for product property enhancement and development in the field.</description><identifier>ISSN: 2071-1050</identifier><identifier>EISSN: 2071-1050</identifier><identifier>DOI: 10.3390/su151512082</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Cellulose ; Chemical reaction, Rate of ; Heat ; Hydroxides ; Kinetics ; Lignin ; Lignocellulose ; Manufacturing ; Methods ; Polyols ; Polyurethanes ; Simulation methods ; Sustainability ; Technology application</subject><ispartof>Sustainability, 2023-08, Vol.15 (15), p.12082</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c371t-6c5322d00874f28b10bafa36f25cda9db79c2a326430952d7aea50d69389c7093</citedby><cites>FETCH-LOGICAL-c371t-6c5322d00874f28b10bafa36f25cda9db79c2a326430952d7aea50d69389c7093</cites><orcidid>0000-0002-1858-9250 ; 0000-0002-7076-0078 ; 0000-0002-6402-6184 ; 0009-0000-1152-6284 ; 0000-0001-6077-8234 ; 0000-0002-8161-4148 ; 0000-0001-5985-0235</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Dingcong, Roger G.</creatorcontrib><creatorcontrib>Radjac, Daryl B.</creatorcontrib><creatorcontrib>Alfeche, Fortia Louise Adeliene M.</creatorcontrib><creatorcontrib>Dizon, Arniel Ching O.</creatorcontrib><creatorcontrib>Tejas, Kassandra Jayza Gift D.</creatorcontrib><creatorcontrib>Malaluan, Roberto M.</creatorcontrib><creatorcontrib>Al-Moameri, Harith H.</creatorcontrib><creatorcontrib>Dumancas, Gerard G.</creatorcontrib><creatorcontrib>Alguno, Arnold C.</creatorcontrib><creatorcontrib>Lubguban, Arnold A.</creatorcontrib><title>An Iterative Method for the Simulation of Rice Straw-Based Polyol Hydroxyl Moieties</title><title>Sustainability</title><description>Bio-derived polyol products have gained global interest as a green and sustainable substitute for fossil-based polyols in a diverse range of polyurethane (PU) applications. 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The method employed a MATLAB script that can simultaneously solve multiple differential equations involving PU gelling reaction kinetics and thermodynamics. In this manner, numerical combinations of the fraction of each type of hydroxyl moiety are generated by looping together the respective numerical fractions for each moiety. The best-fit combinations of the fractions of the mixed polyol’s hydroxyl moieties were successfully found via curve fitting of the simulated and experimental gelling temperature profile with an average numerical deviation of less than 1%. Thus, the method presented in this study offers a faster and more reliable characterization of the polymeric reaction kinetics than the experimental and conventional computational methods for product property enhancement and development in the field.</description><subject>Cellulose</subject><subject>Chemical reaction, Rate of</subject><subject>Heat</subject><subject>Hydroxides</subject><subject>Kinetics</subject><subject>Lignin</subject><subject>Lignocellulose</subject><subject>Manufacturing</subject><subject>Methods</subject><subject>Polyols</subject><subject>Polyurethanes</subject><subject>Simulation methods</subject><subject>Sustainability</subject><subject>Technology application</subject><issn>2071-1050</issn><issn>2071-1050</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNpVkU1PwzAMhisEEtPYiT8QiRNCBSdZm-Y4ELBJm0AbnKssH1umrhlJCuzfEzQOwz7Ysp_XluUsu8RwSymHu9DhIjmBipxkPQIM5xgKOD3Kz7NBCBtIRinmuOxli1GLJlF7Ee2nRjMd104h4zyKa40Wdts1qeNa5AyaW5lK0Yuv_F4ErdCra_auQeO98u5736CZszpaHS6yMyOaoAd_sZ-9Pz2-PYzz6cvz5GE0zSVlOOalLCghCqBiQ0OqJYalMIKWhhRSCa6WjEsiKCmHFHhBFBNaFKBKTisuGXDaz64Oc3fefXQ6xHrjOt-mlTWphhw44QwSdXugVqLRtW2NSyfI5EpvrXStNjbVR6yEEjNGSRJc_xMkJurvuBJdCPVkMf_P3hxY6V0IXpt65-1W-H2Nof79Sn30FfoDBVp8UA</recordid><startdate>20230801</startdate><enddate>20230801</enddate><creator>Dingcong, Roger G.</creator><creator>Radjac, Daryl B.</creator><creator>Alfeche, Fortia Louise Adeliene M.</creator><creator>Dizon, Arniel Ching O.</creator><creator>Tejas, Kassandra Jayza Gift D.</creator><creator>Malaluan, Roberto M.</creator><creator>Al-Moameri, Harith H.</creator><creator>Dumancas, Gerard G.</creator><creator>Alguno, Arnold C.</creator><creator>Lubguban, Arnold A.</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>ISR</scope><scope>4U-</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><orcidid>https://orcid.org/0000-0002-1858-9250</orcidid><orcidid>https://orcid.org/0000-0002-7076-0078</orcidid><orcidid>https://orcid.org/0000-0002-6402-6184</orcidid><orcidid>https://orcid.org/0009-0000-1152-6284</orcidid><orcidid>https://orcid.org/0000-0001-6077-8234</orcidid><orcidid>https://orcid.org/0000-0002-8161-4148</orcidid><orcidid>https://orcid.org/0000-0001-5985-0235</orcidid></search><sort><creationdate>20230801</creationdate><title>An Iterative Method for the Simulation of Rice Straw-Based Polyol Hydroxyl Moieties</title><author>Dingcong, Roger G. ; Radjac, Daryl B. ; Alfeche, Fortia Louise Adeliene M. ; Dizon, Arniel Ching O. ; Tejas, Kassandra Jayza Gift D. ; Malaluan, Roberto M. ; Al-Moameri, Harith H. ; Dumancas, Gerard G. ; Alguno, Arnold C. ; Lubguban, Arnold A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c371t-6c5322d00874f28b10bafa36f25cda9db79c2a326430952d7aea50d69389c7093</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Cellulose</topic><topic>Chemical reaction, Rate of</topic><topic>Heat</topic><topic>Hydroxides</topic><topic>Kinetics</topic><topic>Lignin</topic><topic>Lignocellulose</topic><topic>Manufacturing</topic><topic>Methods</topic><topic>Polyols</topic><topic>Polyurethanes</topic><topic>Simulation methods</topic><topic>Sustainability</topic><topic>Technology application</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dingcong, Roger G.</creatorcontrib><creatorcontrib>Radjac, Daryl B.</creatorcontrib><creatorcontrib>Alfeche, Fortia Louise Adeliene M.</creatorcontrib><creatorcontrib>Dizon, Arniel Ching O.</creatorcontrib><creatorcontrib>Tejas, Kassandra Jayza Gift D.</creatorcontrib><creatorcontrib>Malaluan, Roberto M.</creatorcontrib><creatorcontrib>Al-Moameri, Harith H.</creatorcontrib><creatorcontrib>Dumancas, Gerard G.</creatorcontrib><creatorcontrib>Alguno, Arnold C.</creatorcontrib><creatorcontrib>Lubguban, Arnold A.</creatorcontrib><collection>CrossRef</collection><collection>Gale In Context: Science</collection><collection>University Readers</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><jtitle>Sustainability</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dingcong, Roger G.</au><au>Radjac, Daryl B.</au><au>Alfeche, Fortia Louise Adeliene M.</au><au>Dizon, Arniel Ching O.</au><au>Tejas, Kassandra Jayza Gift D.</au><au>Malaluan, Roberto M.</au><au>Al-Moameri, Harith H.</au><au>Dumancas, Gerard G.</au><au>Alguno, Arnold C.</au><au>Lubguban, Arnold A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An Iterative Method for the Simulation of Rice Straw-Based Polyol Hydroxyl Moieties</atitle><jtitle>Sustainability</jtitle><date>2023-08-01</date><risdate>2023</risdate><volume>15</volume><issue>15</issue><spage>12082</spage><pages>12082-</pages><issn>2071-1050</issn><eissn>2071-1050</eissn><abstract>Bio-derived polyol products have gained global interest as a green and sustainable substitute for fossil-based polyols in a diverse range of polyurethane (PU) applications. According to previous studies, PU properties are highly influenced by the reaction kinetics during their formation. One major factor affecting this is the reactivity of their polyol’s functional hydroxyl moieties that are classified as primary, secondary, and hindered-secondary. However, experimental quantitative characterization of these polyol hydroxyl moieties remains a challenge in the field due to various factors affecting them, including extensive time requirements, the need for substantial and expensive resources, large potential errors, and the generation of wastes, as well as health and safety considerations. In this study, the molar fraction of primary, secondary, and hindered-secondary hydroxyl moieties of a petroleum-based polyol (V490) and a rice straw-based polyol were determined via an iterative computational method. The method employed a MATLAB script that can simultaneously solve multiple differential equations involving PU gelling reaction kinetics and thermodynamics. In this manner, numerical combinations of the fraction of each type of hydroxyl moiety are generated by looping together the respective numerical fractions for each moiety. The best-fit combinations of the fractions of the mixed polyol’s hydroxyl moieties were successfully found via curve fitting of the simulated and experimental gelling temperature profile with an average numerical deviation of less than 1%. 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subjects | Cellulose Chemical reaction, Rate of Heat Hydroxides Kinetics Lignin Lignocellulose Manufacturing Methods Polyols Polyurethanes Simulation methods Sustainability Technology application |
title | An Iterative Method for the Simulation of Rice Straw-Based Polyol Hydroxyl Moieties |
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