{"title":"基团贡献法提高了深共晶溶剂玻璃化转变温度的相关性","authors":"Sakshi S. Tak, Debashis Kundu","doi":"10.1016/j.ctta.2023.100108","DOIUrl":null,"url":null,"abstract":"<div><p>Glass transition temperature (<em>T<sub>g</sub></em>) being a crucial thermal property, linear models for predicting <em>T<sub>g</sub></em> of deep eutectic solvents (DES) are proposed. The group contribution method and genetic algorithm using an experimental dataset of 51 DESs are applied to obtain the group contribution values for each functional group present in DESs by considering their stereochemistry. By segregating the DESs into subclasses according to their molecular structures, linear regressions for each class are performed to develop the model. The framework is used to compute the <em>T<sub>g</sub></em> of all DESs taken in this study, and it shows an absolute average deviation of 2.7%.</p></div>","PeriodicalId":9781,"journal":{"name":"Chemical Thermodynamics and Thermal Analysis","volume":"9 ","pages":"Article 100108"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Group contribution method promoted correlations of glass transition temperature of deep eutectic solvents\",\"authors\":\"Sakshi S. Tak, Debashis Kundu\",\"doi\":\"10.1016/j.ctta.2023.100108\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Glass transition temperature (<em>T<sub>g</sub></em>) being a crucial thermal property, linear models for predicting <em>T<sub>g</sub></em> of deep eutectic solvents (DES) are proposed. The group contribution method and genetic algorithm using an experimental dataset of 51 DESs are applied to obtain the group contribution values for each functional group present in DESs by considering their stereochemistry. By segregating the DESs into subclasses according to their molecular structures, linear regressions for each class are performed to develop the model. The framework is used to compute the <em>T<sub>g</sub></em> of all DESs taken in this study, and it shows an absolute average deviation of 2.7%.</p></div>\",\"PeriodicalId\":9781,\"journal\":{\"name\":\"Chemical Thermodynamics and Thermal Analysis\",\"volume\":\"9 \",\"pages\":\"Article 100108\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Chemical Thermodynamics and Thermal Analysis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2667312623000056\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chemical Thermodynamics and Thermal Analysis","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2667312623000056","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Group contribution method promoted correlations of glass transition temperature of deep eutectic solvents
Glass transition temperature (Tg) being a crucial thermal property, linear models for predicting Tg of deep eutectic solvents (DES) are proposed. The group contribution method and genetic algorithm using an experimental dataset of 51 DESs are applied to obtain the group contribution values for each functional group present in DESs by considering their stereochemistry. By segregating the DESs into subclasses according to their molecular structures, linear regressions for each class are performed to develop the model. The framework is used to compute the Tg of all DESs taken in this study, and it shows an absolute average deviation of 2.7%.
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