Predicting glass transition temperatures of polyarylethersulphones using QSPR methods
The technique of Quantitative Structure Property Relationships has been applied to the glass transition temperatures of polyarylethersulphones. A general equation is reported that calculates the glass transition temperatures with acceptable accuracy (correlation coefficients of between 90-67%, indic...
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| Veröffentlicht in: | PloS one 2012-06, Vol.7 (6), p.e38424-e38424 |
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| creator | Hamerton, Ian Howlin, Brendan J Kamyszek, Grzegorz |
| description | The technique of Quantitative Structure Property Relationships has been applied to the glass transition temperatures of polyarylethersulphones. A general equation is reported that calculates the glass transition temperatures with acceptable accuracy (correlation coefficients of between 90-67%, indicating an error of 10-30% with regard to experimentally determined values) for a series of 42 reported polyarylethersulphones. This method is quite simple in assumption and relies on a relatively small number of parameters associated with the structural unit of the polymer: the number of rotatable bonds, the dipole moment, the heat of formation, the HOMO eigenvalue, the molar mass and molar volume. For smaller subsets of the main group (based on families of derivatives containing different substituents) the model can be simplified further to an equation that uses the volume of the substituents as the principal variable. |
| doi_str_mv | 10.1371/journal.pone.0038424 |
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A general equation is reported that calculates the glass transition temperatures with acceptable accuracy (correlation coefficients of between 90-67%, indicating an error of 10-30% with regard to experimentally determined values) for a series of 42 reported polyarylethersulphones. This method is quite simple in assumption and relies on a relatively small number of parameters associated with the structural unit of the polymer: the number of rotatable bonds, the dipole moment, the heat of formation, the HOMO eigenvalue, the molar mass and molar volume. For smaller subsets of the main group (based on families of derivatives containing different substituents) the model can be simplified further to an equation that uses the volume of the substituents as the principal variable.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0038424</identifier><identifier>PMID: 22719884</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Analysis ; Chemistry ; Correlation coefficient ; Correlation coefficients ; Dipole moments ; Glass ; Glass transition temperature ; Heat of formation ; Materials Science ; Mechanical properties ; Methods ; Molar volume ; Molecular weight ; Performance evaluation ; Polymer blends ; Polymers ; Quantitative Structure-Activity Relationship ; Temperature ; Transition temperatures ; Weather forecasting</subject><ispartof>PloS one, 2012-06, Vol.7 (6), p.e38424-e38424</ispartof><rights>COPYRIGHT 2012 Public Library of Science</rights><rights>2012 Howlin et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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A general equation is reported that calculates the glass transition temperatures with acceptable accuracy (correlation coefficients of between 90-67%, indicating an error of 10-30% with regard to experimentally determined values) for a series of 42 reported polyarylethersulphones. This method is quite simple in assumption and relies on a relatively small number of parameters associated with the structural unit of the polymer: the number of rotatable bonds, the dipole moment, the heat of formation, the HOMO eigenvalue, the molar mass and molar volume. For smaller subsets of the main group (based on families of derivatives containing different substituents) the model can be simplified further to an equation that uses the volume of the substituents as the principal variable.</description><subject>Analysis</subject><subject>Chemistry</subject><subject>Correlation coefficient</subject><subject>Correlation coefficients</subject><subject>Dipole moments</subject><subject>Glass</subject><subject>Glass transition temperature</subject><subject>Heat of formation</subject><subject>Materials Science</subject><subject>Mechanical properties</subject><subject>Methods</subject><subject>Molar volume</subject><subject>Molecular weight</subject><subject>Performance evaluation</subject><subject>Polymer blends</subject><subject>Polymers</subject><subject>Quantitative Structure-Activity Relationship</subject><subject>Temperature</subject><subject>Transition temperatures</subject><subject>Weather 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A general equation is reported that calculates the glass transition temperatures with acceptable accuracy (correlation coefficients of between 90-67%, indicating an error of 10-30% with regard to experimentally determined values) for a series of 42 reported polyarylethersulphones. This method is quite simple in assumption and relies on a relatively small number of parameters associated with the structural unit of the polymer: the number of rotatable bonds, the dipole moment, the heat of formation, the HOMO eigenvalue, the molar mass and molar volume. For smaller subsets of the main group (based on families of derivatives containing different substituents) the model can be simplified further to an equation that uses the volume of the substituents as the principal variable.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>22719884</pmid><doi>10.1371/journal.pone.0038424</doi><tpages>e38424</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Analysis Chemistry Correlation coefficient Correlation coefficients Dipole moments Glass Glass transition temperature Heat of formation Materials Science Mechanical properties Methods Molar volume Molecular weight Performance evaluation Polymer blends Polymers Quantitative Structure-Activity Relationship Temperature Transition temperatures Weather forecasting |
| title | Predicting glass transition temperatures of polyarylethersulphones using QSPR methods |
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