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Developing (Quantitative Structure Property Relationships) QSPR Techniques to Predict the Char Formation of Polybenzoxazines

This study uses the Molecular Operating Environment software (MOE) to generate models to calculate the char yield of polybenzoxazines (PBz). A series of benzoxazine (Bz) monomers were constructed to which a variety of parameters relating to the structure (e.g., water accessible surface, negative van...

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Detalles Bibliográficos
Autores principales: Sairi, Maryam, Howlin, Brendan, Hamerton, Ian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6431917/
https://www.ncbi.nlm.nih.gov/pubmed/30979257
http://dx.doi.org/10.3390/polym8050166
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author Sairi, Maryam
Howlin, Brendan
Hamerton, Ian
author_facet Sairi, Maryam
Howlin, Brendan
Hamerton, Ian
author_sort Sairi, Maryam
collection PubMed
description This study uses the Molecular Operating Environment software (MOE) to generate models to calculate the char yield of polybenzoxazines (PBz). A series of benzoxazine (Bz) monomers were constructed to which a variety of parameters relating to the structure (e.g., water accessible surface, negative van der Waals surface area and hydrophobic volume, etc.) were obtained and a quantitative structure property relationships (QSPR) model was generated. The model was used to generate data for new Bz monomers with desired properties and a comparison was made of predictions based on the QSPR model with the experimental data. This study shows the quality of predictive models and confirms how useful computational screening is prior to synthesis.
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spelling pubmed-64319172019-04-02 Developing (Quantitative Structure Property Relationships) QSPR Techniques to Predict the Char Formation of Polybenzoxazines Sairi, Maryam Howlin, Brendan Hamerton, Ian Polymers (Basel) Article This study uses the Molecular Operating Environment software (MOE) to generate models to calculate the char yield of polybenzoxazines (PBz). A series of benzoxazine (Bz) monomers were constructed to which a variety of parameters relating to the structure (e.g., water accessible surface, negative van der Waals surface area and hydrophobic volume, etc.) were obtained and a quantitative structure property relationships (QSPR) model was generated. The model was used to generate data for new Bz monomers with desired properties and a comparison was made of predictions based on the QSPR model with the experimental data. This study shows the quality of predictive models and confirms how useful computational screening is prior to synthesis. MDPI 2016-04-25 /pmc/articles/PMC6431917/ /pubmed/30979257 http://dx.doi.org/10.3390/polym8050166 Text en © 2016 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Sairi, Maryam
Howlin, Brendan
Hamerton, Ian
Developing (Quantitative Structure Property Relationships) QSPR Techniques to Predict the Char Formation of Polybenzoxazines
title Developing (Quantitative Structure Property Relationships) QSPR Techniques to Predict the Char Formation of Polybenzoxazines
title_full Developing (Quantitative Structure Property Relationships) QSPR Techniques to Predict the Char Formation of Polybenzoxazines
title_fullStr Developing (Quantitative Structure Property Relationships) QSPR Techniques to Predict the Char Formation of Polybenzoxazines
title_full_unstemmed Developing (Quantitative Structure Property Relationships) QSPR Techniques to Predict the Char Formation of Polybenzoxazines
title_short Developing (Quantitative Structure Property Relationships) QSPR Techniques to Predict the Char Formation of Polybenzoxazines
title_sort developing (quantitative structure property relationships) qspr techniques to predict the char formation of polybenzoxazines
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6431917/
https://www.ncbi.nlm.nih.gov/pubmed/30979257
http://dx.doi.org/10.3390/polym8050166
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