Prediction of the Glass-Transition Temperatures of Linear Homo/Heteropolymers and Cross-Linked Epoxy Resins
Chisa Higuchi, Dragos Horvath, Gilles Marcou, Kazunari Yoshizawa, Alexandre Varnek
Department of Fundamental Organic Chemistry
This work proposes a unified approach to predict glass-transition temperatures (Tg) of linear homo/heteropolymers and cross-linked epoxy resins by machine-learning approaches based on descriptors of reagents undergoing polymerization, represented in a formal way such as to encompass all three scenarios: linear homo- and heteropolymers plus network heteropolymers. The "formal"representation of reagents is a problem-specific, herein designed standardization protocol of compounds, unlike typical structure curation rules in chemoinformatics. For example, heteropolymers are represented by the two partner reagents, whereas homopolymers are depicted as formal "heteropolymers"with identical partners. The key rule proposed here is to choose "formal"monomers such as to minimize the number of marked atoms, involved in bonds being formed or changing bond order. Accordingly, carbonyl compounds are rendered as the less-stable vinyl alcohol tautomer, following the same formalism as in olefin polymerization, to minimize the total number of formal polymerization mechanisms and herewith provide the most general framework encompassing a maximum of polymerization processes. ISIDA (in silico design and data analysis) fragment counts with special status given to the "marked atoms"participating in the polymerization process were combined using "mixture"strategies to generate the final polymer descriptors. Three predictive models based on SVR (support vector regression) are discussed here. After reproducing results of Katritzky et al. with a local model applicable only to linear homo/heteropolymers, an epoxy resin-specific model applicable to both linear and network forms was built. Eventually, the general model applicable to all these families was constructed. In 12 × repeated 3-fold cross-validation challenges, it displayed the highest accuracy of Q2 = 0.920, RMSE = 34.3 K over the training set of 270 polymers, and R2 = 0.779, RMSE 35.9 K for an external test set of 119 polymers. GTM (Generative Topographic Mapping) analysis produced a 2D map of "polymer chemical space", highlighting the various classes of polymers included in the study and their relationship with respect to Tg values. The epoxy-specific and general models are publicly available on our web server: http://infochim.u-strasbg.fr/webserv/VSEngine.html.
ACS Applied Polymer Materials
https://doi.org/10.1021/acsapm.9b00198
Process Chemistry and Technology
10.1021/acsapm.9b00198
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Polymer Chemistry 100%
Polymerization Biochemistry, Genetics and Molecular Biology 100%
Simulation Mode Computer Science 80%
Polymerization Reaction Chemistry 60%
Chemical Reaction Reagent Chemistry 60%
Epoxy Resin Chemistry 60%
Atom Chemistry 40%
Number Chemistry 40%
Higuchi, C., Horvath, D., Marcou, G., Yoshizawa, K., & Varnek, A. (2019). Prediction of the Glass-Transition Temperatures of Linear Homo/Heteropolymers and Cross-Linked Epoxy Resins. ACS Applied Polymer Materials, 1(6), 1430-1442. https://doi.org/10.1021/acsapm.9b00198
Prediction of the Glass-Transition Temperatures of Linear Homo/Heteropolymers and Cross-Linked Epoxy Resins. / Higuchi, Chisa; Horvath, Dragos; Marcou, Gilles et al.
In: ACS Applied Polymer Materials, Vol. 1, No. 6, 14.06.2019, p. 1430-1442.
Higuchi, C, Horvath, D, Marcou, G, Yoshizawa, K & Varnek, A 2019, 'Prediction of the Glass-Transition Temperatures of Linear Homo/Heteropolymers and Cross-Linked Epoxy Resins', ACS Applied Polymer Materials, vol. 1, no. 6, pp. 1430-1442. https://doi.org/10.1021/acsapm.9b00198
Higuchi C, Horvath D, Marcou G, Yoshizawa K, Varnek A. Prediction of the Glass-Transition Temperatures of Linear Homo/Heteropolymers and Cross-Linked Epoxy Resins. ACS Applied Polymer Materials. 2019 Jun 14;1(6):1430-1442. doi: 10.1021/acsapm.9b00198
Higuchi, Chisa ; Horvath, Dragos ; Marcou, Gilles et al. / Prediction of the Glass-Transition Temperatures of Linear Homo/Heteropolymers and Cross-Linked Epoxy Resins. In: ACS Applied Polymer Materials. 2019 ; Vol. 1, No. 6. pp. 1430-1442.
@article{7fa58b14f77f42c8a045d79062a5330c,
title = "Prediction of the Glass-Transition Temperatures of Linear Homo/Heteropolymers and Cross-Linked Epoxy Resins",
abstract = "This work proposes a unified approach to predict glass-transition temperatures (Tg) of linear homo/heteropolymers and cross-linked epoxy resins by machine-learning approaches based on descriptors of reagents undergoing polymerization, represented in a formal way such as to encompass all three scenarios: linear homo- and heteropolymers plus network heteropolymers. The {"}formal{"}representation of reagents is a problem-specific, herein designed standardization protocol of compounds, unlike typical structure curation rules in chemoinformatics. For example, heteropolymers are represented by the two partner reagents, whereas homopolymers are depicted as formal {"}heteropolymers{"}with identical partners. The key rule proposed here is to choose {"}formal{"}monomers such as to minimize the number of marked atoms, involved in bonds being formed or changing bond order. Accordingly, carbonyl compounds are rendered as the less-stable vinyl alcohol tautomer, following the same formalism as in olefin polymerization, to minimize the total number of formal polymerization mechanisms and herewith provide the most general framework encompassing a maximum of polymerization processes. ISIDA (in silico design and data analysis) fragment counts with special status given to the {"}marked atoms{"}participating in the polymerization process were combined using {"}mixture{"}strategies to generate the final polymer descriptors. Three predictive models based on SVR (support vector regression) are discussed here. After reproducing results of Katritzky et al. with a local model applicable only to linear homo/heteropolymers, an epoxy resin-specific model applicable to both linear and network forms was built. Eventually, the general model applicable to all these families was constructed. In 12 × repeated 3-fold cross-validation challenges, it displayed the highest accuracy of Q2 = 0.920, RMSE = 34.3 K over the training set of 270 polymers, and R2 = 0.779, RMSE 35.9 K for an external test set of 119 polymers. GTM (Generative Topographic Mapping) analysis produced a 2D map of {"}polymer chemical space{"}, highlighting the various classes of polymers included in the study and their relationship with respect to Tg values. The epoxy-specific and general models are publicly available on our web server: http://infochim.u-strasbg.fr/webserv/VSEngine.html.",
author = "Chisa Higuchi and Dragos Horvath and Gilles Marcou and Kazunari Yoshizawa and Alexandre Varnek",
note = "Funding Information: We thank Dr Fanny Bonachera for the help with GTM calculations. C.H. thanks Kyushu University for supporting her stay at the University of Strasbourg. K.Y. acknowledges KAKENHI Grants JP15K13710 and JP17H03117 from Japan Society for the Promotion of Science (JSPS) and the Ministry of Education, Culture, Sports, Science and Technology of Japan (MEXT), the MEXT Projects of "Integrated Research Consortium on Chemical Sciences," "Cooperative Research Program of Network Joint Research Center for Materials and Devices," "Elements Strategy Initiative to Form Core Research Center," and JST-CREST "Innovative Catalysts." ISIDA GTM software is developed by the Laboratoire de Chemoinformatique Strasbourg and can be obtained upon request (visit http://infochim.u-strasbg.fr/downloads/manuals/Fragmentor2017/Fragmentor2017_Manual_nov2017.pdf ). Publisher Copyright: Copyright {\textcopyright} 2019 American Chemical Society.",
doi = "10.1021/acsapm.9b00198",
journal = "ACS Applied Polymer Materials",
T1 - Prediction of the Glass-Transition Temperatures of Linear Homo/Heteropolymers and Cross-Linked Epoxy Resins
AU - Higuchi, Chisa
AU - Horvath, Dragos
AU - Marcou, Gilles
AU - Yoshizawa, Kazunari
AU - Varnek, Alexandre
N1 - Funding Information: We thank Dr Fanny Bonachera for the help with GTM calculations. C.H. thanks Kyushu University for supporting her stay at the University of Strasbourg. K.Y. acknowledges KAKENHI Grants JP15K13710 and JP17H03117 from Japan Society for the Promotion of Science (JSPS) and the Ministry of Education, Culture, Sports, Science and Technology of Japan (MEXT), the MEXT Projects of "Integrated Research Consortium on Chemical Sciences," "Cooperative Research Program of Network Joint Research Center for Materials and Devices," "Elements Strategy Initiative to Form Core Research Center," and JST-CREST "Innovative Catalysts." ISIDA GTM software is developed by the Laboratoire de Chemoinformatique Strasbourg and can be obtained upon request (visit http://infochim.u-strasbg.fr/downloads/manuals/Fragmentor2017/Fragmentor2017_Manual_nov2017.pdf ). Publisher Copyright: Copyright © 2019 American Chemical Society.
N2 - This work proposes a unified approach to predict glass-transition temperatures (Tg) of linear homo/heteropolymers and cross-linked epoxy resins by machine-learning approaches based on descriptors of reagents undergoing polymerization, represented in a formal way such as to encompass all three scenarios: linear homo- and heteropolymers plus network heteropolymers. The "formal"representation of reagents is a problem-specific, herein designed standardization protocol of compounds, unlike typical structure curation rules in chemoinformatics. For example, heteropolymers are represented by the two partner reagents, whereas homopolymers are depicted as formal "heteropolymers"with identical partners. The key rule proposed here is to choose "formal"monomers such as to minimize the number of marked atoms, involved in bonds being formed or changing bond order. Accordingly, carbonyl compounds are rendered as the less-stable vinyl alcohol tautomer, following the same formalism as in olefin polymerization, to minimize the total number of formal polymerization mechanisms and herewith provide the most general framework encompassing a maximum of polymerization processes. ISIDA (in silico design and data analysis) fragment counts with special status given to the "marked atoms"participating in the polymerization process were combined using "mixture"strategies to generate the final polymer descriptors. Three predictive models based on SVR (support vector regression) are discussed here. After reproducing results of Katritzky et al. with a local model applicable only to linear homo/heteropolymers, an epoxy resin-specific model applicable to both linear and network forms was built. Eventually, the general model applicable to all these families was constructed. In 12 × repeated 3-fold cross-validation challenges, it displayed the highest accuracy of Q2 = 0.920, RMSE = 34.3 K over the training set of 270 polymers, and R2 = 0.779, RMSE 35.9 K for an external test set of 119 polymers. GTM (Generative Topographic Mapping) analysis produced a 2D map of "polymer chemical space", highlighting the various classes of polymers included in the study and their relationship with respect to Tg values. The epoxy-specific and general models are publicly available on our web server: http://infochim.u-strasbg.fr/webserv/VSEngine.html.
AB - This work proposes a unified approach to predict glass-transition temperatures (Tg) of linear homo/heteropolymers and cross-linked epoxy resins by machine-learning approaches based on descriptors of reagents undergoing polymerization, represented in a formal way such as to encompass all three scenarios: linear homo- and heteropolymers plus network heteropolymers. The "formal"representation of reagents is a problem-specific, herein designed standardization protocol of compounds, unlike typical structure curation rules in chemoinformatics. For example, heteropolymers are represented by the two partner reagents, whereas homopolymers are depicted as formal "heteropolymers"with identical partners. The key rule proposed here is to choose "formal"monomers such as to minimize the number of marked atoms, involved in bonds being formed or changing bond order. Accordingly, carbonyl compounds are rendered as the less-stable vinyl alcohol tautomer, following the same formalism as in olefin polymerization, to minimize the total number of formal polymerization mechanisms and herewith provide the most general framework encompassing a maximum of polymerization processes. ISIDA (in silico design and data analysis) fragment counts with special status given to the "marked atoms"participating in the polymerization process were combined using "mixture"strategies to generate the final polymer descriptors. Three predictive models based on SVR (support vector regression) are discussed here. After reproducing results of Katritzky et al. with a local model applicable only to linear homo/heteropolymers, an epoxy resin-specific model applicable to both linear and network forms was built. Eventually, the general model applicable to all these families was constructed. In 12 × repeated 3-fold cross-validation challenges, it displayed the highest accuracy of Q2 = 0.920, RMSE = 34.3 K over the training set of 270 polymers, and R2 = 0.779, RMSE 35.9 K for an external test set of 119 polymers. GTM (Generative Topographic Mapping) analysis produced a 2D map of "polymer chemical space", highlighting the various classes of polymers included in the study and their relationship with respect to Tg values. The epoxy-specific and general models are publicly available on our web server: http://infochim.u-strasbg.fr/webserv/VSEngine.html.
U2 - 10.1021/acsapm.9b00198
DO - 10.1021/acsapm.9b00198
JO - ACS Applied Polymer Materials
JF - ACS Applied Polymer Materials