Maqola

A computational structure–property relationship study of glass transition temperatures for a diverse set of polymers

Min ChenCenter for Computationally Assisted Science and Technology North Dakota State University Fargo North Dakota 58102Farukh JabeenCenter for Computationally Assisted Science and Technology North Dakota State University Fargo North Dakota 58102Bakhtiyor RasulevCenter for Computationally Assisted Science and Technology North Dakota State University Fargo North Dakota 58102Martin OssowskiCenter for Computationally Assisted Science and Technology North Dakota State University Fargo North Dakota 58102Philip BoudjoukDepartment of Chemistry and Biochemistry North Dakota State University Fargo North Dakota 58102

2018en

ABI

Annotatsiya

ABSTRACT The glass transition temperature ( T g ) is one of the most important properties affecting the stability of a polymeric material. A cheminformatics‐based approach has been employed to investigate the glass transition temperatures for a set of polymers. Specifically, a set of 80 polymers was used to build a quantitative structure–property relationship (QSAR). By applying a combination of cheminformatics methods, several predictive models were developed consisting of 1–10 physicochemical variables. The best predictive model, which is based on seven descriptors, successfully predicts the glass transition temperatures for the investigated polymers. Furthermore, the best developed model identified several significant descriptors responsible for glass transition temperatures of the investigated polymers with a correlation coefficient of r 2 = 0.77. The computational model derived from this study may serve as a powerful tool to predict glass transition temperatures for various polymers. © 2018 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2018 , 56 , 877–885

Hali tarjima qilinmagan

Identifikatorlar

DOI: 10.1002/polb.24602

Iqtiboslar va manbalar

3 ta iqtibos0 ta foydalanilgan manba

Koʻrsatkichlar — AkademScholar