Molecular modelling of polymers: 5. Inclusion of intermolecular energetics in estimating glass and crystal-melt transition temperatures

Koehler, M. G.; Hopfinger, A. J.

doi:10.1016/0032-3861(89)90392-3

Cited by 65 publications

(42 citation statements)

References 4 publications

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“…Hopfinger et nomenon which is to be simulated and therefore al. 8,9,15 have tried to go beyond such limitations necessarily required some assumptions. The T g by combining computer modelling with the value corresponds to a physical change in the group additivity approach to calculate T g 's for structure of a glassy material when the temperaamorphous polymers.…”

Section: Qspr Developmentmentioning

confidence: 98%

A novel approach toward the prediction of the glass transition temperature: Application of the EVM model, a designer QSPR equation for the prediction of acrylate and methacrylate polymers

Camelio

Cypcar

Lazzeri

et al. 1997

J. Polym. Sci. A Polym. Chem.

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Section: Qspr Developmentmentioning

confidence: 98%

A novel approach toward the prediction of the glass transition temperature: Application of the EVM model, a designer QSPR equation for the prediction of acrylate and methacrylate polymers

Camelio

Cypcar

Lazzeri

et al. 1997

J. Polym. Sci. A Polym. Chem.

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“…The group contribution methodology was extended by Hopfinger and Koehler through combination with molecular modeling [125,126]. In these papers the main determinants of the glass transition temperature are considered to be the conformational entropy and mass moments of the polymer, which the authors estimate from molecular mechanics and conformational energy calculations.…”

Section: Glass Transition Temperature (T G )mentioning

confidence: 99%

Polymer Informatics

Adams

2010

Polymer Libraries

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Polymers are arguably the most important set of materials in common use. The increasing adoption of both combinatorial as well as high-throughput approaches, coupled with an increasing amount of interdisciplinarity, has wrought tremendous change in the field of polymer science. Yet the informatics tools required to support and further enhance these changes are almost completely absent. In the first part of the chapter, a critical analysis of the challenges facing modern polymer informatics is provided. It is argued, that most of the problems facing the field today are rooted in the current scholarly communication process and the way in which chemists and polymer scientists handle and publish data. Furthermore, the chapter reviews existing modes of representing and communicating polymer information and discusses the impact, which the emergence of semantic technologies will have on the way in which scientific and polymer data is published and transmitted. In the second part, a review of the use of informatics tools for the prediction of polymer properties and in silico design of polymers is offered.

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“…Koehler-Hopfinger et al [41,42] modeled the glass transition temperature of homopolymers by multiple linear regression of the intramolecular chain flexibility. Tan et al [43] predicted the glass transition temperature of poly(acrylic acid), poly-(methacrylic acid), polyacrylamide derivatives using the electronic structure of their monomers as calculated by different quantum chemical methods.…”

Section: Reviewmentioning

confidence: 99%