Dataset Information

Using combined computational techniques to predict the glass transition temperatures of aromatic polybenzoxazines.

ABSTRACT: The Molecular Operating Environment software (MOE) is used to construct a series of benzoxazine monomers for which a variety of parameters relating to the structures (e.g. water accessible surface area, negative van der Waals surface area, hydrophobic volume and the sum of atomic polarizabilities, etc.) are obtained and quantitative structure property relationships (QSPR) models are formulated. Three QSPR models (formulated using up to 5 descriptors) are first used to make predictions for the initiator data set (n?=?9) and compared to published thermal data; in all of the QSPR models there is a high level of agreement between the actual data and the predicted data (within 0.63-1.86 K of the entire dataset). The water accessible surface area is found to be the most important descriptor in the prediction of T(g). Molecular modelling simulations of the benzoxazine polymer (minus initiator) carried out at the same time using the Materials Studio software suite provide an independent prediction of T(g). Predicted T(g) values from molecular modelling fall in the middle of the range of the experimentally determined T(g) values, indicating that the structure of the network is influenced by the nature of the initiator used. Hence both techniques can provide predictions of glass transition temperatures and provide complementary data for polymer design.

SUBMITTER: Mhlanga P

PROVIDER: S-EPMC3542367 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Using combined computational techniques to predict the glass transition temperatures of aromatic polybenzoxazines.

Mhlanga Phumzile P Wan Hassan Wan Aminah WA Hamerton Ian I Howlin Brendan J BJ

PloS one 20130110 1

The Molecular Operating Environment software (MOE) is used to construct a series of benzoxazine monomers for which a variety of parameters relating to the structures (e.g. water accessible surface area, negative van der Waals surface area, hydrophobic volume and the sum of atomic polarizabilities, etc.) are obtained and quantitative structure property relationships (QSPR) models are formulated. Three QSPR models (formulated using up to 5 descriptors) are first used to make predictions for the in ...[more]

PMID: 23326419

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Project description:The thermal conductivities and glass transition temperatures of polybutadiene crosslinked with randomly distributed sulfur chains having different lengths from mono-sulfur (S1) to octa-sulfur (S8) were investigated. The thermal conductivities of the related models as a function of the heat flux autocorrelation function, applying an equilibrium molecular dynamic (EMD) simulation and the Green-Kubo method, were studied for a wide range of temperatures. The influence of the length of sulfur chains, degree of crosslinking, and molar mass of the crosslinker on the glass transition temperature and final values of thermal conductivities were studied. First, the degree of crosslinking is considered constant for the eight simulation models, from mono-sulfur (S1) to octa-sulfur (S8), while the molar mass of the sulfur is increases. The results show that the thermal conductivities of the crosslinked structure decrease with increasing temperature for each model. Moreover, by increasing the lengths of the sulfur chains and the molar weight of the crosslinker, thermal conductivity increases at a constant temperature. The MD simulation demonstrates that the glass transition temperature and density of the crosslinked structure enhance as the length of the sulfur chains and molar mass of the sulfur increase. Second, the molar weight of sulfur is considered constant in these eight models; therefore, the degree of crosslinking decreases with the increase in the lengths of the sulfur chains. The results show that the thermal conductivities of the crosslinked structure decrease with the increase in the temperature for each model. Moreover, by increasing the lengths of sulfur chains and thus decreasing the degree of crosslinking, the trend in changes in thermal conductivities are almost the same for all of these models, so thermal conductivity is constant for a specific temperature. In addition, the glass transition temperature and density of the crosslinked structure decrease.

Dataset Information

Using combined computational techniques to predict the glass transition temperatures of aromatic polybenzoxazines.

Publications

Using combined computational techniques to predict the glass transition temperatures of aromatic polybenzoxazines.

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