2003
DOI: 10.1021/ci0202990
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Correlation between the Glass Transition Temperatures and Repeating Unit Structure for High Molecular Weight Polymers

Abstract: A set of five-parameter descriptors, sum MV(ter)(R(ter)), L(F), DeltaX(SB), sum PEI, and Q(+/-), are developed to express the chain stiffness (or mobility) and the intermolecular forces of polymers. Investigated results show a good correlation (R = 0.9517, R(2) = 0.9056, s = 20.86 K) between the glass transition temperatures (T(g)s) and the five parameters for a diverse set of 88 polymers. The descriptors are easy to calculate directly from the repeating unit structure and have clear physical meanings. This ap… Show more

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Cited by 95 publications
(91 citation statements)
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“…The most referenced predictive model of Tg was produced by Bicerano [4] and subsequently numerous researchers have attempted to achieve the same level of accuracy in their predictions [4][5][6][7]. Beyond the problem of the accurate estimation of Tg, other polymer properties relevant to their end-use performance have been the focus of developers of predictive models.…”
Section: Prediction Of Polymer Materials Propertiesmentioning
confidence: 99%
“…The most referenced predictive model of Tg was produced by Bicerano [4] and subsequently numerous researchers have attempted to achieve the same level of accuracy in their predictions [4][5][6][7]. Beyond the problem of the accurate estimation of Tg, other polymer properties relevant to their end-use performance have been the focus of developers of predictive models.…”
Section: Prediction Of Polymer Materials Propertiesmentioning
confidence: 99%
“…On a larger data set, Katritzky et al [7] developed a QSPR for the molar glass transition temperature (T g /M) of 88 uncross-linked linear homopolymers. The model has five molecular descriptors and the s for T g is 32.9 K. On the same data, Cao and Lin [8] developed a QSPR model (R 2 = 0.9056) by using five molecular descriptors that focus on the influence of chain stiffness and intermolecular forces. Yu et al [9] developed stepwise multiple linear regression (MLR) for 107 polystyrenes and generated a QSPR model (R = 0.959 and s = 15.20 K) from the training set of 96 polystyrenes.…”
Section: Introductionmentioning
confidence: 99%
“…The advantage of this approach lies in the fact that it requires only the knowledge of the chemical structure and is not dependent on any experimental properties. The QSPR approach has been successfully used to predict many polymeric properties, such as refractive index 3,7-10 , glass transition temperature 8,[11][12][13][14][15][16][17] , intrinsic viscosity 18,19 , solubility parameters 20 and conformational property 21 . In this work we demonstrate the usefulness and focus of some of the parameters in deriving predictive QSPR models.…”
Section: Introductionmentioning
confidence: 99%