A temperature-dependent quantum mechanical/neural net model for vapor pressure
Beck B, Clark T (2001)
Publication Status: Published
Publication Type: Journal article
Publication year: 2001
Journal
Book Volume: 41
Pages Range: 1053-1059
Journal Issue: 4
DOI: 10.1021/ci0103222
Abstract
We present a temperature-dependent model for vapor pressure based on a feed-forward neural net and descriptors calculated using AM1 semiempirical MO-theory. This model is based on a set of 7681 measurements at various temperatures performed on 2349 molecules. We employ a 10-fold cross-validation scheme that allows us to estimate errors for individual predictions. For the training set we find a standard deviation of the error s = 0.322 and a correlation coefficient (R-2) of 0.976. The corresponding values for the validation set are s = 0.326 and R-2 = 0.976. We thoroughly investigate the temperature-dependence of our predictions to ensure that our model behaves in a physically reasonable manner. As a further test of temperature-dependence, we also examine the accuracy of our vapor pressure model in predicting the related physical properties, the boiling point, and the enthalpy of vaporization.
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Germany (DE)How to cite
APA:
Beck, B., & Clark, T. (2001). A temperature-dependent quantum mechanical/neural net model for vapor pressure. Journal of Chemical Information and Computer Sciences, 41(4), 1053-1059. https://dx.doi.org/10.1021/ci0103222
MLA:
Beck, Bernd, and Timothy Clark. "A temperature-dependent quantum mechanical/neural net model for vapor pressure." Journal of Chemical Information and Computer Sciences 41.4 (2001): 1053-1059.
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