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Strategies for developing quantitative structure-affinity relationships (QSAfR) for the prediction of break-through performance of 31 chlorinated hydrocarbons on activated carbon have been studied. Two different approaches for the selection of a limited set of compounds for modelling were evaluated through the predictive power of the resulting QSAfR models. When the model was based on a training-set...
An unbiased evaluation of predictive models for the affinity coefficient of the Dubinin-Radushkevich equation was performed. The first step involved the selection of a minimum number of representative and chemically diverse organic compounds, the training set. This set, isopropylamine, heptane, dichloromethane, 2-chloro-2-methylpropane, 2-butanone, 1-chloropentane, acetonitrile, and benzene, covering...
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