Abstract
Differential scanning calorimetry (DSC) followed by mathematical data processing can be used instead of the conventional method of long term thermal aging in predicting the activity of antioxidants in polyolefins. In this method, a regression relationship is established between the oxidation initial temperatures measured by DSC (X data) and the oxidation induction period values determined by thermal aging (Y data). Two approaches, called hard and soft, are employed in the construction of models. In the first case, nonlinear regression analysis is used in combination with successive Bayesian estimation. The second approach combines partial least squares regression and simple interval calculation. Use of a common data set makes it possible to compare these approaches and to draw inferences as to the cases in which one or the other is preferable.
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