Abstract

Generally, the linear correlation coefficient is one of the most significant criteria to appraise the kinetic parameters computed from different reaction models. Actually, the optimal kinetic triplet should meet the following two requirements: first, it can be used to reproduce the original kinetic process; second, it can be applied to predict the other kinetic process. The aim of this paper is to attempt to prove that the common criteria are insufficient for meeting the above two purposes simultaneously. In this paper, the explicit Euler method and Taylor expansion are presented to numerically predict the kinetic process of linear heating reactions. The mean square error is introduced to assess the prediction results. The kinetic processes of hematite reduced to iron at different heating rates (8, 10 and 18 K/min) are utilized for validation and evaluation. The predicted results of the reduction of Fe2O3 → Fe3O4 indicated that the inferior linear correlation coefficient did provide better kinetic predicted curves. In conclusion, to satisfy the above two requirements of reproduction and prediction, the correlation coefficient is an insufficient criterion. In order to overcome this drawback, two kinds of numerical prediction methods are introduced, and the mean square error of the prediction is suggested as a superior criterion for evaluation.

Highlights

  • Overall, to elucidate the reaction mechanisms and describe the kinetic process of the experimental data, the kinetic triplet (i.e., the activation energy, E; the pre-exponential factor, A; the reaction model, f (α)) needs to be evaluated using kinetic analysis methods

  • The kinetic parameters chosen by the linear correlation coefficient can accurately reproduce the original kinetic curves, whereas, for the practical application, the kinetic parameters should successfully predict the other kinetic curves with the same mechanism

  • The correlation coefficient becomes the primary criterion to evaluate the kinetic parameters of different reaction models

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Summary

Introduction

To elucidate the reaction mechanisms and describe the kinetic process of the experimental data, the kinetic triplet (i.e., the activation energy, E; the pre-exponential factor, A; the reaction model, f (α)) needs to be evaluated using kinetic analysis methods. The kinetic parameters chosen by the linear correlation coefficient can accurately reproduce the original kinetic curves, whereas, for the practical application, the kinetic parameters should successfully predict the other kinetic curves with the same mechanism. Is it reasonable to select the kinetic parameters according to the correlation coefficient only? The kinetic parameters obtained using the model-fitting method are rarely applied to predict the nonisothermal kinetic process

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