Kinetic Parameter Evaluation with Linearly Increasing Temperature Profiles: Integral Methods

Abstract

ABSTRACT Two integral methods for kinetic parameter estimation with linear temperature profiles were tested using simulated and experimental data sets. They were the second rational approximation method (SRAM) and the equivalent point method (EPM) using least squares nonlinear regression (LSNR) and weighted least squares nonlinear regression (WLSNR). For three simulated data sets, the SRAM with WLSNR yielded accurate parameter estimation. For the experimental data set, both SRAM and EPM using WLSNR yielded accurate parameter estimation. The standard error in activation energy were 37.3% (for SRAM) and 46.7% (for EPM) lower than that of the differential method. The SRAM with WLSNR was the best parameter estimation procedure.