Smoothing and differentiation of thermogravimetric data of biomass materials

Abstract

Due to the experimental errors, the chemical effect of minor reactions, and some physical effects of heat and mass transfer, there usually exists much noise in the mass loss data resulted from thermal decomposition experiments, and thus high quality smoothing algorithm plays an important role in obtaining reliable derivative thermogravimetric (DTG) curves required for differential kinetic analysis. In this paper three smoothing methods, i.e. Moving Average smoothing, Gaussian smoothing, and Vondrak smoothing, are investigated in detail for pre-treatment of biomass decomposition data to obtain the DTG curves, and the smoothing results are compared. It is concluded that by choosing reasonable smoothing parameters based on the spectrum analysis of the data, the Gaussian smoothing and Vondrak smoothing can be reliably used to obtain DTG curves. The kinetic parameters calculated from the original TG curves and smoothed DTG curves have excellent agreement, and thus the Gaussian and Vondrak smoothing algorithms can be used directly and accurately in kinetic analysis.