Thermogravimetric analysis of bamboo-tar under different heating rates based on distributed activation energy model

Abstract

Carbon fiber is a kind of new polymer material with excellent mechanical properties and being applied widely. The process of carbon fiber prepared by bamboo tar, including extraction, condensation, spinning, oxidation and carbonation, is influenced by the pyrolysis kinetics significantly. In this paper, the thermogravimetric analysis (TGA) of bamboo tar produced in the process of pyrolysis and gasification of the bamboo which is known as Phylostachys sulphurea, was analyzed by the distributed activation energy model (DAEM) to understand the kinetic properties and parameters of bamboo tar. The thermogravimetric analysis of bamboo tar which is used as the raw material of carbon fiber was conducted under 5 different heating rates (i.e. 5, 10, 15, 30 and 50 °C/min, etc.) in nitrogen atmosphere. The results show that the activation energy of bamboo tar and the exponential factor increased significantly with the increase of the heating rate, and the low heating rate is advantageous to the extraction of bamboo tar solvent and the thermal polycondensation, which can provide scientific reference for the optimization of carbon fiber technology. The thermal weight results show that the temperature range of bamboo tar being decomposed rapidly is 213°C-410°C. The ranges of the activation energy were calculated by DAEM, which have small difference in comparisons with five heating rates when the conversion rate is at 0.1-0.6 and the average value of the activation energy is 119 kJ/mol. The stability range of the activation energy is enlarged when the conversion rate is greater than 0.6 and heating rate increases. Keywords: bamboo tar, carbon fiber, thermogravimetric analysis (TGA), distributed activation energy model (DAEM) DOI: 10.25165/j.ijabe.20181106.3839 Citation: Zhang H, Yan B B, Lei T Z, Liu T, Hu J J, Li Y M, et al. Thermogravimetric analysis of bamboo-tar under different heating rates based on distributed activation energy model. Int J Agric & Biol Eng, 2018; 11(6): 180–186.