4.5 Article

Kinetic Study on The Slow Pyrolysis of Isolated Cellulose and Lignin from Teak Sawdust

Journal

THERMOCHIMICA ACTA
Volume 711, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.tca.2022.179202

Keywords

DAEM; teak sawdust; cellulose; klason lignin; TGA; pyrolysis

Funding

  1. Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi, Republik Indonesia through Pendidikan Magister menuju Doktor untuk Sarjana Unggul (PMDSU) Scholarship

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This study aimed to analyze the stages of biomass pyrolysis using a comprehensive kinetics study. Pyrolysis experiments were conducted on teak sawdust, klason lignin, and cellulose, and the results were analyzed using various methods. Consistent trends in activation energy were observed using the model-free methods KAS and OFW. Additionally, a multi-component nth-order DAEM model successfully fit the experimental data and captured the two stages of lignin pyrolysis.
This study was conducted to explicate the stages of biomass pyrolysis by using a comprehensive kinetics study. The pyrolysis was performed on teak sawdust and its isolated klason lignin and cellulose. Pyrolysis experiments were carried out on Thermogravimetric Analysis (TGA) with 3 different heating rates at 5, 10, and 20 K min(-1). The results were analyzed with 2 model-free methods of Kissinger-Akahira-Sunose (KAS) and Ozawa-Flynn-Wall (OFW), and a model-fitting method of nth-order Distributed Activation Energy Model (DAEM). The model-free kinetics analyses using KAS and OFW methods gave consistent activation energy trends for all samples. In teak sawdust pyrolysis, the activation energy fluctuates with the increase of conversion between 235-252 kJ mol(-1). For cellulose, the activation energy increased along with the conversion from 208 to 240 kJ mol(-1). Whereas for lignin, the activation energy widely ranges between 80-250 kJ mol(-1). Further exploration using the multi-component nth-order DAEM was conducted to provide deeper insight on multistage pyrolysis reaction. The 4 components DAEM successfully provided a satisfying mathematical fit to the experimental data of teak sawdust pyrolysis. The proposed model was able to capture the two stages of lignin pyrolysis. The method that has been demonstrated here gave a broader insight to the application of DAEM in describing lignocellulosic biomass pyrolysis.

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