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In relation to this article, we declare that there is no conflict of interest.
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Received December 7, 2019
Accepted April 4, 2020
articles This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Effects of cellulose, hemicellulose and lignin on biomass pyrolysis kinetics

Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, School of Energy and Environment, Southeast University, Nanjing 210096, P. R. China
zzhong@seu.edu.cn
Korean Journal of Chemical Engineering, October 2020, 37(10), 1660-1668(9), 10.1007/s11814-020-0553-y
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Abstract

In order to investigate interactions among biomass components on pyrolysis kinetics, pyrolysis experiments of individual components, synthetic biomass (designed by Design-Export software) and natural biomass (rice husk and corn straw) were conducted on a thermogravimetric analyzer (TGA). The results revealed that the pyrolysis behavior of cellulose is sharp, which is with low pyrolysis reaction order (1.38), high activation energy (168.61 kJ/mol) and high pre-exponential factor (3.50E+12 /s). The pyrolysis behavior of hemicellulose and lignin is slower but more complicated, both with high pyrolysis reaction order (2.30, 1.51), low activation energy (126.31, 87.21 kJ/mol), and low pre-exponential factor (9.67E+09, 2.59E+05 /s). Comparison of the experimental and calculated kinetics of synthetic samples confirmed that interactive effects on pyrolysis kinetics exist in the co-pyrolysis process. In particular, the presence of lignin inhibited the pyrolysis reaction rate of synthetic biomass, and cellulose played the dominant role in the activation energy and frequency factor. The pyrolysis reaction order was strongly influenced by hemicellulose owing to its abundant and complex branched chains. The predicted model was also established for calculating kinetic parameters of natural biomass with known proportions of three components. The predicted results were consistent with the experimental ones, validating the effectiveness of the prediction model.

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