Research on the co-pyrolysis of coal slime and lignin based on the combination of TG-FTIR, artificial neural network, and principal component analysis

Zhanshi Ni, Haobo Bi, Chunlong Jiang, Hao Sun, Wenliang Zhou, Zhicong Qiu, Liqun He and Qizhao Lin

Energy, 2022, vol. 261, issue PA

Abstract: Confronted with the shortage of fossil energy, the large inventory and the serious pollution of industrial solid waste, the development of clean and efficient industrial solid waste disposal methods have become a trend. In this study, Thermogravimetric-Fourier transform infrared spectrometry was utilized to carry out the co-pyrolysis experiment of coal slime and lignin. Pyrolysis experiments were carried out following 7 different mass mixing ratios. The initial pyrolysis temperatures of CS, S9G1, S7G3, S5G5, S3G7, S1G9, and LIG were 414.5, 373.3, 287.6, 233.3, 225.8, 218.6, and 209.6 °C, respectively. By observing the evolution of the gaseous products of the sample pyrolysis, the results showed that the gaseous products mainly include hydrocarbons, aldehydes, ethers, and alcohols. The ratio of lignin in the mixture was changed, and the interaction between the sample particles was different. The principal component analysis method provided helps to understand the mechanism of co-pyrolysis of coal slime and lignin. The relative error of the established artificial neural network prediction was less than 2.5%. This paper comprehensively analyzed the interaction and gas evolution law during the co-pyrolysis of coal slime and lignin.

Keywords: Coal slime; Lignin; TG-FTIR; Co-pyrolysis; Artificial neural network; Principal component analysis (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:261:y:2022:i:pa:s0360544222021260

DOI: 10.1016/j.energy.2022.125238

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