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

Abstract

Faced with increasingly severe environmental and energy issues, the development and utilization of solid waste have become a trend. In this study, a thermogravimetric-Fourier infrared spectrometer-mass spectrometer (TG-FTIR-MS) was used to carry out the co-pyrolysis experiment of coal slime and cellulose. The samples with mass mixing ratios of 0:10, 1:9, 3:7, 5:5, 7:3, 9:1, and 10:0 were pyrolyzed in N2 atmosphere. The percentages of mass loss during the pyrolysis of coal slime and cellulose were 15.69 and 94.28%, respectively. The addition of cellulose to the coal slime could significantly improve the pyrolysis performance of the sample. It was detected by FTIR that the pyrolysis of the blends mainly formed C=O-containing compounds. MS was used to monitor the ion current intensity of gaseous products of sample pyrolysis online. The average activation energy of the reaction between coal slime and cellulose calculated by the Kissinger-Akahira-Sunose method were 237.59 kJ/mol and 174.06 kJ/mol, respectively. The principal component 1 and principal component 2 dominated the co-pyrolysis process of coal slime and cellulose. The MAE, RMSE, and R2 of the artificial neural network prediction model for predicting the pyrolysis process of the sample were 0.5249, 0.8244, and 0.9994, respectively. This research provided basic theory and data support for understanding the co-pyrolysis of coal slime and biomass.