Investigation of co-combustion of sewage sludge and coffee industry residue by TG-FTIR and machine learning methods

Faced with the problems of the environment and resources, the co-combustion of sewage sludge has gradually become a trend. In this paper, the combination of thermogravimetric and Fourier transform infrared spectroscopy (TG-FTIR) was used to study the co-combustion of sewage sludge (SS) and coffee industry residues (CIR). SS and CIR were mixed according to the mass ratios of 1:0, 9:1, 7:3, 5:5, 3:7, 1:9, and 0:1, and the temperature was programmed to be heated to 800 degrees C in the atmosphere with an air flow rate of 50 mL/min. The percentages of mass loss during combustion of SS and CIR were 55.8% and 96.8%, respectively. As the mass percentage of CIR increased, the comprehensive combustion index (CCI) of the sample improved. The Kissinger-Akahira-Sunose (KAS), Flynn-Wall-Ozawa (FWO), and Starink methods were used to evaluate the activation energy (E-alpha) of the reaction. Principal component analysis (PCA) and artificial neural network (ANN) were used to determine the main reaction and predict experimental data of co-combustion of SS and CIR, respectively.