Co-pyrolytic interactions, kinetics and products of biomass pyrolysis coke and rapeseed cake: Machine learning, DAEM and 2D-COS analysis

In this study, an efficient strategy for synergistic disposal of biomass pyrolysis coke (PC) and rapeseed cake (RC) was proposed to explore their clean utilization, with the purposes for evaluating the co-pyrolytic interactions, kinetics, mechanism and products. The results indicated that synergistic effect was strengthened by lower PC ratio and temperature. A multiple distributed activation energy model (MDAEM) was applied to obtain accurate activation energy distributions. Co-pyrolysis resulted in lower average activation energy and wider distribution, from which the activation energy E0 and sigma were in the range of 103.99-214.16 kJ/mol and 3.18-38.09 kJ/mol. MDAEM was also innovatively combined with machine learning to describe and predict co-pyrolysis process, with the determination coefficient R2 beyond 0.999923. Sensitivity analysis and principal component analysis were applied, indicating RC was more sensitive to the heating rate, and preferred dominating reactions at hightemperature region. Temperature dependences of pyrolysates was obtained by two-dimensional correlation spectroscopy method.

Automated summary

An efficient strategy for synergistic disposal of biomass pyrolysis coke and rapeseed cake was proposed in this study. The results showed that the synergistic effect was enhanced by reducing the pyrolysis coke ratio and temperature. The combination of the multiple distributed activation energy model and machine learning accurately described and predicted the co-pyrolysis process. Sensitivity analysis and principal component analysis revealed the sensitivity of rapeseed cake to the heating rate and its preference for dominating reactions at high temperature.