Pyrolysis of cattle dung: model fitting and artificial neural network validation approach

The pyrolysis of the cattle dung was quantified using the Coats-Redfern method. The thermogravimetric and derivate curves (TG/DTG) divided the decomposition into three stages. Apart from stage I (dehydration), stage II exhibited higher thermal decomposition rate in the temperature range of 220-380 degrees C whereas, in stage III (390-690 degrees C), a lower decomposition rate was noticed. Comparative kinetic parameters for solid-state reactions showed that first-order reaction (F-1) had the highest value of regression coefficient (R-2) in both stages. In stage II, the Power-law (P-3/2), reaction order-2 and 3 (F-2 and F-3), and diffusion models (D-1 and D-2) produced higher activation energy (E-a) values, while 3-diffusion (D-3) produced the lowest E-a value. However, in subsequent stage III, only two reaction mechanisms (F-1 and F-2) were estimated with significant R-2 value and F-2 showed higher E-a value. The simulated TG/DTG validated that decomposition of cattle dung was best described by F-1 in both stages. In addition to kinetic analysis through Coats-Redfern method, mass change at 20 degrees C/min was also processed by employing artificial neural network (ANN) and the model was validated with a strong R-2 value and lower mean squared error (MSE). In thermodynamic analysis, the increase in the heating rate decreased increment G and increased increment S for the whole process with stable increment H. This study provides the theoretical and practical guideline for the utilization of cattle dung as a potential energy source.