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 °C whereas, in stage III (390–690 °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 °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 ∆ G and increased ∆ S for the whole process with stable ∆ H . This study provides the theoretical and practical guideline for the utilization of cattle dung as a potential energy source.