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 (F₁) had the highest value of regression coefficient (R²) in both stages. In stage II, the Power-law (P_3/2), reaction order-2 and 3 (F₂ and F₃), and diffusion models (D₁ and D₂) produced higher activation energy (E_a) values, while 3-diffusion (D₃) produced the lowest E_a value. However, in subsequent stage III, only two reaction mechanisms (F₁ and F₂) were estimated with significant R² value and F₂ showed higher E_a value. The simulated TG/DTG validated that decomposition of cattle dung was best described by F₁ 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 R² 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. [ABSTRACT FROM AUTHOR]