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

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Abstract

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 (P3/2), reaction order-2 and 3 (F2 and F3), and diffusion models (D1 and D2) produced higher activation energy (Ea) values, while 3-diffusion (D3) produced the lowest Ea value. However, in subsequent stage III, only two reaction mechanisms (F1 and F2) were estimated with significant R2 value and F2 showed higher Ea 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.

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Acknowledgements

Authors acknowledge the practical, investigative, and academic support from the Institute of Chemical Engineering and Technology, University of the Punjab, Lahore, and Department of Chemical Engineering, University of Engineering and Technology (Lahore and Kala Shah Kaku Campuses), Pakistan.

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Authors and Affiliations

  1. Institute of Chemical Engineering and Technology, University of the Punjab, Lahore, 54590, Pakistan

    Muhammad Ashraf, Abdullah Khan Durrani & Rafi Ullah Khan

  2. Institute of Chemical Sciences, Bahauddin Zakariya University, Multan, 60800, Pakistan

    Muhammad Ashraf

  3. Department of Chemical Engineering, University of Engineering and Technology, Lahore, 54890, Pakistan

    Zaheer Aslam, Naveed Ramzan & Umair Aslam

  4. Department of Computer Science & Information Technology, Mirpur University of Science & Technology, Mirpur, Pakistan

    Samreen Ayaz

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  1. Muhammad Ashraf
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Contributions

i. Muhammad Ashraf (Ph.D. scholar) did all the experimental work, collected the data, and drafted the initial paper.

ii. Dr. Zaheer Aslam did data analysis and its interpretation, followed by several critical revisions of the main draft.

iii. Dr. Umair Aslam did the characterization work and assisted in ANN theoretical work.

iv. Dr. Naveed Ramzan is the co-supervisor and made revisions in the introduction and experimental sections.

v. Dr. Rafi Ullah Khan supervised this research and made revisions in the kinetic analysis section.

vi. Dr. Abdullah Durrani also co-supervised the work and did revisions on the thermodynamic section.

vii. Miss Samreen Ayaz processed ANN on TGA data.

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Correspondence to Muhammad Ashraf.

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Ashraf, M., Aslam, Z., Ramzan, N. et al. Pyrolysis of cattle dung: model fitting and artificial neural network validation approach. Biomass Conv. Bioref. 13, 10451–10462 (2023). https://doi.org/10.1007/s13399-021-02051-2

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