Okonkwo, Chinwe P;
Ajiwe, Vincent IE;
Ikeuba, Alexander I;
Emori, Wilfred;
Okwu, Modestus O;
Ayogu, Jude I;
(2023)
Production and performance evaluation of biodiesel from Elaeis guineensis using natural snail shell-based heterogeneous catalyst: kinetics, modeling and optimisation by artificial neural network.
RSC Advances
, 13
(28)
pp. 19495-19507.
10.1039/d3ra02456c.
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Abstract
This study presents an approach to produce biodiesel from Elaeis guineensis using natural heterogeneous catalysts derived from raw, calcined, and acid-activated forms of waste snail shells. The catalysts were thoroughly characterized using SEM, and process parameters were systematically evaluated during biodiesel production. Our results demonstrate a remarkable crop oil yield of 58.87%, with kinetic studies confirming second-order kinetics and activation energies of 43.70 kJ mol-1 and 45.70 kJ mol-1 for methylation and ethylation, respectively. SEM analysis identified the calcined catalyst as the most effective, exhibiting remarkable reusability for continuous reactions running up to five times. Moreover, the acid concentration from exhaust fumes yielded a low acid value (B100 0.0012 g dm-3), significantly lower than that of petroleum diesel, while the fuel properties and blends satisfied the ASTM standards. The sample-heavy metals were well within acceptable limits, confirming the quality and safety of the final product. Our modelling and optimization approach produced a remarkably low mean squared error (MSE) and a high coefficient of determination (R), providing strong evidence for the viability of this approach at an industrial scale. Our results represent a significant input in sustainable biodiesel production and underscore the enormous potential of natural heterogeneous catalysts derived from waste snail shells for achieving sustainable and environmentally friendly biodiesel production.
| Type: | Article |
|---|---|
| Title: | Production and performance evaluation of biodiesel from Elaeis guineensis using natural snail shell-based heterogeneous catalyst: kinetics, modeling and optimisation by artificial neural network |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1039/d3ra02456c |
| Publisher version: | https://doi.org/10.1039/D3RA02456C |
| Language: | English |
| Additional information: | © The Authors 2023. Original content in this paper is licensed under the terms of the Creative Commons Attribution 3.0 Unported (CC BY 3.0) Licence (https://creativecommons.org/licenses/by/3.0/). |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Chemistry |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10173145 |
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