Biodiesel Production from Waste Cooking Oil Using Extracted Catalyst from Plantain Banana Stem via RSM and ANN Optimization for Sustainable Development

Abstract

Biodiesel is a promising sector worldwide and is experiencing significant and rapid growth. Several studies have been undertaken to utilize homogeneous base catalysts in the form of KOH to develop biodiesel in order to establish a commercially viable and sustainable biodiesel industry. This research centers around extracting potassium hydroxide (KOH) from banana trunks and employing it in the transesterification reaction to generate biodiesel from waste cooking oil (WCO). Various operational factors were analyzed for their relative impact on biodiesel output, and after optimizing the reaction parameters, a conversion rate of 95.33% was achieved while maintaining a reaction period of 2.5 h, a methanol-to-oil molar ratio of 15:1, and a catalyst quantity of 5 wt%. Response surface methodology (RSM) and artificial neural network (ANN) models were implemented to improve and optimize these reaction parameters for the purpose of obtaining the maximum biodiesel output. Consequently, remarkably higher yields of 95.33% and 95.53% were achieved by RSM and ANN, respectively, with a quite little margin of error of 0.0003%. This study showcases immense promise for the large-scale commercial production of biodiesel.

Publication DOI: https://doi.org/10.3390/su151813599
Divisions: College of Engineering & Physical Sciences > School of Engineering and Technology > Mechanical, Biomedical & Design
College of Engineering & Physical Sciences > Energy and Bioproducts Research Institute (EBRI)
College of Engineering & Physical Sciences
Funding Information: The article is part of research work approved by the HEC Pakistan under Project No. (NRPU20-12879/NRPU/R&D/HEC/2020). And this research is also funded by the Researchers Supporting Project number (RSPD 2023R701), King Saud University, Riyadh, Saudi Arabia
Additional Information: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/) Funding: The authors extend their appreciation to the Researchers supporting Project number (RSP2023R701), King Saud University, Riyadh, Saudi Arabia
Uncontrolled Keywords: artificial neural network,biodiesel,circular economy,plantain banana stem,response surface methodology,sustainable development,waste management,Computer Science (miscellaneous),Environmental Science (miscellaneous),Geography, Planning and Development,Energy Engineering and Power Technology,Hardware and Architecture,Management, Monitoring, Policy and Law,Computer Networks and Communications,Renewable Energy, Sustainability and the Environment
Publication ISSN: 2071-1050
Last Modified: 07 Oct 2024 07:52
Date Deposited: 22 Sep 2023 08:13
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2023-09-12
Accepted Date: 2023-09-01
Authors: Ahmad, Gulzar
Imran, Shahid
Farooq, Muhammad
Shah, Asad Naeem
Anwar, Zahid
Rehman, Ateekh Ur
Imran, Muhammad (ORCID Profile 0000-0002-3057-1301)

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