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Biodiesel production from Calophyllum inophyllum-Ceiba pentandra oil mixture: Optimization and characterization

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dc.citedby155
dc.contributor.authorOng H.C.en_US
dc.contributor.authorMilano J.en_US
dc.contributor.authorSilitonga A.S.en_US
dc.contributor.authorHassan M.H.en_US
dc.contributor.authorShamsuddin A.H.en_US
dc.contributor.authorWang C.-T.en_US
dc.contributor.authorIndra Mahlia T.M.en_US
dc.contributor.authorSiswantoro J.en_US
dc.contributor.authorKusumo F.en_US
dc.contributor.authorSutrisno J.en_US
dc.contributor.authorid55310784800en_US
dc.contributor.authorid57052617200en_US
dc.contributor.authorid39262559400en_US
dc.contributor.authorid9232771700en_US
dc.contributor.authorid35779071900en_US
dc.contributor.authorid14042815800en_US
dc.contributor.authorid56997615100en_US
dc.contributor.authorid56192714800en_US
dc.contributor.authorid56611974900en_US
dc.contributor.authorid25928846200en_US
dc.date.accessioned2023-05-29T07:25:34Z
dc.date.available2023-05-29T07:25:34Z
dc.date.issued2019
dc.descriptionAlternative fuels; Biodiesel; Catalysis; Esterification; Esters; Mixtures; Molar concentration; Molar ratio; Neural networks; Potassium hydroxide; Transesterification; Ant Colony Optimization (ACO); Bio-diesel blends; Biodiesel production; Catalyst concentration; Kinetics studies; Reaction temperature; Renewable energies; Transesterification process; Ant colony optimizationen_US
dc.description.abstractIn this study, a novel modeling approach (artificial neural networks (ANN) and ant colony optimization (ACO)) was used to optimize the process variables for alkaline-catalyzed transesterification of CI40CP60 oil mixture (40 wt% of Calophyllum inophyllum oil mixed with 60 wt% of Ceiba pentandra oil) in order to maximize the biodiesel yield. The optimum values of the methanol-to-oil molar ratio, potassium hydroxide catalyst concentration, and reaction time predicted by the ANN-ACO model are 37%, 0.78 wt%, and 153 min, respectively, at a constant reaction temperature and stirring speed of 60 �C and 1000 rpm, respectively. The ANN-ACO model was validated by performing independent experiments to produce the CI40CP60 methyl ester (CICPME) using the optimum transesterification process variables predicted by the ANN-ACO model. There is very good agreement between the average CICPME yield determined from experiments (95.18%) and the maximum CICPME yield predicted by the ANN-ACO model (95.87%) for the same optimum values of process variables, which corresponds to a difference of 0.69%. Even though the ANN-ACO model is only implemented to optimize the transesterification of process variables in this study. It is believed that the model can be used to optimize other biodiesel production processes such as seed oil extraction and acid-catalyzed esterification for various types of biodiesels and biodiesel blends. � 2019 Elsevier Ltden_US
dc.description.natureFinalen_US
dc.identifier.doi10.1016/j.jclepro.2019.02.048
dc.identifier.epage198
dc.identifier.scopus2-s2.0-85062153938
dc.identifier.spage183
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85062153938&doi=10.1016%2fj.jclepro.2019.02.048&partnerID=40&md5=d41ca043e1a459dd21be2addfeb8c01c
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24657
dc.identifier.volume219
dc.publisherElsevier Ltden_US
dc.relation.ispartofAll Open Access, Green
dc.sourceScopus
dc.sourcetitleJournal of Cleaner Production
dc.titleBiodiesel production from Calophyllum inophyllum-Ceiba pentandra oil mixture: Optimization and characterizationen_US
dc.typeArticleen_US
dspace.entity.typePublication
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