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Modelling and optimization of main independent parameters for biodiesel production over a Cu0.4Zn0.6Al2O4 catalyst using an RSM method
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Engineering and Chemical Sciences (from 2013). Islamic Azad Univ, Iran.ORCID iD: 0000-0002-6698-9179
Islamic Azad Univ, Iran.ORCID iD: 0000-0002-2862-008X
Esfarayen Univ Technol, Iran..
Ming Chi Univ Technol, Taiwan.
2021 (English)In: Journal of chemical technology and biotechnology (1986), ISSN 0268-2575, E-ISSN 1097-4660, Vol. 97, no 1, p. 111-119Article in journal (Refereed) Published
Abstract [en]

In this research, the modeling of Cu0.4Zn0.6Al2O4 catalysts performance and optimizing of esterification reactions were considered by the central composite design (RSM) response method. The main independent parameters of temperature, the ratio of alcohol to oil, the amount of catalyst and time duration have been considered for setting the esterification process. To access the maximum activity in the esterification process, the optimum conditions are estimated at 10.42 the molar ratio of alcohol to oil, 2.98 wt.% for the amount of catalyst at the temperature of 163.37 degrees C and within 4.15 hrs. Under these conditions, the conversion will be above 97.94%. These conditions have been applied to adjust the process of transesterification of waste cooking oil. The reusability of the Cu0.4Zn0.6Al2O4 nanocatalyst in the esterification reaction was investigated in this study. Employed statistical techniques and developed models can be employed as a useful tool for design, prediction, and optimization of the biodiesel production process with effective performance for various industrial applications. (c) 2021 Society of Chemical Industry (SCI).

Place, publisher, year, edition, pages
John Wiley & Sons, 2021. Vol. 97, no 1, p. 111-119
Keywords [en]
Cu-0 4, Zn-0 6, Al2O4 catalyst, biodiesel production, esterification reactions, RSM method, optimization
National Category
Chemical Engineering
Research subject
Chemical Engineering
Identifiers
URN: urn:nbn:se:kau:diva-86850DOI: 10.1002/jctb.6916ISI: 000701864500001OAI: oai:DiVA.org:kau-86850DiVA, id: diva2:1608385
Available from: 2021-11-03 Created: 2021-11-03 Last updated: 2022-11-22Bibliographically approved

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Hashemzehi, Mojgan

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