title: Hybrid response surface methodology-genetic algorithm optimization of ultrasound-assisted transesterification of waste oil catalysed by immobilized lipase on mesoporous silica/iron oxide magnetic core-shell nanoparticles.
abstract: The production ofbiodiesel by transesterification of waste cooking oil (WCO) to partially substitute petroleum diesel is one of the measures for solving the twin problems of environment pollution and energy demand. An environmentally benign process for the enzymatic transesterification using immobilized lipase has attracted considerable attention for biodiesel production. Here, a superparamagnetic, high surface area substrate for lipase immobilization is evaluated. These immobilization substrates are composed of mesoporous silica/superparamagnetic iron oxide core-shell nanoparticles. The effects of methanol ratio to WCO, lipase concentration, water content and reaction time on the synthesis of biodiesel were analysed by utilizing the response surface methodology (RSM). A quadratic response surface equation for calculating fatty acid methyl ester (FAME) content as the objective function was established based on experimental data obtained in accordance with the central composite design. The RSM-based model was then used as the fitness function for genetic algorithm (GA) to optimize its input space. Hybrid RSM-GA predicted the maximum FAME content (91%) at the optimum level of medium variables: methanol ratio to WCO, 4.34; lipase content, 43.6%; water content, 10.22%; and reaction time, 6h. Moreover, the immobilized lipase could be used for four times without considerable loss of the activity.
authors.affiliation: Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran.
authors.forename: Mahmoud
authors.initials: M
authors.lastname: Karimi
authors.affiliation: Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran.
authors.forename: Alireza
authors.initials: A
authors.lastname: Keyhani
authors.affiliation: Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran.
authors.forename: Asadolah
authors.initials: A
authors.lastname: Akram
authors.affiliation: Department of Chemical Engineering and Materials Science, University of California Davis, Davis, CA 95616, USA.
authors.forename: Masoud
authors.initials: M
authors.lastname: Rahman
authors.affiliation: Department of Biological and Agricultural Engineering, University of California Davis, Davis, CA 95616, USA.
authors.forename: Bryan
authors.initials: B
authors.lastname: Jenkins
authors.affiliation: Department of Chemical Engineering and Materials Science, University of California Davis, Davis, CA 95616, USA.
authors.forename: Pieter
authors.initials: P
authors.lastname: Stroeve
mesh_terms: D000465:Algorithms; D000704:Analysis of Variance; D056804:Biofuels; D001709:Biotechnology / Q000379:methods; D004800:Enzymes, Immobilized; D017743:Equipment Reuse; D004951:Esterification / Q000528:radiation effects; D008049:Lipase / Q000378:metabolism*; D058185:Magnetite Nanoparticles / Q000737:chemistry*; D008957:Models, Genetic; D012044:Regression Analysis; D012107:Research Design; D012822:Silicon Dioxide / Q000737:chemistry*; D013010:Sonication / Q000379:methods
chemical_list: D056804:Biofuels; D004800:Enzymes, Immobilized; D058185:Magnetite Nanoparticles; D012822:Silicon Dioxide; D008049:Lipase