As a source of biodiesel, recent studies showed that the biodiesel synthesis from castor oil is limited by a number of factors that include having the proper reaction temperature, oil-to-methanol molar ratio, and the quantity of catalyst. A study using response surface methodology as a model has been used to optimize the reaction factor for biodiesel synthesis from castor oil.100 In another similar study, parameters affecting castor oil transesterification reaction were investigated. Using Taguchi method consisting of four parameters (reaction temperature, mixing intensity, alcohol/oil ratio, and catalyst concentration), the best experimental conditions were determined. It was determined that the reaction temperature and mixing intensity can be optimized. Using the optimum results, the authors proposed a kinetic model that resulted in establishing an equation for the beginning rate of transesterification reaction.101 Besides the Taguchi method, a full factorial design of experiment is also another approach that was investigated to optimize biodiesel production from castor oil. Second-order polynomial model was obtained to predict biodiesel yield as a function of these variables. The experimental results for the process garnered an average yield of biodiesel of more than 90%.102 The use of models and simulations can, indeed, greatly facilitate the efficiency of biodiesel production from castor oil. To add further, a simple model using a ping-pong bi-bi mechanism has been proposed, which summarizes an efficient method of noncatalytic transesterification of castor oil in supercritical methanol and ethanol.103 It is an enzymatic reaction model that involves two substrates and two products (referred to as bi-bi system). An enzyme reacts first with one substrate to form a product and a modified enzyme. The modified enzyme would then react with a second substrate to form a final product and would regenerate the original enzyme. In this model, an enzyme is perceived as a ping-pong ball that bounces from one state to another.
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