Optimization Study on the Thermal Decarboxylation of Coconut Oil using Magnesium Oxide as Catalyst

Author : Bañagale, Jashline Ann Aclan
Major Adviser : Capunitan, Jewel A.
Committee Members : Borines, Myra G.; Bambase, Manolito E. Jr.; Movillon, Jovita L.; Demafelis, Rex B.
Year : 2016
Month : May
Type : Thesis
Degree: BS
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This study aimed to optimize the conditions for the decarboxylation of coconut oil using magnesium oxide as catalyst. A three-variable Box-Behnken design (BBD) was used for the analysis of the simultaneous effect of temperature, catalyst loading and solvent concentration on the total percent conversion of triglycerides. It was found that a quadratic model best fits the set of experimental data. From the analysis of variance (ANOVA), all three factors, as well as the temperature-solvent concentration interaction, were found to be significant model terms. The model has insignificant lack of fit and the diagnostic plots were satisfactory, which means that the regression model can be used to predict values of the response at conditions within those used in this study. Based on the regression model, the factor that has the most effect on the response was temperature. Furthermore, contour plots indicate that the response increases with each factor but starts to have antagonistic effects at very high levels. The main factors that possibly contribute to this behavior are catalyst degradation, solvent interference and catalyst agglomeration. The final optimized conditions obtained through regression analysis were 18.41 % (w/w) catalyst loading, 186.99 °C temperature and 86.29 % (w/w) solvent concentration. The maximum triglyceride conversion predicted from the model was 63.25 ± 2.15 %. The model was validated and results indicated that there is no significant difference between predicted and observed values.

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