Castor oil is a unique vegetable oil with peculiar features such as extremely high viscosity and unusual miscibility with short chain alcohol. This necessitates a comprehensive exploration of all process parameters in the transesterification of castor oil, which is rarely done for other vegetable oils. In this study, the methanolysis of castor oil using alkaline catalyst (potassium hydroxide, KOH) was investigated in a batch reactor via the conventional one-variable-at-a-time protocol. The effects of process parameters including reaction time, reaction temperature, methanol-to-oil molar ratio, catalyst concentration and stirring rate on biodiesel yield were evaluated. The results indicate the significant influence of all parameters on the biodiesel yield. An optimum yield of 96% was achieved at a reaction time of 60 min, reaction temperature of 65 o C, methanol-to-oil molar ratio of 12:1, catalyst concentration of 1.5% w/w and stirring rate of 125 rpm. The fuel properties and fourier transform infra-red (FTIR) spectrum of the biodiesel obtained at optimum condition were mostly found to be in conformity with the ASTM D6751 and EN 14214 specification standards.

The mole ratio of an acid base reaction is one of the important values to state the stoichiometric relationship between acids and bases. However, solving acid-base problems based on stoichiometry is still challenging for new chemists.This issue renders the use of a model for predicting the volume of the acid used an exciting endeavour in academia. This work was to study the individual and interactive effects of the titration parameters such as acid concentration, base concentration and the number of the indicator drops on the volume of acid used in the titration process, using methyl orange as an indicator.We also aimed to study the central composite design (CCD) model of response surface methodology (RSM) for experimental design and modelling of the process. The experimental data were analysed using analysis of variance (ANOVA) and fitted to a second-order polynomial equation using multiple regression analysis. The regression analysis showed a good fit of the experimental data to the second-order polynomial model with a coefficient of determination (R2) value of 0.9751 and model F-value of 43.37. The response surface and contour plots were generated from RSM tool for the interactive effects of the studied parameters on the volume of acid used. The developed model was further validated using existing acid-base titration problems from the Senior Secondary Certificate Examination (SSCE) past questions over 30 years. All observations indicated that the developed model was only valid for a monobasic acid.