Modelling of in-situ real-time monitoring of catalysed biodiesel production from sunflower oil using fourier transform infrared

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Mwenge, Pascal Kilunji
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Vaal University of Technology
The industrialisation of the twenty-first century and the worldwide population growth led to the high demand for energy. Fossil fuels are the leading contributor to the global energy, and subsequently, there is a high demand of fuels. The decrease of global fossil fuels and the environmental air pollution caused by these fuels are concerning. Therefore, eco-friendly and renewable fuel such as biodiesel is one the leading alternative. Chromatography and Spectroscopy are the most used analytical methods and proven reliable but are time-consuming, requires qualified personal, extensive samples preparation, costly and do not provide in-situ real-time monitoring. Fourier Transform Infrared (FTIR) has mainly been used for qualitative analysis of biodiesel, but not much work has been reported in real-time monitoring. This study focused on the modelling of in-situ real-time monitoring of the biodiesel production from sunflower oil using FTIR (Fourier Transform Infrared). The first part of the study investigated the effect of catalyst ratio and methanol to oil ratio on biodiesel production by using central composite design (CCD). Biodiesel was produced by transesterification using Sodium Hydroxide as a homogeneous catalyst. A laboratory-scale reactor consisting of; flat bottom flask mounted with a reflux condenser, a hot plate as heating element equipped with temperature, timer and stirring rate regulator was used. Key parameters including, time, temperature and mixing rate, were kept constant at 60 minutes, 60 oC and 600 RPM, respectively. From the results obtained, it was observed that the biodiesel yield depends on catalyst ratio and methanol to oil ratio. The highest yield of 50.65 % was obtained at a catalyst ratio of 0.5 wt% and methanol to oil mole ratio 10.5. The analysis of variances of biodiesel yield showed the R2 value of 0.8387. A quadratic mathematical model was developed to predict the biodiesel yield in the specified parameters range. The same set-up was used to produce waste margarine biodiesel using a homogeneous catalyst, potassium hydroxide (KOH). The effects of four reaction parameters were studied, these were: methanol to oil ratio (3:1 to 15:1), catalyst ratio (0.3 to 1.5 wt. %), temperature (30 to 70 oC), time (20 to 80 minutes). The highest yield of 91.13 % was obtained at 60°C reaction temperature, 9:1 methanol to oil molar ratio, 0.9 wt. % catalyst ratio and 60 minutes. The important biodiesel fuel properties were found to be within specifications of the American Standard Test Method specifications (ASTM). It was concluded that waste margarine can be used to produce biodiesel as a low-cost feedstock. The core of the study was performed using EasyMax Mettler Toledo reactor equipped with a DiComp (Diamond) probe. The quantitative monitoring of the biodiesel production was performed by building a quantitative model with multivariate calibration using iC Quant module from iC IR 7.0 software. Fourteen samples of known concentrations were used for the modelling which were taken in duplicate for model calibration and cross-validation, data were pre-processed using mean centring and variance scale, spectrum math square root and solvent subtraction. These pre-processing methods improved the performance indexes from 7.98 to 0.0096, 11.2 to 3.41, 6.32 to 2.72, 0.9416 to 0.9999, RMSEC, RMSECV, RMSEP and R2Cum, respectively. The R2 values of 1 (training), 0.9918 (test), 0.9946 (cross-validation) indicated the fitness of the model built. The model was tested against the univariate model; small discrepancies were observed at low concentration due to unmodelled intermediates but were quite close at concentrations above 18%. The software eliminated the complexity of the Partial Least Square (PLS) chemometrics. It was concluded that the model obtained could be used to monitor transesterification of sunflower oil at industrial and lab scale. The model thus obtained, a batch reactor setup, EasyMax Mettler Toledodo reactor was used, the experiments were designed and monitored using iControl software. The results were recorded and quantified using iC IR software based on the biodiesel calibrated monitoring model built. The optimisation of the biodiesel was performed using three key parameters (methanol to oil ratio, catalyst ratio and temperature) while keeping time at 60 minutes and mixing rate at 150RPM. The highest yield of 97.85 % was obtained at 60 oC, 0.85 wt % catalyst ratio and 10.5 methanol to oil mole ratio. The analysis of variances of biodiesel production showed the values of 0.9847, 0.9674 and 0.8749, for R-squared, adjusted R-squared and predicted R-squared, respectively. A quadratic mathematical model was developed to predict the biodiesel conversion in the specified parameters ranges. Using the Arrhenius equation, activation energy (Ea) and frequency factor were found to be 41.279 kJ.mole-1 and 1.08 x10-4 M-1. s-1, respectively. The proposed kinetics model was a pseudo-first-order reaction. It was concluded that the model obtained can be used for industrial and laboratory-scale biodiesel production monitoring.
M. Tech. (Department of Chemical Engineering, Faculty of Engineering and Technology), Vaal University of Technology.
Biodiesel, Calibration, Catalyst, Chemometrics, Fourier Transform Infrared (FTIR), Kinetics, Multivariate analysis, Optimisation, Real-time monitoring, Transesterification