Open Access

ARTICLE

Process Characterization of the Transesterification of Rapeseed Oil to Biodiesel Using Design of Experiments and Infrared Spectroscopy

Tobias Drieschner^1,2,*, Andreas Kandelbauer¹, Bernd Hitzmann², Karsten Rebner¹

1 Lehr-und Forschungszentrum Process Analysis and Technology (PA&T) der Hochschule Reutlingen, Reutlingen, 72762, Germany
2 Department of Process Analytics and Cereal Science, Institute of Food Science and Biotechnology, Universität Hohenheim, Stuttgart, 70599, Germany

* Corresponding Author: Tobias Drieschner. Email:

(This article belongs to the Special Issue: New Trends in Renewable and Sustainable Materials for Carbon Neutrality)

Journal of Renewable Materials 2023, 11(4), 1643-1660. https://doi.org/10.32604/jrm.2023.024429

Received 02 June 2022; Accepted 29 August 2022; Issue published 01 December 2022

Abstract

For optimization of production processes and product quality, often knowledge of the factors influencing the process outcome is compulsory. Thus, process analytical technology (PAT) that allows deeper insight into the process and results in a mathematical description of the process behavior as a simple function based on the most important process factors can help to achieve higher production efficiency and quality. The present study aims at characterizing a well-known industrial process, the transesterification reaction of rapeseed oil with methanol to produce fatty acid methyl esters (FAME) for usage as biodiesel in a continuous micro reactor set-up. To this end, a design of experiment approach is applied, where the effects of two process factors, the molar ratio and the total flow rate of the reactants, are investigated. The optimized process target response is the FAME mass fraction in the purified nonpolar phase of the product as a measure of reaction yield. The quantification is performed using attenuated total reflection infrared spectroscopy in combination with partial least squares regression. The data retrieved during the conduction of the DoE experimental plan were used for statistical analysis. A non-linear model indicating a synergistic interaction between the studied factors describes the reactor behavior with a high coefficient of determination (R^²) of 0.9608. Thus, we applied a PAT approach to generate further insight into this established industrial process.

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Keywords

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