Modelling of thermal decomposition kinetics of proteins, carbohydrates and lipids using Scenedesmus microalgae thermal data

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Abstract

In present work, the thermal decomposition behaviour and kinetics of proteins, carbohydrates and lipids is studied by use of models derived from mass-loss data obtained from thermogravimetric analysis of Scenedesmus microalgae. The experimental results together with known decomposition temperature range values obtained from various literature were used in a deconvolution technique to model the thermal decomposition of proteins, carbohydrates and lipids. The models fitted well (R2 > 0.99) and revealed that the proteins have the highest reactivity followed by lipids and carbohydrates. Generally, the decomposition kinetics fitted well with the Coats-Redfern first and second order kinetics as evidenced by the high coefficients of determination (R2 > 0.9). For the experimental conditions used in this work (i.e. high heating rates), the thermal decomposition of protein follows second order kinetics with an activation energy in the range of 225.3-255.6 kJ/mol. The thermal decomposition of carbohydrate also follows second order kinetics with an activation energy in the range of 87.2-101.1 kJ/mol. The thermal decomposition of lipid follows first order kinetics with an activation energy in the range of 45-64.8 kJ/ mol. This work shows that the thermal decomposition kinetics of proteins, carbohydrates and lipids can be performed without the need of experimentally isolating the individual components from the bulk material. Furthermore, it was shown that at high heating rates, the decomposition temperatures of the individual components overlap resulting in some interactions that have a synergistic effect on the thermal reactivity of carbohydrates and lipids.

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Nyoni, B., Tsipa, P., Duma, S., Shabangu, S., & Hlangothi, S. (2020). Modelling of thermal decomposition kinetics of proteins, carbohydrates and lipids using Scenedesmus microalgae thermal data. Asian Journal of Chemistry, 32(11), 2921–2926. https://doi.org/10.14233/ajchem.2020.22768

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