Improved mathematical model of dark fermentation for enhanced biofuels production with zinc supplementation

Abstract

Various are the detrimental impacts on the environment as well as on human beings when burning fossil fuel for energy purposes. This has led to great interests in alternative energy sources as prime solution. Lignocellulosic biomass is considered to be the major biological renewable energy source for biofuels production. Lignocelluloses are plentiful, naturally found and require simple processing. To this end, microbial fermentation systems have seen potential gains for the generation of biofuels. Biomass contains different mixed sugars and it can serve as promising substrate in fermentation processes like AcetoneButanol-Ethanol (ABE) dark fermentation. Moreover, the addition of zinc in ABE fermentation plays a substantial role in genetic modifications and the regulation of specific enzymes of the metabolic pathway which leads to enhanced production of biofuels. In order to predict the behavior of each carbohydrate and thus find the optimum conditions in ABE fermentation, a predictive mathematical model of ABE dark fermentation was developed in this study. This model serves to follow the dynamic progression of three different carbohydrates used as sole carbon source namely xylose, arabinose and glucose found in lignocelluloses. The model was simulated under seven scenarios with and without supplementary zinc and then validated with different experimental data. Sensitivity analysis, parameter scan and parameter estimation were performed in order to fit best the experimental data. The simulated results of this model show compliance with the experimental results. Each carbohydrate showed enhanced consumption rates under supplementary zinc and therefore higher level of solvents. However, more studies can be conducted based on this built model in order to predict the optimum conditions for the combination of all three carbohydrates to come up with a comprehensive mathematical lignocellulose model.