Aplicação de técnicas de modelagem e simulação para a produção de etanol de segunda geração

• Autor(a) principal: Montaño, Inti Doraci Cavalcanti
• Data de Publicação: 2013
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Repositório Institucional da UFSCAR
• Texto Completo: https://repositorio.ufscar.br/handle/ufscar/3938
• topic: Engenharia química; Hidrólise enzimática; Bagaço de cana; Modelo metabólico; Xilulose; Saccharomyces cerevisiae; Celulose; Biorreator; Batelada alimentada; Xilose; Modelo metabólico em escala genômica; Enzymatic hydrolysis; Cellulose; Sugarcane bagasse; Bioreactor; fed batch; Xylose; Genome-scale metabolic model; ENGENHARIAS::ENGENHARIA QUIMICA

The use of fossil fuels has a significant impact on the environment, making biofuels a renewable and friendly alternative. Brazil, as one of the leading producers of sugar and ethanol, generates as main residue sugar cane bagasse, which is usually burned for power generation. However, this biomass can be reused as raw material for the production of second generation bioethanol (2G). The consolidation of the industrial production of second-generation (2G) bioethanol relies on the improvement of the economics of the process. Thus, it is important the use of both the fermentable fractions present in sugarcane bagasse, cellulose (C6) and hemicellulose (C5), for the economically feasible process. Within this general scope, the second chapter of this thesis addresses one aspect that impacts the costs of the biochemical route for producing 2G bioethanol: defining optimal operational policies for the reactor running the enzymatic hydrolysis of the C6 biomass fraction. A simple Michaelis Menten pseudo-homogeneous kinetic model with product inhibition was used in the dynamic modeling of a fed-bath reactor, and two feeding policies were implemented and validated in bench-scale reactors processing pre-treated sugarcane bagasse. The first policy was defined with the purpose of sustaining high rates of glucose production, adding enzyme (Accellerase® 1500) and substrate simultaneously during the reaction course. The second approach applied classical optimal control theory, for determining optimal substrate feeding profiles, in order to maximize the performance index proposed. Economical criteria were used for comparing the reactor performance operating in successive batches and in fed-batch modes. Fed-batch mode was less sensitive to enzyme prices than successive batches. Process intensification in the fed-batch reactor led to final glucose concentrations around 200 g/L. The third chapter, in turn, focuses on the xylose utilization, the main sugar found in the C5 fraction, for fermentation to ethanol by yeast Saccharomyces cerevisiae. Although this yeast is not capable of fermenting xylose, it is able to ferment D-xylulose obtained by isomerisation of xylose by glucose isomerase enzyme, generating ethanol and/or xylitol as the main products. The optimization of ethanol production requires the analysis of the metabolism of xylulose. In this context, the genome-scale metabolic model iND750 was adjusted. In silico experiments were carried out using the software OptFlux and compared with experimental data of batch cultivation of S. cerevisiae, in order to validate the model and establishing relationships between fluxes of assimilating xylulose and oxygen and selectivity in the production of ethanol compared to xylitol. Experiments of simultaneous isomerization and fermentation (SIF) of xylose were carried out in a continuous bioreactor containing alginate pellets as biocatalyst with enzyme glucose isomerase and S. cerevisiae coimobilizated. Final concentrations of 6 g/L of ethanol and 5 g/L of xylitol were achieved in continuous cultivation.