RESUMO
Among the steps for the conversion of biomass into bioenergy, there is enzymatic hydrolysis. However, factors such as composition, formation of inhibitors, inhibition and enzymatic deactivation can affect the yield and productivity of this process. Lignocellulosic biomass is composed of cellulose, hemicellulose and lignin. However, lignin is organized in a complex and non-uniform way, promotes biomass recalcitrance, which repress the enzymatic attack on cellulose to be converted into glucose, and, consequently, the production of biofuel. Thus, a challenge in enzymatic hydrolysis is to model the reaction behavior. In this context, this study aims to evaluate the performance in enzymatic hydrolysis for the conversion of cellulose present in sugarcane bagasse into glucose. Therefore, modeling and optimization will be proposed to produce high glucose concentration rates. Therefore, a previously developed study will be used, in which the authors proposed a kinetic model for the hydrolysis step. However, as a differential to what has been proposed, the calculation will be carried out evaluating the evaporation, in order to maximize the response to the glucose concentration. Thus, considering evaporation and optimized kinetic parameters, it was possible to obtain high rates of glucose concentration at 204.23 $g.L^{-1.
Assuntos
Celulose , Saccharum , Lignina , Biocombustíveis , Biomassa , GlucoseRESUMO
Proper simulation of processes of the natural gas industry such as dehydration, liquefaction and regasification require accurate prediction of thermodynamic properties of the working fluids. For such processes, cubic equations of state are the calculation methods most frequently employed. Among them, the Peng-Robinson equation is usually the one recommended for gas, refinery and petrochemical applications in many simulators. Numerous works have been proposed in order to improve the temperature dependence relation of the attraction parameter of the equation - the so called alpha function. In this work, five currently available alpha functions are evaluated for the prediction of molar volumes and enthalpies of natural gas samples. Additionally, parameters of one of the models are readjusted to volumetric data of methane, in order to represent its supercritical behavior more accurately. Experimental data of 44 mixtures are compared with calculated results. Van der Waals mixing rules are used, with binary interaction parameters set as zero. In the case of the original alpha function, it is also tested how the inclusion of non-zero binary parameters affects the predictions. The extended Saffari-Zahedi model presents the smallest average deviation for the molar volumes (1.35%). For the enthalpy calculation, the inclusion of the binary parameters results in deviation values of 2.62% for gas-gas transitions and 4.44% for gas-liquid transitions.