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MODELING AND EVALUATION OF DIFFERENT OPERATING PROCESS FOR PRE-TREATMENT, HYDROLYSIS AND FERMENTATION FOR 2G ETHANOL PRODUCTION

Grant number: 12/10857-3
Support type:Scholarships in Brazil - Post-Doctorate
Effective date (Start): September 01, 2012
Effective date (End): February 29, 2016
Field of knowledge:Engineering - Chemical Engineering - Chemical Process Industries
Principal researcher:Rubens Maciel Filho
Grantee:Laura Plazas Tovar
Home Institution: Faculdade de Engenharia Química (FEQ). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil

Abstract

The sugarcane bagasse (a byproduct generated by agribusiness in Brazilian ethanol production) is a renewable and economical alternative for the sustainable production of Second-Generation Biofuels (2G) and for electricity generation (cogeneration). Several steps comprise the process, including: pre-treatment, hydrolysis and fermentation and ethanol concentration related to the desired products (Anhydrous Ethanol vs. Hydrous Ethanol). The development of new technologies employed in the agricultural sector has brought with it an increase in productivity of sugarcane and obtaining by-products (the sugarcane bagasse and the straw). However, different technologies have been explored in recent years in order to hydrolyze the polysaccharides cellulose and hemicellulose to produce glucose and xylose, respectively. One of the major challenges involving the lignocellulosic ethanol production (2G) is the pre-treatment to remove of compositional and structural barriers of lignocellulosic materials, leading to an improvement in the percentage of hydrolysis and increasing yields of fermentable sugars (from cellulose and hemicellulose) efficient and economically viable.This project for postdoctoral position aims to develop deterministic models for the pretreatment and hydrolysis processes and unstructured nonsegregated models for the fermentation process, based on detailed kinetics and mass transfer phenomena by appropriate methodologies for their representation. It will be considered dynamic models. The numerical solution will be achieved by numerical approaches to solve the equations. Finally, it will be held on the validation of the developed models with experimental data obtained by: (1) experimental exercise carried out in the Laboratory of Optimization, Project and Advanced Control (LOPCA) and Laboratory of Research on Bioenergy (BIOEN) in the School of Chemical Engineering (State University of Campinas - UNICAMP) and in the Research Center at Michigan State University (MSU) in the case of AFEX process, developed by Dale (Jin et al., 2011; Bals et al., 2010); and (2) by data reported in the published literature.

Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
TOVAR, LAURA PLAZAS; RIVERA, ELMER CCOPA; MARIANO, ADRIANO PINTO; WOLF MACIEL, MARIA REGINA; MACIEL FILHO, RUBENS. Prediction of overall glucose yield in hydrolysis of pretreated sugarcane bagasse using a single artificial neural network: good insight for process development. JOURNAL OF CHEMICAL TECHNOLOGY AND BIOTECHNOLOGY, v. 93, n. 4, p. 1031-1043, APR 2018. Web of Science Citations: 1.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.