Orientadores: Francisco Maugeri Filho, Helen Treichel / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia de Alimentos / Made available in DSpace on 2018-08-14T15:38:41Z (GMT). No. of bitstreams: 1 Mazutti_MarcioAntonio_D.pdf: 2533224 bytes, checksum: 5aa67cc7c607161a5f135fc67eb66778 (MD5) Previous issue date: 2009 / Resumo: Nas últimas duas décadas houve um aumento considerável no emprego de fermentação em estado sólido (FES) para a obtenção de enzimas de interesse em alimentos, incluindo a inulinase. No entanto, todos os trabalhos reportados na literatura abordam a produção de inulinase em escala de bancada, usando poucos gramas de substrato. Essa estratégia de condução do processo é muito importante na etapa de seleção dos substratos e triagem dos microrganismos produtores. Porém, não permite a avaliação do desempenho do processo em escalas maiores. O objetivo desse trabalho foi investigar a produção de inulinase por FES num biorreator de leito fixo com capacidade para 3kg (base seca) usando a levedura Kluyveromyces marxianus NRRL Y-7571. Inicialmente, foi realizado um delineamento composto central rotacional (DCCR) para otimizar a massa inicial de células, a temperatura e a vazão do ar de entrada do biorreator. A partir dos resultados obtidos na otimização, foram realizados 7 experimentos em torno da região otimizada, visando a avaliação cinética do processo. Foram monitorados experimentalmente o consumo de açúcar redutor total (ART), a produção de dióxido de carbono (CO2) e a geração de calor metabólico. A produção de água metabólica, massa de células e etanol, além do consumo de oxigênio, foram calculados a partir de uma equação estequiométrica, tomando como base a produção de CO2 e o consumo de ART. Os dados obtidos na avaliação cinética foram usados para a geração de um modelo de crescimento da levedura Kluyveromyces marxianus NRRL Y-7571 em FES. Este modelo é baseado em redes neurais artificiais (RNA), onde são usadas como entradas para a rede a massa inicial de ART, temperatura do ar de entrada do biorreator, temperatura do ar de saída do biorreator e tempo de fermentação. Como respostas têm-se as taxas associadas com o crescimento da levedura Kluyveromyces marxianus, como a produção de CO2, calor metabólico, etanol, água metabólica, atividade da inulinase e massa celular, além das taxas de consumo de oxigênio (O2) e ART. Por fim, o modelo de crescimento microbiano foi acoplado ao balanço macroscópico de energia no biorreator com o objetivo de prever os perfis de temperatura ao longo do processo. Entre os resultados obtidos no DCCR tem-se que a máxima produção de inulinase obtida foi de 437±36 unidades por grama de substrato seco (U.gds-1) (produtividade de 18,2 U.gds-1.h-1) quando a temperatura do ar de entrada, vazão volumétrica de ar e massa de células foram 30°C, 2,2 m3.h-1 e 22 g, respectivamente. Na avaliação cinética do processo, foram verificadas diferenças nas taxas associadas ao crescimento microbiano entre as condições experimentais. O aumento da temperatura do ar de entrada mostrou ter influência no tempo onde as taxas máximas foram verificadas, sendo que quanto mais alta a temperatura menor foi esse tempo. A temperatura máxima obtida na corrente de ar na saída do biorreator atingiu valores próximos a 50°C, não afetando o teor de umidade do substrato, o qual se manteve acima de 65%. A produção de inulinase mostrou variações significativas com a altura do biorreator. As maiores taxas associadas com o crescimento microbiano foram verificadas quando a temperatura do ar de saída atingiu valores compreendidos entre 30¿38°C, o que corresponde a 4-9 horas de fermentação. O modelo matemático baseado em redes neurais empregado para predizer as principais taxas associadas ao crescimento da levedura K. marxianus em FES mostrou desempenho satisfatório na representação dos dados experimentais e ao acoplar esse modelo à equação de balanço de energia macroscópico do processo obteve-se uma representação satisfatória dos perfis de temperatura ao longo do biorreator / Abstract: In the last two decades there has been a considerable increase in the interest of using solid-state fermentation (SSF) for the development of several bioprocesses and products, including enzyme production, as the inulinase. Nevertheless, all works related in the literature regarding the inulinase production were conducted in small scales, using few grams of substrate. This strategy is interesting to select the most promising substrate and microorganisms, which are able to produce the desired product, but this scale is not appropriated for the evaluation of process performance in larger scales. This work evaluate the inulinase production by SSF in a packed-bed bioreactor with available capacity of 3 kg (dry basis) using the yeast Kluyveromyces marxianus NRRL Y-7571. Initially, it was evaluated the technical viability to produce inulinase by SSF in the packed-bed bioreactor. To optimize the operational conditions, such as temperature and flow rate of inlet air and the initial mass of cells, a central composite rotational design (CCRD) for three independent variables was carried out. Starting from the results obtained in the CCRD, seven new experimental runs were carried out within the range investigated for the independent variables to evaluate the kinetics of cell growth and inulinase production by Kluyveromyces marxianus NRRL Y-7571 in the packed-bed bioreactor. A stoichiometry correlation between CO2, ethanol, metabolic water, O2 and total reducing sugar was determined. Besides, the metabolic heat production was estimated by a proper energy balance in the inlet and outlet air stream. The data obtained during the kinetic evaluation of the process were employed on the development of a mathematical model based on artificial neural networks (ANN) to predict the above mentioned microbial rates associated with the microbial growth in function of the fermentation time, initial total reducing sugar concentration, inlet and outlet air temperatures. In the last step of the work, the model related to the microbial growth was coupled to the macroscopic energy balance in the bioreactor to predict the temperature profile through the substrate bed. The results obtained in the CCRD showed that the optimum inulinase production was 436.7±36.3 U.gds-1 at 24 h of fermentation (productivity of 18.2 U.gds-1.h- 1) when SSF was carried out at 30°C of air inlet temperature, 2.2 m3.h-1 of air flow rate and 22 g of cells. During the kinetic evaluation of the process it was verified that the manipulated variables affected the process performance. The maximum temperature reached in the outlet air stream was about 50°C, however not affecting the moisture content of the substrates that was higher than 65% (w/w) inside the bioreactor. The inulinase production showed significant variations in different bed heights inside the bioreactor. The highest microbial rates were verified when the mean temperature of moist substrate reached values in the range of 30 to 38°C that leads to a fermentation time between 4 to 9 hours. The model developed to predict the main microbial rates of the yeast K. marxianus grown in solid-state fermentation showed a good performance during both training and validation steps. The framework developed showed to be an interesting alternative to substitute the simple empirical microbial model in the macroscopic balance of energy in the bioreactor, since the proposed hybrid model predicted efficiently the temperature profiles through the bioreactor / Doutorado / Doutor em Engenharia de Alimentos

This work describes two phase field models for the simulation of the interface evolution between a LiCoO2 cathode (LCO) and a Li7La3Zr2O12 solid electrolyte (LLZO) in a Li-metal/LLZO/LCO battery during high temperature sintering. In these conditions atomic species tend to diffuse into the opposing material, creating an intermediate layer of mixed composition which resists the movement of lithium ions. This undesired effect prevents the resulting solid-state battery to achieve its theoretical performances and needs to be avoided. The first model is an adaptation of the work of J. M. Hu et alii [1] for a similar interface problem encountered between yttria-stabilized zirconia electrolytes (YSZ) and lanthanum-strontium-manganite cathodes (LSM) in solid oxide fuelcells (SOFC), while the second is based on the work of D. A. Cogswell [2][3] for phase separation in metal alloys, extended to include electrostatic effects due to internal charge unbalances and externally applied electric fields. Animplementation of the latter is however lacking, and the interested reader is encouraged to build one up on the theoretical framework presented in this paper. In the conclusion section it is possible to find insights on how to prevent the interfacial diffusion between LCO and LLZO with reference to experimental attempts and simulations, as well as future directions for the development of the models.

Friction bit joining (FBJ) is a new solid-state spot joining technology developed in cooperation between Brigham Young University of Provo Utah, and MegaStir Technologies of West Bountiful Utah. Although capable of joining several different material combinations, this research focuses on the application of FBJ to joining 5754 aluminum to DP 980 steel, two alloys commonly used in automotive applications. The thicknesses of the materials used were 0.070 inches (1.78 mm) and 0.065 inches (1.65 mm), respectively. The FBJ process employs a consumable 4140 steel bit and is carried out on a purpose built research machine. In the first stage of the weld cycle the bit is used to drill through the aluminum top sheet to be joined. After this, spindle speed is increased so that the bit tip effectively forms a friction weld to the steel bottom sheet. Momentary stoppage of the spindle facilitates weld cooling before the spindle is restarted, shearing the bit tip from the bit shank, and retracted. Incorporated into the bit tip geometry is a flange that securely holds the aluminum in place after joint formation is complete. This research consists of several developmental steps since the technology only recently began to be formally studied. Initial joint strengths observed in lapshear tensile testing averaged only 978.5 pounds (4.35 kN), with a relatively high standard deviation for the data set. Final lapshear tensile test results were improved to an average of 1421.8 pounds (6.32 kN), with a significantly lower, and acceptable, standard deviation for the data set. Similar improvements were realized during the development work in cross tension tensile test results, as average strengths increased from 255.8 pounds (1.14 kN) to 566.3 pounds (2.52 kN). Improvements were also observed in the standard deviation values of cross tension data sets from initial evaluation to the final data set presented in this work.