Ciencias Exactas y Ciencias de la Salud
Permanent URI for this collectionhttps://hdl.handle.net/11285/551039
Pertenecen a esta colección Tesis y Trabajos de grado de las Maestrías correspondientes a las Escuelas de Ingeniería y Ciencias así como a Medicina y Ciencias de la Salud.
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- Applications of artificial neural networks for experimental design optimization of Chlorella vulgaris microalgae growth(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2022) Díaz Hernández, María Monserrat; CHAIREZ ORIA, JORGE ISAAC; 42787; dnbsrp; Parra Saldívar, Roberto; Escuela de Ingeniería y Ciencias; Campus Ciudad de México; Alfaro Ponce, MarielThis thesis proposes developing an optimization experimental model to optimize nutrient consumption and microalgae growth from the Novozymes company’s sidestream. The optimization model was created using the Box-Behnken experimental design for three factors. These three criteria were considered to raise the Chlorella v. biomass, and three different levels for each factor were chosen and implemented. The first factor chosen was CO2 since microalgae are important in producing energy for growth and proteins, lipids, and nucleoid acid. The second component chosen was agitation, which allows for the exchange of gases in the medium and the uniform consumption of nutrients from the medium. The day/night cycle was used to generate mixotrophic cultivation, which encouraged the culture to utilize the carbon in the sidestream while maintaining the green pigments of Chlorella vulgaris due to the presence of light. Following the experimentation phase, the best levels for each factor were 0.5% CO2, 70 RPM of agitation, and 8:16 hrs of day/night cycle. These amounts were used in a photobioreactor to cultivate and observe nutrient consumption behavior for eight days. Following these days, the COD level was reduced by 47.34%, the total nitrogen decrement was 48.70 %, the total phosphorus decrement was 96.42 %, and the dry biomass increased by 300 %. Simultaneously, a suitable neural network was designed to optimize the optimal levels for the same three parameters; this model was trained, validated, and evaluated using the experimental results. The ideal amounts for each factor were 0.5% CO2, 77 RPM of agitation, and 8:16 hours of day/night cycle. These levels were used in a photobioreactor to cultivate and observe nutrient consumption behavior for eight days. Following these days, the COD level declined by 40.80%, the total nitrogen decrement was 44.63%, the total phosphorus decrement was 98.65%, and the dry biomass increased by 400%. Both models are based on the work’s greatest contribution of reducing sidestream nutrients and promoting the increase in microalgae biomass in a shorter time than traditional methods that range from 12 to 14 days, as well as being a solution for treating wastewater from the enzyme manufacturing process.
- Evaluation of the external resistance, graphite and modified graphene as electrodes in microbial fuel cells for the improvement of wastewater treatment and power generation(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2021-06-15) Cámara Gutiérrez, Iris Cassandra; LOPEZ ZAVALA, MIGUEL ANGEL; 37056; López Zavala, Miguel Ángel; emipsanchez/puemcuervo; Montesinos Castellanos, Alejandro; Monárrez Cordero, Blanca Elizabeth; García Orozco, Jorge Humberto; School of Engineering and Sciences; Campus MonterreyCurrently, the constant increase of population and its not sustainable consumption has caused the depletion of water and actual sources of energy are not bast enough to meet the growing necessities. A proposed solution that tackles these problems resides in the application of renewable energy processes, such as the production of bioenergy through the treatment of wastewater by electrogenic bacteria in microbial fuel cells. This document presents the results of the thesis research, to obtain the degree of Master of Science in Engineering with a specialty on clean energy and sustainable water use. The objective of this work was to evaluate the external resistant and electrode materials (graphite and modified graphene) in a dual chamber microbial fuel cell for improving the wastewater treatment and electricity generation. Through this investigation, different external resistances and two electrode materials were evaluated. The results obtained allow to identify the combination of operating conditions that give the best performance. A 10-fold increase in power output and a 20-fold increase in coulombic efficiency were obtained. This study shows a cost-effective way to improve power generation in microbial fuel cells, contributing to offering new clean renewable energy sources.