https://repositorio.ufba.br/handle/ri/2612 2026-05-17T05:58:15Z 2026-05-17T05:58:15Z Melo, Luciana Lima https://repositorio.ufba.br/handle/ri/44432 2026-04-29T18:48:32Z 0002-02-27T00:00:00Z

Título: Modificação da fibra da luffa cylindrica (l. aegyptiacal) com ácidos graxos para aplicação como biossorvente de óleo diesel Autor(es): Melo, Luciana Lima Primeiro Orientador: Vidal, Rosangela Regia Lima Abstract: The high demand for and widespread use of petroleum and its derivatives, such as diesel oil, across various economic sectors have caused significant impacts on the environment and human health. In the environment, these compounds have become major pollutants, primarily due to spills. In this context, sorption processes emerge as a promising alternative for removing oily pollutants from water, underscoring the need for biodegradable, low-cost, and highly efficient materials. Luffa cylindrica fiber (vegetable sponge) shows potential as a biosorbent due to its porous structure and mechanical stability. However, its sorptive capacity still requires improvement. Thus, this work proposes the surface modification of Luffa cylindrica fiber with fatty acids (lauric, palmitic, stearic, oleic, and linoleic acids) to increase its affinity for oily compounds. The main objective was to evaluate the effect of these modifications on the sorption capacity of diesel oil. Sample characterization was performed using Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and thermogravimetric analysis (TGA). Sorption studies were conducted by varying sorbent mass, process time, agitation speed, and temperature. Batch experiments were carried out using reference systems (diesel oil, distilled water, or saline water) and systems containing diesel oil spilled into distilled or saline water. The results indicated that oleic acid modification provided the most significant increase in diesel oil sorption capacity among the evaluated systems. The pseudo-second-order model showed the best fit to the kinetic data, indicating that the process is controlled by surface interactions. The predominant mechanism is driven primarily by hydrophobic interactions and van der Waals forces, reflecting the nonpolar affinity between diesel oil and the modified fiber surface. It is concluded that modifying Luffa cylindrica fiber with oleic acid increases its hydrophobicity and sorption efficiency, highlighting the material's potential for oil spill remediation. Editora / Evento / Instituição: Universidade Federal da Bahia Tipo: Dissertação

0002-02-27T00:00:00Z Medeiros, Ravena Maria de Almeida https://repositorio.ufba.br/handle/ri/44288 2026-03-24T19:37:22Z 2025-03-14T00:00:00Z

Título: Otimização do cultivo de chlorolobion braunii em associação de concentrado salino e água salobra: um bioprocesso para obtenção de biomassa e produção de biodiesel Autor(es): Medeiros, Ravena Maria de Almeida Primeiro Orientador: Cardoso, Lucas Guimarães Abstract: Effluents used as a culture medium for microalgae represent a strategy that combines wastewater treatment—promoting nutrient removal—with the generation of high value-added biomass. The ability of microalgae to accumulate lipids and carbohydrates in their biomass makes them a promising source for biofuel production. The aim of this study was to optimize the production and characterize the biomass of the microalga Chlorolobion braunii using a combination of brackish water and saline concentrate, a condition not previously explored. In addition, the potential of this biomass for biodiesel production was evaluated. The experiments were carried out in Erlenmeyer-type bioreactors (1 L), and the best biomass production condition was determined using a central composite rotational design with the following factors: volume of saline concentrate in brackish water (0–100%) and urea concentration (0.00– 0.08 g/L). The optimized condition was defined as 36.6% saline concentrate, 63.4% brackish water, and 0.02 g/L urea. The best treatment was the experiment with 50% brackish water and 50% saline concentrate, which produced 0.556 g/L of biomass with an average productivity of 0.014 g/L/day, and high levels of biomolecules such as 21.14% carbohydrates and 29.40% lipids. It also achieved bioremediation of 86.25% of nitrates (NO₃⁻), 79.17% of phosphates (PO₄³⁻), and a 23.18% reduction in salinity. The biomass showed high fatty acid content, with 24.94% C16:0 (palmitic acid) and 38.44% C18:1n9c (oleic acid), producing biodiesel that meets the quality standards of the American Society for Testing and Materials (ASTM D6751) and the Brazilian National Agency of Petroleum, Natural Gas and Biofuels (ANP). This study optimized the biomass production of Chlorolobion braunii and demonstrated the feasibility of using only a combination of brackish water and saline concentrate—without prior treatment and without the addition of synthetic medium—resulting in high levels of biomolecules that can serve as feedstock for the generation of high value-added bioproducts. Editora / Evento / Instituição: Universidade Federal da Bahia Tipo: Dissertação

2025-03-14T00:00:00Z Santos, Vivian Lima dos https://repositorio.ufba.br/handle/ri/44130 2026-02-27T18:00:58Z 2026-01-14T00:00:00Z

Título: Otimização da transesterificação do óleo de rícino utilizando aprendizagem de máquina Autor(es): Santos, Vivian Lima dos Primeiro Orientador: Santos, Luiz Carlos Lobato dos Abstract: The global demand for energy and the environmental impacts associated with fossil fuels have driven the search for renewable sources, with a highlight on biodiesel. Castor oil (Ricinus communis L.) is a promising raw material because it is non-edible and has adaptable cultivation, although its transesterification faces common process challenges. In this context, machine learning (ML) emerges as a tool to model and optimize this complex and non-linear process. The general objective of this work was to develop and compare the performance of different ML architectures for the predictive modeling and optimization of the operational parameters of the homogeneous transesterification of castor oil, aiming to maximize biodiesel yield. Six architectures were analyzed: Multilayer Perceptron (MLP-logsig and MLP-tansig), Radial Basis Function Network (RBF), a hybrid model (RBF+MLP), Random Forest (RF), and Adaptive Neuro-Fuzzy Inference System (ANFIS), using a database of 406 labeled experimental sets from the literature. The models were evaluated using metrics such as the correlation coefficient (R), mean square error (MSE), and root mean square error (RMSE). The MLP-tansig model demonstrated the best predictive performance, with R > 0.98 in all phases and a test RMSE of 3.03%. For the reverse optimization stage, a Genetic Algorithm (GA) was coupled to the models, and the GA-RBF combination yielded the operational conditions most consistent with the literature, despite the superior point prediction performance of the MLP-tansig model: basic catalyst, alcohol/oil molar ratio of 19.35:1, catalyst concentration of 1.13% (w/w), temperature of 49.91 °C, reaction time of 70.44 min, and stirring at 548.32 rpm, achieving a predicted yield of 100% methyl esters. It is concluded that the proposed methodology is robust and effective, integrating artificial intelligence into process engineering to optimize biodiesel production, with potential application to other biomasses. Editora / Evento / Instituição: Universidade Federal da Bahia Tipo: Dissertação

2026-01-14T00:00:00Z Silva, Diniz Alves de Sant'Ana https://repositorio.ufba.br/handle/ri/43072 2025-09-29T16:46:13Z 2024-04-10T00:00:00Z

Título: Avaliação das tecnologias e potencial econômico para produção de ácido bio succinico Autor(es): Silva, Diniz Alves de Sant'Ana Primeiro Orientador: Pontes, Luis Antônio Magalhães Abstract: Succinic acid (SA), also known as butanedioic acid, has been used as a raw material in the food and pharmaceutical industries, in addition to its potential utilization in the production of biodegradable polymeric materials such as polybutene succinate, polyamides, and green solvents, as well as plasticizers, paints, and varnishes. Despite the petrochemical route currently accounting for about 97% of the total production of succinic acid, production using biomass as a feedstock has become competitive in light of petroleum price fluctuations and global concerns about the use of fossil-based raw materials and their impact on greenhouse gas emissions. This research evaluated the routes for obtaining biosuccinic acid from biomass, including the necessary pretreatment to make the material available for fermentation, the synthesis technologies of BioSA using various microorganisms, and the proposition of a separation and purification process to obtain the product with adequate purity. Simultaneously, the study assesses the global market, analyzing opportunities and threats for BioSA production routes as a substitute raw material for the production of 1,4-butanediol (BDO) and polybutylene succinate (PBS), and as a substitute for maleic anhydride, indicating its competitive advantage and key production bottlenecks. Several microorganisms have been studied and analyzed in BioSA production. Escherichia coli and Actinobacillus succinogenes show the greatest potential for the fermentation process, being the microorganisms with the highest number of patents and research works conducted, and therefore, they should be the focus of our studies regarding optimal conditions to increase BioSA yield and productivity. The main competitors operating in the global biosuccinic acid market include BioAmber, Reverdia, and Succinity, as well as other companies investing in research and development of new technologies for biosuccinic acid production. It is expected that the market will continue to thrive in the coming years, with growth forecasts of approximately 6,0% per year until 2027. Editora / Evento / Instituição: Universidade Federal da Bahia Tipo: Tese

2024-04-10T00:00:00Z