http://repositorio.ufc.br/handle/riufc/23501 Wed, 08 Apr 2026 13:28:16 GMT 2026-04-08T13:28:16Z http://repositorio.ufc.br/handle/riufc/85003 Título: Análise bibliométrica da produção do óxido de grafeno reduzido em aplicações energéticas Autor(es): Nogueira, Júlio de Souza Abstract: This work presents a bibliometric analysis of reduced graphene oxide (rGO), using data extracted from the Scopus database and processed through the R programming language with the support of the Bibliometrix and Biblioshiny packages. The study mapped the evolution of scientific production from 2012 to 2025, revealing continuous growth, strong interdisciplinarity, and broad geographical distribution, with notable contributions from India, China, and Korea. Publications are primarily focused on synthesis routes, material characterization, and technological applications, especially in electrochemical devices and perovskite solar cells. Network analyses identified three main thematic clusters: synthesis methodologies, electrochemical performance, and the integration of rGO in photovoltaic systems. The results also highlighted significant gaps, such as variability in synthesis routes, lack of standardization in characterization methods, and limited studies addressing long-term operational stability. The findings indicate that rGO is a promising and versatile material with increasing scientific relevance and strong potential for advanced technological applications; however, its consolidation requires methodological standardization, scalability assessments, and deeper investigations into device-level durability. Tipo: TCC Thu, 01 Jan 2026 00:00:00 GMT http://repositorio.ufc.br/handle/riufc/85003 2026-01-01T00:00:00Z http://repositorio.ufc.br/handle/riufc/84993 Título: Análise comparativa do impacto financeiro entre a migração para o mercado livre de energia e a instalação de usina fotovoltaica Autor(es): Costa, Wesley de Oliveira Abstract: The Brazilian electricity sector, in recent decades, has provided increasing freedom to consumers through the gradual opening of the free energy market and the regulation of distributed generation. Such factors have driven the expansion of renewable energy sources and have allowed consumers to produce their own energy or purchase energy from the source of their interest. In this way, the present study will use, as its methodology, the development of a case study of a food retail company with a contracted demand of 100 kW, and, based on the analysis of the energy consumption history of the consumer unit, a financial comparison will be carried out between distributed generation with the installation of a photovoltaic power plant and migration to the Free Energy Market, with the regulated market serving as the comparison criterion. To verify the savings that the investment in a solar power plant will bring to the establishment, the energy tariff values of the utility Enel CE in the year 2025 will be used to compare the amounts paid on the energy bill with and without distributed generation. As for the scenario of migration to the free market, after verifying the company’s eligibility and choosing the energy source that will supply it, the average energy prices of the free market in recent years, published by the CCEE, and the tariff discounts due to incentives for renewable energy power plants will be used in order to estimate the savings obtained from the migration. In view of these results, it will be assessed which investment proves to be more financially attractive based on metrics such as Net Present Value, Internal Rate of Return, and Payback. Tipo: TCC Thu, 01 Jan 2026 00:00:00 GMT http://repositorio.ufc.br/handle/riufc/84993 2026-01-01T00:00:00Z http://repositorio.ufc.br/handle/riufc/84988 Título: Produção de bioeletricidade a partir do efluente de altoforno por células de combustível microbianas Autor(es): Borges, Reginna Marjorye Carvalho Abstract: The utilization of non-renewable energy sources for power generation, the consequent emission of greenhouse gases, the water scarcity and the large volume of wastewater have had a significant impact on the environment in recent decades. The steel industry, in particular, is recognized as one of the most energy-intensive industries and a generator of complex wastewater, requiring technological innovations and public policies to encourage decarbonization. In this context, the development of bioelectrochemical systems such as Microbial Fuel Cells (MFCs) has gained visibility due to its ability to generate electricity in conjunction with waste treatment, allowing an economical and sustainable integration with industrial processes. This study aims to evaluate the efficiency of Microbial Fuel Cells (MFCs) in the treatment of an effluent from the Blast Furnace (AF) process in the steel industry, while simultaneously generating energy from two reactors, MFC-1 and MFC-2, developed at the Federal University of Ceará (UFC). The experiments lasted six months each, with a gradual increase in the percentage of AF effluent in each MFC. Electrochemical and chemical oxygen demand (DQO) tests were performed monthly. The results demonstrated that, despite the complex components of the effluent, both cells achieved stable voltage values up to 60% effluent usage (between 200 and 300 mV) and excellent organic matter removal values, with COD values exceeding 80% at AF concentrations up to 40%, demonstrating the viability of the technology for electrical efficiency and wastewater treatment. Tipo: TCC Thu, 01 Jan 2026 00:00:00 GMT http://repositorio.ufc.br/handle/riufc/84988 2026-01-01T00:00:00Z http://repositorio.ufc.br/handle/riufc/84963 Título: Revisão bibliográfica do uso de inteligência artificial em sistemas de energias renováveis Autor(es): Bezerra da silva, Pedro Felipe Abstract: The widespread integration of renewable energy sources into the grid raises significant technical challenges due to their intermittent and stochastic nature. This work investigates the application of artificial intelligence as a strategic tool to manage and optimize these systems through a literature review in the Scopus database, spanning the period from 2015 to 2024. The qualitative analysis of 40 selected publications allowed for the identification of established trends in the literature, highlighting a prevalence of applications directed towards solar and wind energy. It was found that deep learning methodologies have established themselves as the primary choice for generation forecasting and predictive maintenance; more precisely, the examined studies highlight the primacy of Long Short-Term Memory neural networks in managing the non-linearity of climate data, outperforming traditional statistical approaches. Within the context of predictive maintenance, Convolutional Neural Networks stand out as the ideal model for automatic defect identification. Concomitantly, the literature indicates that meta-heuristic optimization algorithms are fundamental for maximizing efficiency in photovoltaic and wind systems. However, this integration does not occur without facing challenges: the analysis signals technical limitations regarding data quality and availability, in addition to addressing the energy paradox inherent in training large-scale models and knowledge fragmentation. Future projections indicate the indispensability of more integrated strategies. It is concluded that artificial intelligence constitutes a transformative vector capable of accelerating the energy transition on a global scale; however, cooperation among researchers, the industrial sector, and policymakers is necessary to overcome the identified challenges. Tipo: TCC Thu, 01 Jan 2026 00:00:00 GMT http://repositorio.ufc.br/handle/riufc/84963 2026-01-01T00:00:00Z