Mestrado em Química
URI Permanente para esta coleção
Nível: Mestrado Acadêmico
Ano de início: 2006
Conceito atual na CAPES: 5
Ato normativo: Homologação da 85ª Reunião do CTC-ES, Parecer CNE/CES nº 163/2005.
Processo nº 23001.000081/2005-56 do Ministério da Educação.
Publicado no DOU 28/07/2005, seção 1, página 11)
Periodicidade de seleção: Anual
Área(s) de concentração: Química
Url do curso: https://quimica.vitoria.ufes.br/pt-br/pos-graduacao/PPGQ/detalhes-do-curso?id=954
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- ItemAvaliação da dispersão química de petróleos e óleos intemperizados utilizando o teste de eficiência de dispersibilidade pelo método SFT(Universidade Federal do Espírito Santo, 2025-01-01) Amaral, Amanda Souza; Co-orientador1; https://orcid.org/; https://buscatextual.cnpq.br; Orientador1; https://orcid.org/; https://buscatextual.cnpq.br; https://orcid.org/; https://buscatextual.cnpq.br; 1º membro da banca; https://orcid.org/; https://buscatextual.cnpq.br; 2º membro da banca; https://orcid.org/; https://buscatextual.cnpq.br; 3º membro da banca; https://orcid.org/; https://buscatextual.cnpq.brOil spill-related environmental disasters pose significant threats to marine and coastal ecosystems, demanding mitigation strategies capable of ensuring fast and effective responses. Among the main response techniques, the use of chemical dispersants stands out for its ability to reduce interfacial tension between oil and water, thereby facilitating the formation of smaller oil droplets that are more prone to biodegradation. The efficiency of this approach depends both on the oil’s dispersibility and on environmental factors such as wind and ocean currents. This dispersibility, in turn, varies according to the chemical composition and physicochemical properties of each type of crude oil. In this study, the Swirling Flask Test (SFT), a widely used method required by regulatory agencies, was applied to evaluate the dispersion efficiency of the commercial dispersants Corexit EC9500A and Finasol OSR 52 across different samples of crude and weathered oils. The analyses included measurements of density, viscosity, resin content, asphaltene content and SAP+A fraction. Dispersion efficiency was determined based on the amount of hydrocarbons dispersed, which is directly influenced by the oil's physicochemical properties. This assessment is crucial for devising effective response strategies that enhance containment measures and protect environmentally sensitive areas. The results indicated that the API gravity and chemical composition of the oils significantly influenced dispersion performance, with water salinity being the most impactful environmental parameter. Additionally, statistical techniques such as linear regression and principal component analysis (PCA) were applied to identify correlations and patterns. The findings reinforce the relevance of the SFT as a technical tool for contingency planning and for the informed selection of dispersants based on oil type and environmental conditions.
- ItemDesenvolvimento e validação de um método de quantificação de canabinoides em produtos apreendidos e matrizes medicamentosas por Cromatografia líquida de alta eficiência acoplada à Espectrometria de Massas (UHPLC-MS)(Universidade Federal do Espírito Santo, 2025-03-07) Almeida, João Victor Macedo de; Santos, Nayara de Araujo dos; https://orcid.org/0000-0003-2754-2013; https://buscatextual.cnpq.br; Romão, Wanderson ; https://orcid.org/0000-0002-2254-6683; http://lattes.cnpq.br/9121022613112821; https://orcid.org/0009-0004-7879-651X; http://lattes.cnpq.br/9363882066586198; Kuster, Ricardo Machado; https://orcid.org/; https://buscatextual.cnpq.br; Chaves, Andrea Rodrigues ; https://orcid.org/0000-0002-8961-5348; http://lattes.cnpq.br/4149814906786366Cannabis sativa L. is an ancient species cultivated for various applications, including recreational and medicinal use. Nowadays, the demand for its products has grown significantly, leading to an increase in the search for medicinal oils and a rise in smuggling, making it the main trafficked drug. In this context, our work optimized the extraction process of CBD, CBN, CBC, CBDA, Δ9-THC e Δ9-THCA in oil Cannabis and marijuana samples, varying solvent, sonication and vortex agitation time, as well as validated a determination method for seven cannabinoids using Ultra-Performance Liquid Chromatography coupled with low-resolution Mass Spectrometry (UHPLC-LTQ-MS), according to the RDC 166 of 2017 guidelines. The optimization showed that ethyl acetate was the most suitable solvent for oil extraction. For the marijuana sample, the extraction was performed with ethyl acetate as the solvent, using sonication and vortex agitation for 10 and 7.5 minutes, respectively. No matrix effect was observed in the presented method, and LOQ ranged between 1 and 5 ng. mL⁻¹, and LOD between 0.3 and 1.5 ng. mL⁻¹. Recovery ranged from 84.6 to 107.6% in oil and 80.6 to 105.9% in marijuana. Precision was evaluated in three ways: within a single day (RSD: 3.14–10.87% in oil, 3.25–10.14% in marijuana), across different days with a second analyst (RSD: 1.98–10.71% in oil, 4.65–12.81% in marijuana), and laboratories with a third analyst (RSD: 5.59–13.94% in oil, 4.65–13.56% in marijuana). The proposed method offers high sensitivity, selectivity, and precision, being adequate and satisfactory for quantifying CBD, CBN, CBC, CBDA, Δ⁹-THC, and Δ⁹-THCA
- ItemDesenvolvimento de uma metodologia eletroanalítica para classificação de bebidas do café arábica usando um protótipo de potenciostato multicanal lab-made(Universidade Federal do Espírito Santo, 2025-03-13) Silva , Tárcila Mathiasso Nascimento da; Ferreira, Rafael de Queiroz ; https://orcid.org/0000-0002-5190-8508 ; http://lattes.cnpq.br/5053247764430323; https://orcid.org/0009-0007-9040-6168; http://lattes.cnpq.br/4931631664124833 ; Rosa, Thalles Ramon; https://orcid.org/0000-0001-9913-5885; http://lattes.cnpq.br/2629035369494897; Filgueiras, Paulo Roberto; https://orcid.org/0000-0003-2617-1601 ; http://lattes.cnpq.br/1907915547207861Arabica coffee is widely traded and recognized for its high quality. Before reaching the final consumer, Arabica coffee undergoes a rigorous sensory evaluation by qualified professionals known as Q-graders. This analysis classifies coffee into “Finas” and “Fenicadas” beverages and plays a crucial role in determining the commercial value of the coffee. Given that the quality of the beverage is directly related to its chemical composition, this study describes the development of an electroanalytical methodology combined with chemometrics for the classification of Arabica coffee beverages. Cyclic voltammetry was used in conjunction with commercially available gold screen-printed electrodes (BT250). The electrodes underwent a cleaning and conditioning process to reduce operating costs and enhance stability using 0.5 mol L−1 H2SO4. Voltammetric data from 210 Arabica coffee samples were analyzed using partial least squares discriminant analysis (PLS-DA). The training set produced excellent metrics, with an error rate of only 7%. The external test set showed an error rate of 12%. Parallel to this methodology, a lab-made multichannel potentiostat prototype was developed, designed with an exclusive electronic circuit and a structure manufactured using 3D printing. The equipment features 10 channels, allowing for consecutive analyses. The methodology applied in the benchtop potentiostat was also implemented in this prototype. The results obtained for the training set indicated an error rate of 4.77%, while the test set recorded an error rate of 22%. The expectation is that the prototype will achieve metrics comparable to those obtained with the conventional benchtop potentiostat. The results indicate a promising future for the integration of voltammetric and chemometric techniques in the classification of Arabica coffee beverages.
- ItemMétodos de aprendizagem de máquina aplicados à ciência do petróleo(Universidade Federal do Espírito Santo, 2025-03-17) Barboza, Maria Carolina da Vitória Alvarenga; Ferreira, Rafael de Queiroz; https://orcid.org/0000-0002-5190-8508; http://lattes.cnpq.br/5053247764430323 ; Filgueiras, Paulo Roberto; https://orcid.org/0000-0003-2617-1601; http://lattes.cnpq.br/1907915547207861; https://orcid.org/0009-0007-7744-4434; http://lattes.cnpq.br/6535362149640541 ; Oliveira, Emanuele Catarina da Silva; https://orcid.org/0000-0003-0699-6104; http://lattes.cnpq.br/1715851915787164 ; Souza, Murilo de Oliveira; https://orcid.org/0000-0002-5299-564X; http://lattes.cnpq.br/1832643912229312This study aims to present a new machine learning approach to classify crude oil samples based on their physicochemical properties, such as sulfur (S) concentration, total acid number (TAN), and API gravity (American Petroleum Institute). Crude oil is a complex mixture predominantly composed of carbon and hydrogen substances, along with heteroatomic elements such as nitrogen, oxygen, and sulfur. This complexity makes precise analysis essential, especially to avoid problems throughout the production chain. Proposed method seeks to overcome the limitations of traditional techniques, which are often time-consuming, require large sample volumes, and use excessive solvents. As a promising alternative, spectroscopic techniques have been employed for crude oil characterization, and machine learning methods have demonstrated high efficiency in analyzing complex mixtures. These methods offer faster and more accurate exploration of chemical variability compared to conventional approaches. This study, 196 crude oil samples, varying in sulfur content, TAN, and API gravity, were analyzed. The use of SVM (Support Vector Machine) ensembles was explored as a powerful approach to improve classification performance by reducing the variability of individual models, increasing robustness against overfitting, and enabling better generalization than a single model. To evaluate performance, criteria such as sensitivity, specificity, error rate, Matthews correlation coefficient, and accuracy were used, comparing SVM ensemble models with PLS-DA and standard SVM. The results demonstrated that the combination of NIR spectroscopy (Near Infrared Spectroscopy) with SVM ensemble models is an efficient and reliable method for the simultaneous qualification of sulfur content, TAN, and API gravity in crude oils. This is because SVM ensembles tend to perform better, reducing overfitting. Moreover, they create more robust models, reduce variance, and increase model stability.
- ItemUso de técnicas químicas avançadas para caracterização da identidade de méis de abelhas sem ferrão do Espírito Santo(Universidade Federal do Espírito Santo, 2025-03-13) Dias, Lucas Rodrigues de Oliveira; Ferreira, Rafael de Queiroz; http://lattes.cnpq.br/5053247764430323; Cunha Neto, Álvaro; https://orcid.org/0000-0002-1814-6214; http://lattes.cnpq.br/7448379486432052; http://lattes.cnpq.br/7422491599920966; Athayde, Geisamanda Pedrini Brandão; https://orcid.org/0000-0002-4315-0653; http://lattes.cnpq.br/8037324704189596; Morais, Verônica Santos de; https://orcid.org/0000-0002-7324-2057; http://lattes.cnpq.br/3680926664416715Stingless bee honey is considered a functional food due to the complex presence of chemical compounds with antioxidant properties. The chemical composition of honey is associated with several factors, such as the bee species, flowering, soil, and storage method. In this sense, this study investigated the chemical composition and antioxidant capacity of honey samples produced by Melipona species from different regions of the state of Espírito Santo - ES, Brazil. A comprehensive chemical characterization of each honey was conducted using advanced techniques, such as Fourier transform mid infrared spectroscopy (FT-MIR), gas chromatography-mass spectrometry (GC-MS), and nuclear magnetic resonance (NMR), combined with chemometric tools. The flavonoid and total phenolic contents of the honey samples were determined using TPC (total phenolic compounds) and TFC (total flavonoid content) methods. Finally, the total antioxidant capacity (TAC) of each stingless bee honey sample was evaluated using FRAP (ferric reducing antioxidant power), DPPH (2,2-diphenyl-1-picrylhydrazyl), and CRAC (ceric reducing antioxidant capacity) assays. The PCA (principal component analysis) model based on FT-MIR signals showed the separation between the honey samples of Melipona capixaba and Melipona quadrifasciata. Volatile organic compounds (VOCs) were detected by GC-MS, and the most abundant classes were carboxylic acids, ketones, aldehydes and alcohols. The classification using the PCA model based on partial GC-MS chromatograms allowed the visualization of the clusters of honey samples from Melipona capixaba and Melipona quadrifasciata. Simple phenols such as p-cresol and allyl guaiacol were also identified in the honey. In addition, the TPC and TFC contents had selective correlations with TAC. A high Pearson correlation was observed between TPC and the CRAC antioxidant assay. Thus, chemometrics combined with chemical information obtained from the use of advanced FT-MIR, GC-MS, and NMR techniques; and from TFC and TPC, CRAC, FRAP, and DPPH methods are comprehensive tools that allow tracing an identity aligned with the quality of stingless bee honey from ES.