http://repositorio.ufc.br/handle/riufc/492 Thu, 25 Jun 2026 14:38:29 GMT 2026-06-25T14:38:29Z http://repositorio.ufc.br/handle/riufc/86883 Título: Biochar and biochar-bentonite composite from Carnauba (Copernicia prunifera) straw modified by high-energy ball milling: preparation, characterization, and methylene blue adsorption Autor(es): Silva, Laryssa Coutinho da Abstract: The conversion of agrowaste into engineered adsorbent materials represents a sustainable strategy for wastewater treatment. Biochar and biochar–clay composites were prepared from raw and dewaxed carnauba (Copernicia Prunifera) straw through high-energy ball milling (HEBM) and evaluated for methylene blue (MB) adsorption. Carbonization at 550 °C enriched fixed carbon and ash while reducing volatile matter. Dewaxed biochar (DCSB) exhibited higher carbon content (45.63 wt%) and a higher degree of carbonization compared to non-dewaxed biochar (CSB), leading to superior adsorption performance (Langmuir qm = 328.13 mg g-1 for DCSB vs. 255.70 mg g-1 for CSB). SEM analysis revealed that HEBM produced highly fragmented materials with a fine powder-like morphology, while FTIR and XRD analyses confirmed the preservation of the fundamental chemical structure and the predominantly amorphous character of the biochars. A material-dependent response to HEBM was observed: CSB required higher specific energy (26.46 kJ g-1 ) to reach its maximum adsorption capacity, whereas DCSB achieved its optimum at a much lower energy (7.86 kJ g-1 ), indicating that dewaxing alters the biochar's susceptibility to mechanochemical activation. Notably, bentonite- containing composites exhibited broader energy tolerance, maintaining high adsorption performance across a wide range of milling conditions, indicating greater robustness of the composites to variations in HEBM conditions. FTIR, EDS, and XRD analyses confirmed the successful incorporation of bentonite into the composites. HEBM enhanced adsorption kinetics, while bentonite improved removal efficiency (up to 97.75%) and surface heterogeneity. Among modified samples, adsorption followed the Elovich model (R2 up to 0.99), suggesting the presence of heterogeneous adsorption sites, while equilibrium data were best described by the Freundlich isotherm (R2 up to 0.97). Maximum adsorption capacities calculated from the Langmuir model reached 307.86 mg g-1 (BDCSB4002) and 274.61 mg g-1 (DCSB2006), although the Langmuir model did not provide the best fit for the modified materials reflecting the heterogeneous nature of the adsorption process. The adsorption mechanism involves π–π interactions, electrostatic attraction, hydrogen bonding, and intraparticle diffusion. These findings demonstrate that DCSB exhibits the highest Langmuir maximum adsorption capacity, HEBM and bentonite modification offer improvements in adsorption kinetics and removal efficiency, supporting the potential of engineered carnauba biochar and biochar–clay composites as sustainable adsorbents dye removal in wastewater treatment. Tipo: Dissertação Thu, 01 Jan 2026 00:00:00 GMT http://repositorio.ufc.br/handle/riufc/86883 2026-01-01T00:00:00Z http://repositorio.ufc.br/handle/riufc/86596 Título: Synthesis and characterization of multi-spectral luminescent nanocrystals based on NaYF4 and NaGdF4 Autor(es): Resquin, Lucas Santiago Medina Abstract: Multispectral luminescent nanoparticles based on hexagonal-phase (β-) NaYF4 and NaGdF4 ma- trices, doped with rare-earth (RE) ions (Yb3+ /Er3+ /Tm3+ /Eu3+ ) and transition metals (Fe3+ /Mn2+ ), were successfully synthesized via the thermal decomposition method. The structural characteri- zation by X-ray diffraction (XRD) confirmed the formation of highly crystalline, single-phase hexagonal structures with lattice parameters consistent with the reference ICSD patterns. Fourier- transform infrared (FTIR) spectroscopy verified the effective surface capping of the nanoparticles with oleic acid (OA) ligands. The optical properties were evaluated using ultraviolet-visible (UV-Vis) absorption and photoluminescence (PL) spectroscopy. Under near-infrared (976 nm) excitation, efficient upconversion (UC) emission was observed, mediated by Yb3+ sensitization and energy transfer to Er3+ /Tm3+ activators. Core@shell architectures exhibited a significant enhancement in UC intensity compared to core-only structures, demonstrating the effectiveness of the inert shell in suppressing surface-related quenching. Under ultraviolet (365 nm) excitation, downconversion (DC) luminescence was dominated by characteristic emissions from Eu3+ , Er3+ , and Tm3+ , with OA acting simultaneously as a surface ligand, sensitizer, and blue emitter. The introduction of transition metals (5% Fe3+ or Mn2+ ) into the core of NaGdF4-based nanoparticles induced distinct modifications: Mn2+ doping enhanced the relative intensity of the (110) diffrac- tion peak and promoted resonant energy transfer that intensified red emission from Er3+ . The core@shell design effectively mitigated the non-radiative quenching typically associated with Mn2+ doping in core-only systems. These findings demonstrate that transition-metal codoping, combined with core@shell engineering, provides a viable route to tune energy-transfer pathways and emission profiles in RE-doped nanostructures. Tipo: Dissertação Thu, 01 Jan 2026 00:00:00 GMT http://repositorio.ufc.br/handle/riufc/86596 2026-01-01T00:00:00Z http://repositorio.ufc.br/handle/riufc/86409 Título: Previsão computacional do teor de silício no ferro-gusa Autor(es): Xavier, João Victor Barroso Abstract: The silicon content of pig iron is one of the main indicators of its quality and the thermal state of the blast furnace. Furthermore, a high silicon content can damage industrial equipment, leading to the need for maintenance and, consequently, a loss of process efficiency. For these reasons, several studies have been developed over decades to predict and monitor the silicon content in pig iron, suggesting the use of data-driven models. In this context, this work tested models such as the logistic perceptron, multilayer perceptron artificial neural networks with up to two hidden layers, and different versions of support vector machines adapted for regression (SVR, TSVR, LSSVR) to predict the silicon content in pig iron. A technique for estimating the number of hidden neurons in neural networks based on singular value decomposition (SVD) was also investigated to reduce tuning time and computational cost. Among the neuron-based models, the neural network with one hidden layer presented the best balance between performance and computational cost, while the SVD-based technique provided a smaller hyperparameter testing window, therefore, it was used in a sensitivity analysis to study the influence of each input variable on the silicon content in pig iron. Tipo: Dissertação Thu, 01 Jan 2026 00:00:00 GMT http://repositorio.ufc.br/handle/riufc/86409 2026-01-01T00:00:00Z http://repositorio.ufc.br/handle/riufc/86385 Título: Avaliação de aminoácidos como inibidores de corrosão para aço carbono AISI 1018 submetidos a meio contendo NaCl com e sem saturação de CO2 Autor(es): Moura, Milena Jacinto da Silva Abstract: Corrosion represents one of the most significant challenges faced by industries, leading to considerable financial losses. Various compounds are used to prevent, reduce, or even halt corrosion in different materials affected by these effects. Thus, sectors such as oil and gas employ chemical compounds known as corrosion inhibitors. However, some substances, despite having inhibitory effects, may pose environmental and human health risks. In this context, natural, non-aggressive, and ecologically sustainable compounds, such as amino acids, aqueous extracts, and ionic liquids, are being investigated as alternatives to conventional corrosion inhibitors. Amino acids have been demonstrated to be corrosion inhibitors for a variety of materials, such as carbon steel, stainless steel, and metal alloys, in different corrosive environments. This study proposes an analysis of five amino acids — histidine, methionine, cysteine, serine, and phenylalanine — as potential corrosion inhibitors. These amino acids were investigated with varying inhibitor concentrations (250, 500, and 1000 ppm), medium temperature (25, 40, and 60°C), and the use of a surfactant to evaluate the synergism, based on whether or not inhibition efficiency increased, and the evaluation of the medium with carbon dioxide (CO2) saturation. To assess the effectiveness of these compounds as corrosion inhibitors, gravimetric and electrochemical techniques, such as potentiodynamic polarization (PP) and electrochemical impedance spectroscopy (EIS), were employed. UV-VIS measurements were performed to analyze the compounds in solution. A molecular modeling study complemented the analysis of the amino acids. The characterization of the amino acids was carried out using techniques such as Fourier transform infrared spectroscopy (FTIR) and thermogravimetric analysis (TGA). For surface analysis, images were collected using scanning electron microscopy (SEM) and atomic force microscopy (AFM). The results indicated an efficiency order of the amino acids: histidine > cysteine > phenylalanine > serine > methionine, which was confirmed by theoretical calculations. In the tests performed, the amino acids histidine, cysteine, and phenylalanine respectively showed efficiencies of 91%, 90%, and 88%, standing out as the most promising results. The amino acids showed the best inhibition response at a temperature of 25°C to 3.5 wt% NaCl. Tipo: Tese Mon, 01 Jan 2024 00:00:00 GMT http://repositorio.ufc.br/handle/riufc/86385 2024-01-01T00:00:00Z