Renan Augusto Pontes Ribeiro

A Inteligência Artificial (IA) tem desempenhado um papel cada vez mais central na transformação da educação contemporânea, especialmente em áreas que demandam elevado nível de abstração conceitual, como o ensino de Química. Esta revisão de literatura analisa, de forma abrangente, as principais tecnologias educacionais baseadas em IA aplicadas ao contexto da Química, incluindo chatbots e tutores inteligentes, sistemas de aprendizagem adaptativa, laboratórios virtuais enriquecidos por algoritmos preditivos, modelos generativos voltados para visualização molecular e ferramentas de avaliação automatizada com análise de desempenho em tempo real. Os estudos analisados evidenciam que a IA contribui para a personalização da aprendizagem, favorecendo trajetórias formativas individualizadas, a compreensão de fenômenos complexos por meio de múltiplas representações e a automatização de tarefas repetitivas do professor, o que amplia o tempo dedicado à mediação pedagógica qualitativa. Também são discutidos os impactos e implicações dessas tecnologias para a formação docente, abordando o desenvolvimento de competências digitais, a necessidade de compreensão crítica das ferramentas, aspectos éticos relacionados ao uso de dados e obstáculos para a implementação em diferentes realidades educacionais. Conclui-se que essas tecnologias podem transformar positivamente o ensino de Química, desde que empregadas de modo responsável, contextualizado e alinhado a práticas pedagógicas interdisciplinares, garantindo qualidade e equidade ao processo de aprendizagem.

In this work, α-Ag₂WO₄ particles with different cross-sections were obtained using the co-precipitation method at different synthesis temperatures. The samples were characterized by X-ray diffraction (XRD), field-scanning electron microscopy (SEM), and X-ray photoelectron spectroscopy (XPS). The antimicrobial activity was analyzed using the Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC) methods against the Escherichia coli and Salmonella spp. gram-negative bacteria. The antimicrobial tests against Escherichia coli and Salmonella spp. indicated that concentrations of 2.5–5 mg/mL and 5 mg/mL completely inhibit its growth, respectively. The antimicrobial activity was analyzed employing band-edge positions for ROS generations and the superficial distribution of Ag⁺ species that contribute to antimicrobial activity. Quantum-chemical calculations were used at the DFT level to investigate the surface-dependent reactivity of α-Ag₂WO₄, and we demonstrated how the antimicrobial properties could be tailored by the geometry and electronic structure of the exposed surfaces, providing guidelines for the morphology design.

The COVID-19 pandemic has emerged as an unprecedented global healthcare emergency, demanding the urgent development of effective materials to inactivate the SARS-CoV-2 virus. This research was planned to disclose the remarkable biocidal activity of SiO₂-Ag composites incorporated into low-density polyethylene. For this purpose, a joint experimental and theoretical [based on first-principles calculations at the density functional theory (DFT) level] study is performed. Biological assays showed that this material eliminatesStaphylococcus aureusand SARS-CoV-2 virus in just 2 min. Here, we investigate a previously unexplored process that we postulate may occur along the O₂ and H₂O adsorption and activation processes of pure and defective SiO₂-Ag surfaces for the generation of reactive oxygen species (ROS). The obtained results help us to predict the nature of ROS: superoxide anion radicals, ^•O₂^-, hydroxyl radicals, ^•OH, and hydroperoxyl radicals, ^•HO₂, that destroy and degrade the structure of the SARS-COV-2 virus. This is consistent with the DFT studies, where the energetic, electronic, and magnetic properties of the intermediates show a feasible formation of ROS. Present findings are expected to provide new insights into the relationship among the structure, property, and biocidal activity of semiconductor/metal SiO₂-Ag composites.

The influence of Eu3+ cations in the host matrix of CaZrO3 was investigated by analyzing its luminescence and structural properties. The Ca1-xZrO3:Eux crystals (x = 0.01, 0.02, 0.04, and 0.08 mol%) were obtained by a simple sol-gel method followed by a soft thermal treatment without any surfactant. The structural characterization was performed at short-, medium- and long-distance to verify the effect of the dopant in the host matrix. To endorse the experimental results, first-principles calculations were performed by using the CRYSTAL program associated with the density functional theory. The luminescence profile of the sample was investigated by analyzing the excitation and emission spectrum monitoring the emission at 614 nm and excited at 394 nm, noting that the sample Eu-doped with 0.08 mol% has greater emission intensity. The color variations of the characteristic emissions of Ca1-xZrO3:Eux crystals were evaluated according to the Commission Internationale de L’Éclairage, observing a red shift for all Eu-doped samples. A general luminescence scheme was proposed combining the density of state and the band structure calculations.

Combined experimental and theoretical analysis reveals the superior properties of Co _{1− x} Ni _x Fe ₂ O ₄ nanoparticles – a putative candidate for energy-harvesting applications.