The development of electronic gadgets has become of great relevance for the detection of fraud in beverages such as wine, due to the addition of adulterants that bring risks to human health as well as economic impacts. Thus, the present study aims to apply a buckypaper (BP) based on functionalized multiwalled carbon nanotubes (MWCNTs)/cellulose fibers as a sensor for the analysis of Port wine intentionally adulterated with 5 vol.% and 10 vol.% distilled water and ethyl alcohol. The morphology of BP characterized by scanning electron microscopy indicates the formation of agglomerates of random MWCNTs dispersed on the surface and between the fibers of the cellulosic paper. The analysis of the response of the film through the normalized relative resistance change showed a higher response of 0.75 ± 0.16 for adulteration with 10 vol.% of water and a mean response time of 10.0 ± 3.60 s and recovery of approximately 17.2 min for adulteration with 5 vol.% alcohol. Principal component analysis (PCA) was used in data processing to evaluate the ability of BP to recognize and discriminate analytes and adulterating agents, allowing the investigation of its potential application as a low-cost and easy-to-handle multisensor.

This work investigated the effects of iodine on copper/functionalized carbon nanotubes (Cu/f-CNT) that were used in the coating of 1350 Aluminum Alloy wires, using the process of electrophoretic exposure with a solution of copper sulfate and iodine, under an electrical current of 1.2 A and a voltage of 10 V. The Al@Cu/f-CNT was characterized by Scanning Electron Microscopy in Secondary Electron mode, X-ray Diffraction and Raman spectroscopy, in addition to electrical measurements, at room temperature and under heating, via kelvin bridge. The results showed an increase of approximately 18% in the electrical conductivity of the IACS compared to the standard aluminum conductor, due to the iodine doping of the outer walls of the f-CNT, causing an expansion between the layers, and reflecting the increase in the conduction channels. This method of electrodeposition of Cu/f-CNT on the surface of metallic wires shows promise for the production of nanostructured cables with high ampacity, lightness and high performance, for application in power transmission lines.

The development of miniaturized sensors has become relevant for the detection of chemical/biological substances, since they use and detect low concentrations, such as flocculants based on amines for the mining industry. In this study, buckypaper (BP) films based on carboxylic acid functionalized multi-walled carbon nanotubes (f-MWCNTs) were produced through vacuum filtration on cellulose filter paper to carry out sensory function in samples containing ether-amine (volumes: 1%, 5%, 10% and 100%). The morphological characterization of the BPs by scanning electron microscopy showed f-MWCNT aggregates randomly distributed on the cellulose fibers. Vibrational analysis by Raman spectroscopy indicated bands and sub-bands referring to f-MWCNTs and vibrational modes corresponding to chemical bonds present in the ether-amine (EA). The electrical responses of the BP to the variation in analyte concentration showed that the sensor differentiates deionized water from ether-amine, as well as the various concentrations present in the different analytes, exhibiting response time of 3.62 ± 0.99 min for the analyte containing 5 vol.% EA and recovery time of 21.16 ± 2.35 min for the analyte containing 10 vol.% EA, revealing its potential as a real-time response chemiresistive sensor.

The increasing demand for materials with enhanced properties and high-performance devices has driven substantial research into nanomanufacturing, particularly using carbon nanotubes (CNTs), because of their exceptional properties and high sensitivity to chemical doping. In this way, this work summarizes nanomanufacturing methods for CNT-based devices developed in Brazil, covering the complete cycle from nanocomposite production to functional device assembly across cellulosic, polymeric, and metallic matrix systems. For cellulosic matrices, vacuum filtration enables the production of buckypaper, which is subsequently assembled into chemiresistive, thermoresistive, and thermoelectric devices. For polymeric matrices, 3D printing combined with surface functionalization techniques (spray coating, inverted immersion, and direct immersion) produces piezoresistive robotic sensors, metal-free thermal sensors, and biomedical scaffolds for tissue engineering. For metallic matrices, electrodeposition can produce Cu-CNT-coated aluminum comparable to traditional copper power transmission cables, while arc welding produces stainless steel composites with properties comparable to commercial high-grade steels. These devices have commercial and industrial applications, with low-cost and scalable production methods in comparison with conventional materials. Characterization results demonstrate that CNT integration into diverse matrices successfully bridges nanoscale properties to macroscopic functional devices. Current challenges include uniform CNT dispersion and structural defect control, laboratory to industry scale transition, and long-term device stability under environmental conditions. Future perspectives encompass lab-on-chip systems, wearable devices, 3D-printed smart structures, Internet of Things integration, and machine learning-enhanced analytics.

Este artigo investiga o uso da mineração de dados na vigilância epidemiológica de pacientes com Influenza, focando em sintomas que indicam a necessidade de internação. Utilizando o algoritmo de regras de associação Apriori no software WEKA, foram analisadas combinações de sintomas em dados epidemiológicos para identificar padrões relacionados ao agravamento da doença. Os resultados revelaram que sintomas como febre, tosse, dispneia e desconforto respiratório estão fortemente associados à hospitalização. Combinações de sintomas, como febre e tosse e febre, tosse e dispneia, apresentaram altos níveis de suporte e confiança, destacando-se como indicadores relevantes de casos graves. Esses achados demonstram o potencial da mineração de dados para identificar padrões que auxiliam na estratificação de risco e triagem clínica, permitindo intervenções mais eficazes. A identificação precoce de combinações de sintomas críticos pode melhorar o direcionamento de recursos de saúde pública e o planejamento de atendimento, especialmente em períodos de alta demanda devido a surtos de Influenza. Este estudo contribui para a otimização dos sistemas de vigilância epidemiológica, sugerindo que técnicas de mineração de dados podem aperfeiçoar a tomada de decisões em crises de saúde pública.