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The unique electrical properties of carbon nanotubes (CNTs) are highly desired in many technological applications. Unfortunately, in practice, the electrical conductivity of most CNTs and their assemblies has fallen short of expectations. One reason for this poor performance is that electrical resistance develops at the interface between carbon nanomaterials and metal surfaces when traditional metal-metal type contacts are employed. Here, a method for overcoming this resistance using covalent bond formation between open-ended CNTs and Cu surfaces is investigated experimentally and supported by theoretical calculations. The open-ended CNTs are vertically oriented compared to the substrate and have carboxylic functional groups that react with aminophenyl groups (linkers) grafted on metal surfaces. The covalent bond formation, crosslinking carboxylic and amine, via amide bond formation occurs at 120 °C. The covalent bonding nature of the aminophenyl linker is demonstrated theoretically using (100), (110), and (111) Cu surfaces, and bridge-like bond formation between carbon and two adjacent Cu atoms is revealed. The electrical conductivity calculated for a single intramolecular-type junction supports covalent bond formation between Cu and CNTs. Experimentally, the robustness of the covalent bonding between vertically oriented CNTs is tested by exposing CNTs on Cu to sonication, which reveals that CNTs remain fixed to the Cu supports. Since bonding CNTs to metals was performed at low temperatures, the reported method of covalent bond formation is expected to facilitate the application of CNTs in multiple fields, including electronics.

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The presence of particulate Pb in tap water has been a limiting factor in the design of accurate and portable platforms for quantifying this toxic metal. Convenient and affordable electrochemical techniques are blind toward particulate species and thus require addition of reagents and additional chemical processing such as sample acidification. This study describes the fundamentals and the first use of membrane electrolysis for the reagentless sample preparation of tap water for the detection of particulate Pb contaminants. Membrane electrolysis allows for the in-situ generation of nitric acid, which, in combination with anodic stripping voltammetry, provides a powerful tool for the accurate and reagent-free detection of Pb2+. The configuration of the setup allows for its semi-autonomous operation and requires minimal attention, making electrochemical methods more suitable and accessible for continuous measurements of particulate contaminants in tap-water. The voltammetric response is linear in the range of 24.1-398 nM of Pb, which covers the action level of 48 nM suggested by the World Health Organization.

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The demand for electrically insulated microwires and microfibers in biomedical applications is rapidly increasing. Polymer protective coatings with high electrical resistivity, good chemical resistance, and a long shelf-life are critical to ensure continuous device operation during chronic applications. As soft and flexible electrodes can minimize mechanical mismatch between tissues and electronics, designs based on flexible conductive microfibers, such as carbon nanotube (CNT) fibers, and soft polymer insulation have been proposed. In this study, a continuous dip-coating approach was adopted to insulate meters-long CNT fibers with hydrogenated nitrile butadiene rubber (HNBR), a soft and rubbery insulating polymer. Using this method, 4.8 m long CNT fibers with diameters of 25-66 µm were continuously coated with HNBR without defects or interruptions. The coated CNT fibers were found to be uniform, pinhole free, and biocompatible. Furthermore, the HNBR coating had better high-temperature tolerance than conventional insulating materials. Microelectrodes prepared using the HNBR-coated CNT fibers exhibited stable electrochemical properties, with a specific impedance of 27.0 ± 9.4 MΩ µm2 at 1.0 kHz and a cathodal charge storage capacity of 487.6 ± 49.8 mC cm-2. Thus, the developed electrodes express characteristics that made them suitable for use in implantable medical devices for chronic in vivo applications.

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Self-assembled monolayers (SAMs) of alkanethiols on gold have become a central focus of controllable surface chemistry because they can be easily formed from the solution phase and characterized using various techniques. Understanding the formation processes occurring at a nanoscale level is crucial to form defect-free SAMs for tailored applications in bio- and nanotechnology. Although many reports study and characterize SAMs after they are formed on gold surfaces, typical methods have not extensively studied the SAM formation process at the nanoscale. This paper focuses on the formation of defect-free SAMs and elucidates the formation mechanism occurring at the nanoscale level during the formation process. Exploiting the strength of scanning electrochemical cell microscopy, we monitored SAM formation via a soluble redox reporter on a polycrystalline gold foil using voltammetric and amperometric techniques. We formed SAMs by varying the concentration of 3-mercapto-1-propanol [HS(CH2)3OH], 6-mercapto-1-hexanol [HS(CH2)6OH], and 9-mercapto-1-nonanol [HS(CH2)9OH] to determine the effects of the thiol chain length, concentration, and location on the substrate (grain boundaries) on monolayer formation. We observed real-time changes in the quasisteady-state current of our redox reporter during the self-assembly process. Importantly, we formed defect-free SAMs at the nanoscale level using different concentrations of HS(CH2)6OH and HS(CH2)9OH and found that SAM formation at the nanoscale is concentration-dependent and varies when at a boundary between two crystal grains.

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Implantable neural electrodes are generally used to record the electrical activity of neurons and to stimulate neurons in the nervous system. Biofouling triggered by inflammatory responses can dramatically affect the performance of neural electrodes, resulting in decreased signal sensitivity and consistency over time. Thus, long-term clinical applications require electrically conducting electrode materials with reduced dimensions, high flexibility, and antibiofouling properties that can reduce the degree of inflammatory reactions and increase the lifetime of neural electrodes. Carbon nanotubes (CNTs) are well known to form flexible assemblies such as CNT fibers. Herein, we report the covalent functionalization of predefined CNT fiber and film surfaces with hydrophilic, antibiofouling phosphorylcholine (PC) molecules. The electrochemical and spectroscopic characteristics, impedance properties, hydrophilicity, and in vitro antifouling nature of the functionalized CNT surfaces were evaluated. The hydrophilicity of the functionalized CNT films was demonstrated by a decrease in the static contact angle from 134.4° ± 3.9° before to 15.7° ± 1.5° after one and fully wetting after three functionalization cycles, respectively. In addition, the extent of protein absorption on the functionalized CNT films was significantly lower than that on the nonfunctionalized CNT film. Surprisingly, the faradic charge-transfer properties and impedance of the CNT assemblies were preserved after functionalization with PC molecules. These functionalized CNT assemblies are promising for the development of low-impedance neural electrodes with higher hydrophilicity and protein-fouling resistance to inhibit inflammatory responses.

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The outbreak of COVID-19, since its appearance, has affected about 200 countries and endangered millions of lives. COVID-19 is extremely contagious disease, and it can quickly incapacitate the healthcare systems if infected cases are not handled timely. Several Conventional Neural Networks (CNN) based techniques have been developed to diagnose the COVID-19. These techniques require a large, labelled dataset to train the algorithm fully, but there are not too many labelled datasets. To mitigate this problem and facilitate the diagnosis of COVID-19, we developed a self-attention transformer-based approach having self-attention mechanism using CT slices. The architecture of transformer can exploit the ample unlabelled datasets using pre-training. The paper aims to compare the performances of self-attention transformer-based approach with CNN and Ensemble classifiers for diagnosis of COVID-19 using binary Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection and multi-class Hybrid-learning for UnbiaSed predicTion of COVID-19 (HUST-19) CT scan dataset. To perform this comparison, we have tested Deep learning-based classifiers and ensemble classifiers with proposed approach using CT scan images. Proposed approach is more effective in detection of COVID-19 with an accuracy of 99.7% on multi-class HUST-19, whereas 98% on binary class SARS-CoV-2 dataset. Cross corpus evaluation achieves accuracy of 93% by training the model with Hust19 dataset and testing using Brazilian COVID dataset.

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A convenient and simple, RhII -catalyzed denitrogenative method for the synthesis of biologically interesting 2-amino-benzoxazinones and 5-amino-oxadiazoles from readily available isatoic anhydrides and oxadiazolones has been developed. These reactions proceed via an O-H insertion onto α-imino RhII -carbenoid species followed by a rearrangement. The scope of the reaction can also be extended to benzoxazinones to access amino-substituted benzoxazines.