Owing to their cost-effectiveness and the natural abundance of magnesium, magnesium-ion batteries (MIBs) were introduced as encouraging alternatives to Lithium-ion batteries. Following the successful synthesis of carbon nano-tube, its B and N doped derivatives which were doped with B and N enjoyed the attention of researchers as novel anode materials (AM) for MIBs. Here, we investigated a BC2N nano-tube (BC2NNT) as an encouraging AM for MIBs. To have a deeper understanding of the electrochemical properties, cycling stability, specific capacity (SC) and the adsorption behavior of this nano-tube, first-principles density functional theory computations were performed. By performing NMR calculations, we identified two types of non-aromatic hexagonal rings, namely B2C2N2 (I) and BC4N (II). Magnesium was adsorbed onto I with the adsorption energy of −40.38 kcal/mol and on II with the adsorption energy −20.15 kcal/mol. The SCs were as high as 783 mAh/g. The predicted average open-circuit voltage for BC2NNT was 1.94 V, which was greater than that of other 2D materials. The findings demonstrated the possibility of utilizing the BC2NNT as an AM for MIBs. The results can provide useful insights into the design of boron-carbon-nitrogen-based AMs for MIBs.
AA wahid, journal mustansiriyah of sports science, 2023
This paper aims to study the chemical degradation of Brilliant Green in water via photo-Fenton (H2O2/Fe2+/UV) and Fenton (H2O2/Fe2+) reaction. Fe- B nano particles are applied as incrustation in the inner wall surface of reactor. The data form X- Ray diffraction (XRD) analysis that Fe- B nanocomposite catalyst consist mainly of SiO2 (quartz) and Fe2O3 (hematite) crystallites. B.G dye degradation is estimated to discover the catalytic action of Fe- B synthesized surface in the presence of UVC light and hydrogen peroxide. B.G dye solution with 10 ppm primary concentration is reduced by 99.9% under the later parameter 2ml H2O2, pH= 7, temperature =25°C within 10 min. It is clear that pH of the solution affects the photo- catalytic degradation
... Show MoreThe corrosion inhibiting properties of the new furan derivative 5-(furan-2-ylmethylsulfonyl-4-phenyl-2,4- dihydro [1,2,4] triazole-3-thione in acidic solution (1.0 M HCl) were explored utilizing electrochemical, surface morphology (AFM), and quantum chemical calculations approaches. The novel furan derivative 5-(furan-2-ylmethylsulfonyl-4-phenyl-2,4- dihydro [1,2,4] triazole-3-thione shows with an inhibitory efficiency value of 99.4 percent at 150 ppm, carbon steel corrosion in acidic medium is effectively inhibited, according to the results. The influence of temperature on corrosion prevention was studied using adsorption parameters and activation thermodynamics. The novel furan derivative creates a protective layer over the metallic surfa
... Show MoreThe phenomenon of informal building Spread recently in Iraqi residential areas, in general, and in Baghdad, in particular, due to the urgent housing need, on the one hand, and lack of commitment to building controls, on the other hand, to highlight the phenomenon of uncommitted building to controls and housing governing legislation in Iraq, leading to heterogeneity in both building densities and plot areas, and disorder in the urban fabric and urban escape of those areas. Research problem identified as the absence of a clear vision about the General aspects of the phenomenon of informal building in residential street scene, and the role of designed housing projects as a substitute for informal building in built residential areas. The des
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... Show MoreThe evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed
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