Study of fuel insolubles: Formation conditions and characterization of copper compounds

The solids formed in the systems containing copper in different oxidation states, in the presence and absence of hexanoic acid and dodecanethiol, together and separately, at room temperature, were studied. The experiments were performed in a mineral oil matrix, free of sulfur compounds and metals; a diesel oil matrix; and the reagents alone, without any matrix. The deposits formed were analyzed by elemental analysis (EA), infrared spectroscopy (IR), thermogravimetric analysis (TGA) and total copper by inductively coupled plasma-optical emission spectrometry (ICP-OES), for their identification and determination of the probable structures. In samples containing both hexanoic acid and dodecanethiol, when there is copper(I), anhydrous copper(II) hexanoate is preferentially formed, but in samples of copper(II), copper(II) mercaptate is formed first. In samples of metallic copper in mineral oil matrix, no deposit formations occur. In all cases in which deposits were formed, they were the same as in diesel oil matrix.     

Superior corrosion protection performance of polypdopamine-intercalated CeO2/polyurethane nanocomposite coatings on steel in 3.5% NaCl solution

Journal of Applied Electrochemistry - Newly synthesized polyurethane (PU)–polydopamine (Pda)/CeO2 (cerium oxide) nanocomposite-coated mild steel was investigated for its corrosion protection...     

A comparative study on the metaheuristic-based optimization of skew composite laminates

Engineering with Computers - Plate structures are the integral parts of any maritime engineering platform. With the recent focus on composite structures, the need for optimizing their design and...     

Electronic band structure and optoelectronic properties of double perovskite Sr2MgMoO6 through modified Becke-Johnson potential

The crystal structure, electronic and optical properties of double perovskite Sr₂MgMoO₆ have been calculated by using the full-potential linear augmented plane wave (FP-LAPW) method. The band structure and density of states (DOS) were carried out by the modified Becke–Johnson (mBJ) exchange potential approximation based on the density functional theory (DFT). The calculated band structure shows a direct band gap (Γ–Γ) of 2.663 eV for Sr₂MgMoO₆. The compound Sr₂MgMoO₆ has a triclinic structure with the space group I-1, the lattice parameters a=5.5666 Å, b=5.5661 Å and c=7.9191 Å, which are used in our calculations. The optical parameters, like dielectric constant, refractive index, reflectivity and energy loss function were also calculated and analyzed. This work provides the first quantitative theoretical prediction of the optical properties and electronic structure for the triclinic phase of Sr₂MgMoO₆.     

Bulky rigid substitutions: A route to high electron mobility and high solid-state luminescence efficiency of perylene diimide

In this paper, we report that a kind of perylene diimide derivative with bulky rigid substituents, 1,7-bis(p-tert-butylphenoxy)-N,N′-dicyclohexyl-perylene-3,4,9,10-tetracarboxylic diimide (TBPCHPDI) possesses both high electron mobility (1.8 cm² V⁻¹s⁻¹) and high fluorescence quantum yield (0.32) in the solid state. Through X-ray diffraction (XRD), UV–Vis absorption and fluorescence spectra, and differential scanning calorimetry (DSC) measurements, it is demonstrated that the above phenomenon can be ascribed to the unique crystal structure of TBPCHPDI: due to steric hindrance of bulky rigid substituents, the intermolecular π–π actions are neglectable, providing high luminescence efficiency; in the mean time, the spacing between perylene chromophores is still very short (3.47 Å), which is favorable for the hopping transportation of charge carrier from one molecule to neighboring molecule. Therefore, our finding would help design and synthesize novel organic semiconductive materials with potential applications in electrically pumped lasers which require high emission efficiency when large current density is applied.     

Optimal 5G network slicing using machine learning and deep learning concepts

Network slicing is predetermined to hold up the diversity of emerging applications with enhanced performance and flexibility requirements in the way of splitting the physical network into numerous logical networks. Consequently, a tremendous data count has been generated with an enormous number of mobile phones due to these applications. This has made remarkable challenges and has a considerable influence on the network slicing performance. This work aims to design an efficient network slicing using a hybrid learning algorithm. Thus, we proposed a model, which involves three main phases: (a) Data collection, (b) Optimal weighted feature extraction (OWFE), and (c) Slicing classification. First, we collected the 5G network slicing dataset, which involves the attributes associated with various network devices like “user device type, duration, packet loss ratio, packet delay budget, bandwidth, delay rate, speed, jitter, and modulation type.” Next, we performed the OWFE, in which a weight function is multiplied with the attribute values to have high scale variation. We optimized this weight function by the hybridization of two meta-heuristic algorithms—glowworm swarm optimization and deer hunting optimization algorithm (DHOA)—and named the proposed model glowworm swarm-based DHOA (GS-DHOA). For the given attributes, we classified the exact network slices like “eMBB, mMTC, and URLLC” for each device by a hybrid classifier using deep belief and neural networks. The weight function of both networks is optimized by the GS-DHOA. The experiment results revealed that the proposed model could influence the provision of accurate 5G network slicing.     

Mechanosynthesis of hydroxyapatite–ferrite composite nanopowder

In the present work, an investigation of the mechanosynthesis of calcium hydroxyapatite (HA, Ca₁₀(PO₄)₆(OH)₂) from a mixture of calcium oxide (СаО) and ammonium hydrophosphate ((NH₄)₂HPO₄) and mechanotreatment of HA in a planetary mill with the use of steel drums and milling body has been performed. The obtained results have shown that the mechanosynthesis of crystalline nanodisperse HA proceeds through the stage of formation of an amorphous material. The temperature treatment of HA powders at 1000 °C has enabled us to establish the influence of the treatment time on the phase composition of the powders and establish the following sequence of phase transformations: Ca₁₀(PO₄)₆(OH)₂→β-Ca₃(PO₄)₂ (t_milling~2 h), β-Ca₃(PO₄)₂→α-Ca₃(PO₄)₂ (t_milling~5 h), β-,α-Ca₃(PO₄)₂→Ca₁₀(PO₄)₆(OH)₂ (t_milling~7 h).The mechanosynthesis and mechanotreatment of hydroxyapatite in steel drums with steel balls is accompanied by the contamination of hydroxyapatite by their wear debris (iron + manganese). A large part of oxidized iron forms superparamagnetic inclusions distributed in HA powder. A small part of Fe³⁺ and Mn²⁺ ions from the steel wear debris enters into the hydroxyapatite lattice, substituting Ca²⁺ ions. As a result, a nanocomposite powder consisting of hydroxyapatite, alloyed by Fe³⁺ and Mn²⁺ ions and ferrite inclusions forms. The phase composition of HA powders, the degree of their alloying by Fe³⁺ and Mn²⁺ ions, and the content of ferrite inclusions can be controlled by changing the time of mechanotreatment.     

Mathematical modeling of a box-type solar cooker employing an asymmetric compound parabolic concentrator

A novel design of solar cooker is introduced. The cooker is of box-type equipped with an asymmetric compound parabolic concentrator (CPC) as booster-reflector. It consists of an insulated box equipped with a vertical double glazing cover on a side, and a vertical absorber plate laid out just behind the transparent cover. The booster-reflector is fixed on the glazed side of the box. The absorber plate and the glazing form a vertical channel, open at the top and bottom, and enclosed at the sides. The two openings allow the inside air circulation. A mathematical model of the heat transfer processes involved with this solar cooker, containing a cooking pot loaded with water and deposited on the box floor; was developed and the effects of various parameters, such as solar radiation, load of water and clouds on the dynamic behavior of the cooker are studied.     

An analytical procedure for multi-site,multi-season streamflow generation using maximum entropy bootstrapping

Stochastic time series models are very useful in many environmental domains. In this paper, an analytical procedure for multi-site, multi-season streamflow generation using maximum entropy bootstrap stochastic model (M3EB) is developed that can implicitly preserve both the spatial and temporal dependence structure, in addition to the other statistical characteristics present in the historical time series. The proposed model is computationally less demanding and simple in terms of modeling complexity. The maximum entropy bootstrap (MEB) generates random samples from the empirical cumulative distribution function (ECDF) and rearranges the random series based on the rank ordering of the historical time series. The modeling structure of MEB implicitly satisfies the ergodic theorem (preservation of summary statistics) and guarantees the reproduction of the time dependent structure of an underlying process. The orthogonal transformation is used with M3EB to capture the spatial dependence present in the multi-site collinear data. The performance of M3EB is verified by comparing the statistical characteristics between the observed and synthetically generated streamflows. Three case studies from Colorado River Basin, USA; Red River Basin, USA and Canada; and Cauvery River Basin, India; are used to demonstrate the advantages of M3EB. The statistical measures adopted for evaluation of M3EB performance include monthly statistics (mean, standard deviation and skewness), temporal and spatial correlation, smoothing (flows other than present in historical data) and extrapolation (flows outside the range of historical data). The M3EB model shows (i) a high level of accuracy in preserving the statistics; and (ii) a high computational efficiency. Since M3EB can be used for multiple variable problems, the model can be easily extended to other environmental or hydroclimatic time series data.