Double co-host emitter based top emitting white organic light emitting diodes with enhanced brightness and efficiency

quninolinato)-4-phenylphenolate alu-minium (BAlq) as HTL which is responsible for blue light emission is found to have best characteristics when compared to other simulated devices. It has a maximum luminance of 10 000 cd/m2 and current efficiency of 15.25 cd/A, respectively, and CIE coordinates are at (0.329, 0.319). The device is found to be compatible to be used in solid state lighting applications because of the low driving voltage of the device.     

Covid-19 Forecasting with Deep Learning-based Half-binomial Distribution Cat Swarm Optimization

About 170 nations have been affected by the COvid VIrus Disease-19 (COVID-19) epidemic. On governing bodies across the globe, a lot of stress is created by COVID-19 as there is a continuous rise in patient count testing positive, and they feel challenging to tackle this situation. Most researchers concentrate on COVID-19 data analysis using the machine learning paradigm in these situations. In the previous works, Long Short-Term Memory (LSTM) was used to predict future COVID-19 cases. According to LSTM network data, the outbreak is expected to finish by June 2020. However, there is a chance of an over-fitting problem in LSTM and true positive; it may not produce the required results. The COVID-19 dataset has lower accuracy and a higher error rate in the existing system. The proposed method has been introduced to overcome the above-mentioned issues. For COVID-19 prediction, a Linear Decreasing Inertia Weight-based Cat Swarm Optimization with Half Binomial Distribution based Convolutional Neural Network (LDIWCSO-HBDCNN) approach is presented. In this suggested research study, the COVID-19 predicting dataset is employed as an input, and the min-max normalization approach is employed to normalize it. Optimum features are selected using Linear Decreasing Inertia Weight-based Cat Swarm Optimization (LDIWCSO) algorithm, enhancing the accuracy of classification. The Cat Swarm Optimization (CSO) algorithm’s convergence is enhanced using inertia weight in the LDIWCSO algorithm. It is used to select the essential features using the best fitness function values. For a specified time across India, death and confirmed cases are predicted using the Half Binomial Distribution based Convolutional Neural Network (HBDCNN) technique based on selected features. As demonstrated by empirical observations, the proposed system produces significant performance in terms of f-measure, recall, precision, and accuracy.     

Wettability and interfacial phenomena in the liquid-phase bonding of refractory diboride ceramics: Recent developments

Joining and integration technologies are integral to manufacturing of components based on ultrahigh-temperature ceramics (UHTCs) such as transition metal diborides. Brazing is a particularly attractive joining technique because of its simplicity and versatility, but its use to join the UHTCs demands knowledge of the complex interplay among high-temperature wettability, interfacial reactions, and chemical and thermoelastic compatibilities. This paper summarizes the research and development activities carried out over the last two decades to characterize the wettability and interfacial phenomena in brazing of refractory diboride ceramics. The contact angle data of various metal alloys on diboride-based ceramics have been collected and critically evaluated in conjunction with an analysis of the chemistry and structure of the interface to understand the underlying mechanisms and phenomena that govern interface formation. It explores how solid–liquid interactions impact and are impacted by physical, chemical, and mechanical properties of joined materials. It also describes how this knowledge has been successfully utilized to create liquid-phase bonded diboride-based joints. The paper concludes with a summary of the current state of the art and highlights integration challenges and future research and technology development needs in the area.     

Diffusion bonding of SiC ceramics with interlayers of metallic titanium foils and PVD titanium coatings

Silicon carbide (SiC) is a candidate material for high-temperature structural aerospace applications due to its thermal and mechanical properties. Joining technologies enable the fabrication of complex shaped components needed for such applications. Various interlayers and processing conditions were used to form diffusion bonds between SiC substrates. Interlayers of titanium (Ti) foils and physically vapor deposited Ti coatings were used in the thicknesses of 10 and 20 μm with processing hold times of 1, 2, and 4 h. Polished cross sections of resulting diffusion bonds were analyzed using scanning electron microscopy (SEM) coupled with energy-dispersive spectroscopy (EDS) and using transmission electron microscopy (TEM). From the TEM analysis, selected-area diffraction patterns for Ti₃SiC₂, Ti₅Si₃C_x, and TiSi₂ were observed. Moreover, TiC and an unknown phase were present in diffusion bonds formed with metallic titanium foil. From the SEM/EDS analyses, intermediate phases of Ti₅Si₃C_x and TiC were found to be present in microcracked diffusion bonds. With the thinner Ti interlayers and/or longer processing time, microcracking was alleviated or eliminated due to the presence of the more stable and lower thermal expansive phases of Ti₃SiC₂ and TiSi₂. Detailed analysis of microstructures and the probable phases that formed in the bonded regions is presented.     

Analysis of couple stress nanofluid flow under convective condition in the temperature-dependent fluid properties and Lorentz forces

In recent years, a great deal of interest has been generated in modern micro- and nanotechnologies for micro/nano-electronic devices. These technologies are increasingly utilizing sophisticated fluid media to enhance performance. Among the new trends is the simultaneous adoption of nanofluids and biological micro-organisms. Motivated by bio-nanofluid vertical channel oxygenators in medical engineering, in the current work, a mathematical model is developed to examine the flow of mixed convective couple-stress nanofluids in a vertical channel with a transverse magnetic field, fluid viscosity that changes with temperature, and thermal conductivity. The non-Newtonian model follows Brownian motion and heat spread by nanoparticles in a fluid under coupled stress. Highly linked, nonlinear regulating equations are translated into nondimensional equations using relevant variables. The governing equations are then turned into a form with no dimensions. The Keller-box technique, a second-order finite difference method for solving second-order equations, is used to solve them numerically. On the other hand, the effects of different non-Newtonian flow parameters, such as the couple stress fluid parameter, the magnetic parameter, the variable fluid viscosity, the variable thermal conductivity parameters, the Brinkman number, the nanofluid and buoyancy parameters, and the rate of chemical reaction parameter, are carefully studied. The velocity, temperature, and concentration fields are calculated over a wide range of possible values for the relevant parameters.     

Tailoring the Angular Mismatch in MoS2 Homobilayers through Deformation Fields

Ultrathin MoS₂ has shown remarkable characteristics at the atomic scale with an immutable disorder to weak external stimuli. Ion beam modification unlocks the potential to selectively tune the size, concentration, and morphology of defects produced at the site of impact in 2D materials. Combining experiments, first-principles calculations, atomistic simulations, and transfer learning, it is shown that irradiation-induced defects can induce a rotation-dependent moiré pattern in vertically stacked homobilayers of MoS₂ by deforming the atomically thin material and exciting surface acoustic waves (SAWs). Additionally, the direct correlation between stress and lattice disorder by probing the intrinsic defects and atomic environments are demonstrated. The method introduced in this paper sheds light on how engineering defects in the lattice can be used to tailor the angular mismatch in van der Waals (vdW) solids.     

Editorial for special issue on “advanced topics in document analysis and recognition”

International Journal on Document Analysis and Recognition (IJDAR) -     

Effect of Mo and W interlayers on microstructure and mechanical properties of Si3N4–nickel-base superalloy joints

Si₃N₄/nickel-base superalloy (Inconel-625) and Si₃N₄/Si₃N₄ joints with refractory metal (W and Mo) interlayers were vacuum brazed using a Ti-active braze Cu-ABA (92.75Cu–3Si–2Al–2.25Ti) at 1317 K for 30 min with the following interlayered arrangements: Si₃N₄/Mo/W/Inconel and Si₃N₄/Mo/W/Si₃N₄. The joints exhibited Ti segregation at the Si₃N₄/Cu-ABA interface, elemental interdiffusion across the joint interfaces, and sound metallurgical bonding. Knoop microhardness profiles revealed hardness gradients across the joints that mimicked the interlayered arrangement. The compressive shear strength of Si₃N₄/Si₃N₄ joints both with and without W and Mo layers was ∼142 MPa but the strength of Si₃N₄/Inconel joints increased from ∼9 MPa for directly bonded joints without interlayers to 53.5 MPa for joints with Mo and W interlayers.     

Mobile FD-CR with High-Speed VTFET CMOS SOI Switch Under Channel Estimation Error

Silicon - In this paper, Silicon-on-Insulator vertical TFET based CMOS high-speed switch is implemented on Full-duplex Cognitive Radio (FD-CR), and the impact of cognitive radio (CR) node mobility...     

An overview of mono-ethylene glycol synthesis via CO coupling reaction: Catalysts,kinetics, and reaction pathways

Monoethylene glycol (MEG) is a promising chemical and a useful feedstock for the synthesis of several industrial products. The current commercial process of MEG production utilizes petroleum feedstock (ethylene) and an expensive catalyst, and the yield is low. Syngas is an attractive alternate feedstock for MEG. Syngas to MEG proceeds in two steps: the self-closing, green step of carbonylation of alkyl nitrile to produce dialkyl oxalate, and further hydrogenation of oxalate to MEG. Many reviews which focused on catalyst development, reaction mechanisms, and process variables were published earlier. The present work covers the developments in the syngas-to-MEG synthesis process after 2014. It overviews the performance of novel catalyst systems reported in literature. A discussion on reaction pathways and kinetic models is also presented. This work will provide useful insight into syngas-to-MEG conversion.