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.     

A Comprehensive Survey of Emergency Communication Network and Management

Wireless Personal Communications - The performance of wireless communication network is important in emergency rescue operations while ensuring optimum usage of limited wireless resources. Due to...     

A study of hydrogen as an alternative fuel

ABSTRACT

As oil prices increase, the interest in alternative fuels increases. This is evidenced by demonstration programmes and commitments by states such as India. The concern of the air quality in many areas around the world makes ?nding solutions more urgent. As the price of oil increases, alternate fuels become more ruthless. Major questions remain to be answered on which fuel or fuels will emerge and to what extent alternative sources will replace gasoline as the main product of crude oil. A combination of available alternative fuels will evolve with the most likely choices affected by a number of technical, political and market factors. In order to allow a wider application of alternative fuels, a number of obstacles have to be overcome. These include economic, technological, and infrastructural issues. In the past, gasoline has been plentiful and has had a signi?cant price advantage compared to other fuels. This could change quickly and alternative fuels would need to become more commonplace. One of the alternatives involves the more widespread use of biomass-produced fuels. In this paper describes that hydrogen as an alternative fuel. Hydrogen powered fuel cells could have wide applications, replacing batteries in many portable application, vehicle and using hydrogen for home electrical needs.     

A Cloud-Based Platform for Soybean Plant Disease Classification Using Archimedes Optimization Based Hybrid Deep Learning Model

Wireless Personal Communications - Bean which is botanically called Phaseolus vulgaris L. belongs to the Fabaceae family. Unnecessary economic losses arise during bean disease identification due to...     

Improved performance on seizure detection in an automated electroencephalogram signal under evolution by extracting entropy feature

Multimedia Tools and Applications - In recent years, enormous people in all age category were affected with epilepsy throughout the world. To detect and evaluate the epilepsy seizure, the...     

AIDECS: An AI-based,distributed environmental control system for self-sustaining habitats

The work described here derives from the implementation of intelligent control for a Bioregenerative Closed Ecological Life Support System. The AI-Based, Distributed Environment Control System (AIDECS) will be capable of supporting, in an integrated fashion, all activities ranging from planning of agricultural activities at the highest level to real-time control of environmental conditions at the lowest level. This paper describes the AIDECS subsystem that deals with control over two widely different time scales: (1) that of scheduling crop planting and harvesting over the extended horizon needed to ensure maintenance of the CO₂/O₂ and other gas balances (typically involving units of weeks, months and years), and (2) tha of controlling environmental parameters such as temperature and humidity to be properly correlated with crop requirements and external weather conditions (typically involving units of hours and days).     

Optimising industrial hemp fibre for composites

The optimisation of New Zealand grown hemp fibre for inclusion in composites has been investigated. The optimum growing period was found to be 114 days, producing fibres with an average tensile strength of 857 MPa and a Young’s modulus of 58 GPa. An alkali treatment with 10 wt% NaOH solution at a maximum processing temperature of 160 °C with a hold time of 45 min was found to produce strong fibres with a low lignin content and good fibre separation. Although a good fit with the Weibull distribution function was obtained for single fibre strength, this did not allow for accurate scaling to strengths at different lengths. Alkali treated fibres, polypropylene and a maleated polypropylene (MAPP) coupling agent were compounded in a twin-screw extruder, and injection moulded into composite tensile test specimens. The strongest composite consisted of polypropylene with 40 wt% fibre and 3 wt% MAPP, and had a tensile strength of 47.2 MPa, and a Young’s modulus of 4.88 GPa.     

Deep Learning-Based FOPID Controller for Cascaded DC-DC Converters

Smart grids and their technologies transform the traditional electric grids to assure safe, secure, cost-effective, and reliable power transmission. Non-linear phenomena in power systems, such as voltage collapse and oscillatory phenomena, can be investigated by chaos theory. Recently, renewable energy resources, such as wind turbines, and solar photovoltaic (PV) arrays, have been widely used for electric power generation. The design of the controller for the direct Current (DC) converter in a PV system is performed based on the linearized model at an appropriate operating point. However, these operating points are ever-changing in a PV system, and the design of the controller is usually accomplished based on a low irradiance level. This study designs a fractional-order proportional-integrated-derivative (FOPID) controller using deep learning (DL) with quasi-oppositional Archimedes Optimization algorithm (FOPID-QOAOA) for cascaded DC-DC converters in micro-grid applications. The presented FOPID-QOAOA model is designed to enhance the overall efficiency of the cascaded DC-DC boost converter. In addition, the proposed model develops a FOPID controller using a stacked sparse autoencoder (SSAE) model to regulate the converter output voltage. To tune the hyper-parameters related to the SSAE model, the QOAOA is derived by the including of the quasi-oppositional based learning (QOBL) with traditional AOA. Moreover, an objective function with the including of the integral of time multiplied by squared error (ITSE) is considered in this study. For validating the efficiency of the FOPID-QOAOA method, a sequence of simulations was performed under distinct aspects. A comparative study on cascaded buck and boost converters is carried out to authenticate the effectiveness and performance of the designed techniques.     

Delineating the effect of substituent and π-bridge flip on the photophysical properties of pyrene derivatives: answers from DFT/TD-DFT calculations

Journal of Materials Science - Pyrene-based Schiff base derivatives have attracted enormous potential as fluorescent probe for multifarious research applications due to their fashionable...     

Tuning the dielectric,ferroelectric and electromechanical properties of Ba0.83Ca0.10Sr0.07TiO3–MnFe2O4 multiferroic composites

We report the successful synthesis of Ba_0.83Ca_0.10Sr_0.07TiO₃–MnFe₂O₄ multiferroic composites showing significant improvement in electromechanical and magnetoelectric properties. All the composite samples have formed a diphasic perovskite-ferrite composite without the presence of any impurity or intermediate phase. The bare as well as composite samples have shown classical dielectric behavior even at higher ferrite substituted samples. The electrical characteristics of composite samples have shown slight deterioration, which is mainly attributed to non-ferroelectric MnFe₂O₄. However, the composites still exhibit high enough piezoelectric behavior and the modification in the electromechanical response of composites is mainly caused by a change in applied stress with MnFe₂O₄ addition. The M-H loops of composites have demonstrated a ferrimagnetic behavior with a substantial increase in saturation magnetization on increasing the ferrite concentration. Further, the composites have shown better coupling between the ferroelectric and ferrimagnetic phases, which has resulted in an improved magnetoelectric characteristic. The role of oxygen vacancies on ferroelectric and magnetic properties of prepared composites has been systematically studied.