Search

Lightweight materials with better resistance to sliding wear are prominent candidates for automobile brake drums, clutch pads and cylinder block applications to facilitate fuel economy. This attempt is reserved to cater to materials with higher tribological quality needs. Less dense foamy pumice stone particles were involved in three different percentages (5, 10, and 15 wt%) to reinforce lightweight AZ31 Mg alloy. A stir-assisted squeeze casting technique was pursued to process the composite and refine the grain structure. A phase detection, elemental mapping and microstructure study were done through X-ray diffraction (XRD), energy dispersive spectroscopy (EDS), and scanning electron microscopy (SEM), respectively. An experimental dry sliding wear scrutiny was administered using a pin-on-disc apparatus by considering: (i) ambient and elevated temperature environments and (ii) three different levels of loads. The results reveal a significant drop in wear loss and a frictional coefficient for 15% pumice-loaded composite than the base alloy. Post-wear examination acknowledges the fact that the ambient temperature wear is governed by adhesive-abrasive wear and high temperature is by abrasive wear mechanisms. Worn-out scrutiny authenticates the presence of oxide layers and their role in lubrication. A comparative study with previous works upholds the novel magnesium composite is the right candidate for the mentioned automobile applications.

The subwavelength grating microring resonator based filter shows great promise in optical sensing and communication. However, it spectrum nature makes it unsuitable for tracking or extracting a single wavelength from a broadband light source. In this paper, we used side-mode suppression, based on an angular grating- subwavelength microring resonator which offer high flexibility in wavelength design within the silicon-on-insulator (SOI) waveguide. By periodically arranging silicon waveguide pieces in three different widths, we can set the effective index along the inner sidewall of subwavelength microring resonator. thereby can achieve the precise wavelength selection. We examine the effects of various key parameters on the center wavelength, side-mode suppressed ratio, and quality factor of this filter.The proposed structure's isalso analysed for coupling strength between the bus and subwavelength grating ring resonator. The wavelength selection, compact size, compatibility with other similar nature waveguide-based devices and design flexibility highlight its significant potential in compact optical sensing and optical communication

Numerical simulation of magnetohydrodynamic radiative double-diffusive convective heat and mass transfer of a ternary hybrid nanofluid with thermophoretic particle deposition in an inclined annulus is studied. Both sides of cylinders are preserved at uniform temperatures, while the remaining sides are thermally insulated. The coupled nonlinear partial differential equations are solved using a finite difference approach. The detailed computational results of heat and mass transfer rate, temperature, concentration and flow fields are presented and discussed for a distinct range of significant physical parameters. The results demonstrated that increasing the angle of the inclination factor increases fluid flow. In light of buoyancy, when the annular cavity is set downward, the enhanced shear velocity is transported upwards, where it reaches its optimal temperature. The higher temperature difference leads to augmented dynamic fluid motion, particularly in the radial direction, as the system seeks to balance the thermal energy through convective transfer. The Brownian motion parameter has abrupt mobility of nanoparticles in liquid, which promotes particle collisions with liquid molecules, yielding kinetic energy. Increased values of thermophoretic parameters augment the thermophoresis force. Thermophoretic particle deposition increases the concentration of nanoparticles in an annulus due to the migration of particles from hot to cold regions under the influence of temperature gradient. The heat and mass transfer characteristics of ternary hybrid nanofluid are forecasted through an artificial neural network-based Levenberg–Marquardt backpropagated algorithm. The built model shows the heat and mass transfer rate root mean squared values through the Levenberg–Marquardt algorithm as one and mean squared error values as 1e-07 and 1e-08 respectively.

The study proposed the removal of Brilliant Green, a cationic dye, by adsorption process from wastewater solution utilizing a low-cost adsorbent such as Nutraceutical Industrial Pepper Seed Spent (NIPSS). The study comprises an investigation of the parametric influence on the adsorption process. The parameters identified are pH, dye concentration, process temperature, quantity of the adsorbent, and particle size. The study of statistics found from experiments was carried out by incorporating Freundlich, Brouers-Sotolongo, Langmuir, Toth, Sips, Jovanovic, and Redlich-Peterson isotherm models. The adsorption kinetics were determined by implementing pseudo-first-order and second-order models, diffusion film models, and Dumwald-Wagner and Weber-Morris models. The experimental adsorption capacity qe was found to be about 130 mg/g. This value was closest to the maximum adsorption of 144.6mg/g predicted by the Brouers-Sotolongo isotherm which had a correlation coefficient (R2) of 0.998. The adsorption kinetics data was confirmed to be a pseudo-second-order model. The change in free energy, enthalpy change, and entropy change were vital thermodynamic factors in concluding that adsorption is almost spontaneous and endothermic process. Change in enthalpy (ΔH°) reduced value indicates the physical nature of the process. The adsorption of BG dye on the adsorbent surface was authenticated by FTIR spectroscopy and SEM imaging. A Central Composite Design (CCD) Quadratic model under Response Surface Methodology (RSM) was implemented for statistical optimization of adsorption capacity for the five parameters studied, namely, time, temperature, concentration of the dye, weight of the adsorbent, and pH. Software Design Expert 7.0 was used to evaluate 3D contour plots. The process of optimization yielded a value of 350 mg/g. Thus, incrementing the adsorption process by 84.2 %. The study provides insights on various dye and adsorbent interaction possibilities and derives that NIPSS is an efficient adsorbent to extract BG dye from wastewater solutions.

The present investigation focuses on the microstructural behavior and mechanical properties of Aluminium alloy 2024 reinforced with SiC nanoparticles by applying the Friction Stir Processing (FSP) technique. Taguchi L9 orthogonal array was used to find the optimal process parameters. The experiment used the expected best process parameters, which confirmed the predicted highest value for the mechanical characteristic. Traverse speed, axial load, and rotating speed are the main factors affecting aluminum metal matrix composite. Hence, this experiment examined the effects of five different tool spinning speeds, specifically 800, 900, 1000, 1100, and 1200 rpm. Weld samples are fabricated wherein the stir zone contains SiC nanoparticles. The results of the study indicate that the optimal welding rotational speed of 1000 rpm has a significant impact on the microstructure, wear rate, and microhardness. Specifically, it was observed that the stirred zone exhibited enhanced wear resistance compared to other zones. The study's findings revealed that after implementing friction stir processing (FSP), a well-defined shear zone was observed on the advancing side of the stir zone. Additionally, it is found that the uniform dispersion and strong bonding of SiC particles with an aluminium matrix further enhance wear resistance.

In a variety of industries, including transportation, agriculture, and manufacturing, diesel engines are often employed. Due of rising prices and environmental concerns, researchers examined whether biodiesels might replace diesel. The current study looks into American Saffron Oil's feasibility as a feedstock for biodiesel production. The transesterification technique is used to extract American saffron oil methyl este(ASOME), which is then examined for its physical and chemical properties in accordance with ASTM standards. Diesel fuel and American Saffron Oil methyl ester are mixed on a volume basis to create a variety of fuel blends, including B20, B40, and B60. The test results showed that the 20 % ASOME mix had better performance and reduced emissions. Also, utilizing DIESEL-RK simulation software, diesel engine tests are conducted for the B20, B40, and B60 under identical operating circumstances. Moreover, diesel engine testing for the B20, B40, and B60 are carried out using DIESEL-RK simulation software under comparable operating circumstances. Results of simulation software tests show improved engine performance and reduced pollutants. When experimental data is compared to DIESEL-RK modeling software, it is found that brake thermal efficiency increased by 5.7 % and emissions of hydrocarbon and carbon monoxide decreased by 2.5 % and 14.3 %, respectively.

This research aims to provide an efficient and cost-effective renewable energy supply. It assesses the potential for photovoltaic (PV) and hydro energy in Pirthala, Haryana, India, using HOMER Pro® v3.14.2. A Hybrid renewable energy system (HRES) can continuously power 855 homes. The optimal HRES configuration comprises well-optimized PV modules, hydro turbines, converters, and batteries. The top four configurations were selected based on criteria such as net present cost (NPC) and cost of energy production (COE). The most effective HRES configuration involves a 3461-kW solar array, a 98.1 kW hydro turbine, 304 lithium-ion batteries of 100 kWh, and a 2785-kW converter, achieving a 100 % integration of renewable energy. This ideal HRES was thoroughly assessed regarding economic, technical, and renewable energy considerations. The results and the optimized HRES configuration can serve as a valuable reference for similar initiatives in rural areas, contributing to adopting renewable energy sources and enhancing energy access and reliability.

Environmental sustainability concerns have led to exploring alternative fuels like biodiesel in transportation. However, biodiesel engines emit pollutants like NOx, CO, and PM, posing health and environmental risks. This review explores the use of Aluminium Oxide (Al2O3), Ruthenium Oxide (RuO2), Titanium Oxide (TiO2), Cerium Oxide (CeO2), Graphene Oxide, Multi-walled Carbon Nanotubes (CNT) and other nanoparticles, in biodiesel engine. It focuses on their unique properties, characterization, emission control, environmental impact, and engine performance. The study emphasizes the significance of different biodiesel blends, compositions, and nanoparticle additions in determining engine performance and emissions. Results vary based on nanoparticle type, size, concentration, and blend composition. The review examines the impact of nanoparticles on various aspects of biodiesel blends, including density, viscosity, cetane number, calorific value, and flash points. It found that nanoparticle additives significantly influence Brake Thermal Efficiency and combustion efficiency. The study also found that nanoparticle-enhanced biodiesel blends have improved ignition properties, faster evaporation, higher oxygen content, and elevated cetane numbers, leading to cleaner combustion and more environmentally friendly engine operation. The research supports the beneficial effects of nanoparticles on biodiesel characteristics and emissions reduction. The review suggests that nanoparticles in biodiesel engines can improve fuel characteristics, engine performance, and emissions reduction but cautions against potential environmental and health risks. The findings suggest further research and optimization for sustainable and efficient engine performance in pursuing greener transportation fuels, highlighting the potential of nanoparticles in biodiesel blends.

Cardiovascular diseases, particularly coronary artery disease, pose big challenges to human life. Deployment of the stent is a preferable treatment for the above-mentioned disease. However, stents are usually made up of shape memory alloy called Nitinol. The poorer surface finish on the machined nitinol stents accelerates the migration of Nickel ions from the implanted nitinol stent, which is considered toxic and can lead to stenosis. The current study deals with controlling surface quality by minimising surface roughness and improving corrosion resistance. Femtosecond laser (fs-laser 10−15 s) micromachining was employed to machine the Nitinol surface to achieve sub-micron surface roughness. The Grey relational analysis (GRA)-coupled design of the experimental technique was implemented to determine optimal levels of four micromachining parameters (laser power, pulse frequency, scanning speed, and scanning pattern) varied at three levels to achieve minimum surface roughness and to maximise the volume ablation. The results show that to yield minimum surface roughness and maximum volume ablation, laser power and scanning speed are in a higher range. In contrast, the pulse frequency is lower, and the scanning pattern is in a zig-zag manner. ANOVA results manifest that scanning speed is the predominant factor in minimising surface roughness, followed by pulse frequency. Furthermore, the corrosion behaviour of the machined nitinol specimens was evaluated, and the results show that specimens with lower surface roughness had lower corrosion rates.

Over the past few years, the use of DC-DC buck-boost converters for Photovoltaic (PV) in renewable energy applications has increased for better results. One of the main issues with this type of converter is that output voltage is achieved with the undesired ripples. Many models are available in the literature to address this issue, but very limited work is available that achieves the desired goal using deep learning-based models. Whenever it comes to the PV, then it is further limited. Here, a deep learning-based model is proposed to reduce the steady-state time and achieve the desired buck- or boost mode for PV modules. The deep learning-based model is trained using data collected from the conventional PID controller. The output voltage of the experimental setup is 12V while the input voltage from the PV modules is 10V (when the sunlight decreases) to 24V (for 3.6 kVA) to 48V (for more than 5 kVA). It is among the few models using a single big battery (12V) for off-grid and on-grid for a single building. Experimental results are validated using objective measures. The proposed model outperforms the conventional PID controller-based buck-boost converters. The results clearly show improved performance in terms of steady-state and less overshoot.

The increase in strength and stiffness of a metal matrix composite connecting (MMC) rod when compared to conventional rods have motivated researchers in this area. This opens a new window for the present research, here Al7075 alloy and Al7075-based composite connecting rods were fabricated by machining composite blocks using computer numerical control machining centre. Al7075-based composite connecting rods comprises of 91 % Al7075, 3 % hexagonal boron nitride (h-BN) and 6 % of zirconium dioxide (ZrO2). Modal characteristics and mechanical performance of the prepared components were analysed. An experimental modal analysis was conducted on the connecting rod under fixed-free condition to identify the natural frequency and its mode shapes, further the outcomes were compared with the numerical values. The ANSYS workbench is used to estimate the component's failure load based on finite element (FE) approach. The results obtained from modal analysis revealed that the composite connecting rod is more dynamically stable than its unreinforced counterpart. Composite connecting rods also showed better load-bearing capacity as compared to Al7075 in terms of tensile and compressive loading. Failure load analysis results indicate that under compressive load the component bends along the shank (I-beam), while under tensile load, cracks originate at the section connecting the piston pin end and the I-beam. The composite connecting rod sustained 13.5 % higher compressive load and16.5 % higher tensile load than the Al7075 connecting rod, making it a suitable alternative material. The failure mechanisms have been investigated by extensive scanning electron micrography of fabricated connecting rods.

Abstract Perovskites are the key enabler materials for the solar cell applications in the achievement of high performance and low production costs. In this article, the structural, mechanical, electronic, and optical properties of rubidium-based cubic nature perovskite LiHfO3 and LiZnO3 are investigated. These properties are investigated using density-functional theory with the aid of CASTEP software by introducing ultrasoft pseudo-potential plane-wave (USPPPW) and GG-approximation-PB-Ernzerhof exchange–correlation functionals. It is investigated that the proposed compounds exhibit stable cubic phase and meet the criteria of mechanical stability by the estimated elastic properties. Also, according to Pugh's criterion, it is noted that LiHfO3 is ductile and LiZnO3 is brittle. Furthermore, the electronic band structure investigation of LiHfO3 and LiZnO3 shows that they have indirect bandgap (BG). Moreover, the BG analysis of the proposed materials shows that these are easily accessible. Also, the results for partial density of states (DOS) and total DOS confirm the degree of a localized electron in the distinct band. In addition, the optical transitions in the compounds are examined by fitting the damping ratio for the notional dielectric functions scaling to the appropriate peaks. At absolute zero temperature, the materials are observed as semiconductors. Therefore, it is evident from the analysis that the proposed compounds are excellent candidates for solar cells and protective rays applications.

Graphene-based metamaterials are gaining popularity for developing various reconfigurable and electrically tunable optical devices – especially in terahertz (THz) and infrared (IR) bands. Therefore, in this paper, we aim to investigate the broadband metamaterial-based absorber that efficiently absorbs the THz radiation ranging from 2.2 to 4.6 THz. The proposed absorber comprises a simple meta-square ring of graphene, which possesses different slots in its structure to induce multiple plasmonic resonances. It is observed that the proposed absorber manifests above 95% absorption for the normally incident THz waves, and it also maintains its absorption value over 80% for different obliquely incident operating conditions. Furthermore, the proposed absorber shows polarization-insensitive features. In addition, the absorption characteristics regulate from 95% to 15% by adjusting the chemical potential of graphene from 1 eV to 0.1 eV. Some of the salient features of the proposed absorber is largest reported bandwidth for single layer absorber with smallest footprint without sacrificing polarization insensitivity or amplitude tunability. From the application point of view, it could provide the pathway for implementing switching, cloaking, smart absorbers, and detection phenomena in the THz range.

Perovskite materials are considered the gateway of various physical applications to meet the production and consumption of energy and medical fields. Density Functional Theory (DFT) becomes the most important field in the modern era to investigate perovskite materials for various physical properties. DFT nowadays is used to explore the perovskite materials for a lot of applications like photocatalytic, optoelectronic, and photovoltaics. We discussed radium based cubic hydrides RbRaX3 (while X = F & Cl) perovskite material's electrical, optical, elastic, & physical characteristics with the help of DFT-based CASTEP code with PBE exchange-correlation efficient of GGA. The RbRaF3 & RbRaCl3 have three-dimensional nature by means of space group 221 (Pm3 m). According to electronic characteristics, the direct bandgap of RbRaF3 RbRaCl3 are 3.18eV and 2.209eV, respectively. Both compounds are brittle in nature via Poisson's ratio & Pugh's criteria. Thus, our novel RbRaX3 (X = F and Cl) compounds have excellent applications for solar cell and medical areas.

One of the challenges for Mobile Network Operators (MNO) in 5G deployment is to ensure reliability in the various sections of the network as the new services and applications, for instance, video on demand, telemedicine, online learning, smart transportation and augmented reality require not only high bandwidth but also demand uninterrupted service. However, this reliability requires substantial investment. Therefore, MNO only deploys protection or backup resources in the network unless it is cost-effective. The study aims to present a reliable and low-cost protection scheme based on an Ultra-Dense Wavelength Division Multiplexing Passive Optical Network (UDWDM PON) for the transport layer of the 5G network, i.e., for the fronthaul/backhaul section. We have evaluated the Capital Expenditure (CAPEX) cost of UDWDM PON with and without protection in a dense urban area. We also measure the figure of merit between the cost and reliability of the system and, subsequently, confirm that the proposed protection scheme can achieve system reliability up to four nines with very low additional CAPEX investment. Finally, the efficacy of the proposed protection scheme is also demonstrated through simulation experiments.

Perovskite materials play a vital role in the field of material science via experimental as well as theoretical calculations. Radium semiconductor materials are considered the backbone of medical fields. These materials are considered in high technological fields to be used as controlling the decay ability. In this study, radium-based cubic fluoro-perovskite XRaF3 (where X = Rb and Na) are calculated using a DFT (density functional theory). These compounds are cubic nature with 221 space groups that construct on CASTEP (Cambridge-serial-total-energy-package) software with ultra-soft PPPW (pseudo-potential plane-wave) and GGA (Generalized-Gradient-approximation)-PBE (Perdew-Burke-Ernzerhof) exchange-correlation functional. The structural, optical, electronic, and mechanical properties of the compounds are calculated. According to the structural properties, NaRaF3 and RbRaF3 have a direct bandgap with 3.10eV and 4.187eV of NaRaF3 and RbRaF3, respectively. Total density of states (DOS) and partial density of states (PDOS) provide confirmation to the degree of electrons localized in distinct bands. NaRaF3 material is semiconductors and RbRaF3 is insulator, according to electronic results. The imaginary element dispersion of the dielectric function reveals its wide variety of energy transparency. In both compounds, the optical transitions are examined by fitting the damping ratio for the notional dielectric function scaling to the appropriate peaks. The absorption and the conductivity of NaRaF3 compound is better than the RbRaF3 compound which make it suitable for the solar cell applications increasing the efficiency and work function. We observed that both compounds are mechanically stable with cubic structure. The criteria for the mechanical stability of compounds are also met by the estimated elastic results. These compounds have potential application in field of solar cell and medical. Objectives: The band gap, absorption and the conductivity are necessary conditions for potential applications. Here, literature was reviewed to check computational translational insight into the relationships between absorption and conductivity for solar cell and medical applications of novel RbRaF3 and NaRaF3 compounds.

Optical fibers have been involved in the area of sensing applications for more than four decades. Moreover, interferometric optical fiber sensors have attracted broad interest for their prospective applications in sensing temperature, refractive index, strain measurement, pressure, acoustic wave, vibration, magnetic field, and voltage. During this time, numerous types of interferometers have been developed such as Fabry-Perot, Michelson, Mach-Zehnder, Sagnac Fiber, and Common-path interferometers. Fabry-Perot interferometer (FPI) fiber-optic sensors have been extensively investigated for their exceedingly effective, simple fabrication as well as low cost aspects. In this study, a wide variety of FPI sensors are reviewed in terms of fabrication methods, principle of operation and their sensing applications. The chronology of the development of FPI sensors and their implementation in various applications are discussed.

A canonical problem configured in three different arrangements of periodic multilayered isotropic dielectric material layers with a dissipative dielectric defect, to guide multiple compound Tamm waves with Uller–Zenneck wave characteristics, was formulated and solved. The numerical solutions showed multiple Tamm waves guided at a fixed wavelength along the dissipative defect with same polarization state. These waves propagate with different phase speeds, different propagation distances, different field localizations, and different field profiles. The results identified excitation of symmetric and anti-symmetric solutions of p-polarized Tamm waves and p- and s-polarized waveguide modes. The high phase speed solutions ceased to exist beyond a certain limit of dissipative dielectric defect thickness, but the low phase speed solutions were computed for a wide range of dissipative dielectric defect thickness. The Tamm waves were compounded when the thickness of defect is very small and transmuted into waveguide modes for increasing thickness of dissipative dielectric defect because most of the energy is then strongly confined to the dissipative dielectric defect. The excitation of multiple Tamm waves and waveguide modes at a given dissipative dielectric defect thickness and fixed wavelength can be considered for multi-channel optical communication and sensing applications. [ABSTRACT FROM AUTHOR]