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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.

Abstract Perovskite solar cells (PSCs) hold potential for low-cost, high-efficiency solar energy, but their sensitivity to moisture limits practical application. Current fabrication requires controlled environments, limiting mass production. Researchers aim to develop stable PSCs with longer lifetimes under ambient conditions. In this research work, we investigated the stability of perovskite films and solar cells fabricated and annealed in natural air using four different anti-solvents: toluene, ethyl acetate, diethyl ether, and chlorobenzene. Films (about 300 nm thick) were deposited via single-step spin-coating and subjected to ambient air-atmosphere for up to 30 days. We monitored changes in crystallinity, electrical properties, and optics over time. Results showed a gradual degradation in the films’ crystallinity, morphology, and electro-optical properties. Notably, films made with ethyl acetate exhibited superior stability compared to other solvents. These findings contribute to advancing stable and high-performance PSCs manufactured under normal ambient conditions. In addition, we also discuss the possible machine learning (ML) approach to our future work direction to optimize the materials structures, and synthesis process parameters for future high-efficient perovskite solar cells fabrication.

The emerging need for a sustainable environment prompts the research community to develop functional materials with bio- and organic waste. This research advocates biodegradable waste management and its performance evaluation. The involvement of Caesalpinia decapetala (CD) as a potential reinforcement in the epoxy matrix and its analytical evaluation of thermal stability are novel ideas for disposing of bio and organic waste. Three different variants (10, 20, and 30wt%) of CD seed particles are used to develop the epoxy composite, and further, their influence on dynamic mechanical characteristics such as damping type, loss modulus, and storage modulus has been investigated. The results corroborate that the higher CD seed content (30 wt%) in the epoxy matrix enhances the storage modulus, loss modulus, and damping on a scale of 1.14,1.25, and 1.07 times that of the neat epoxy matrix. The reason behind the improved dynamic properties has been validated through theoretical modeling. A substantial increment in the degree of entanglement and activation energy in the band of 8.33 * [10.sup.-3] moles/[m.sup.3] and 20.201 kJ/mol, respectively, in comparison with neat epoxy, is considered to be good authentication for the thermal stability of the CD 30 specimen. The analytical prediction of storage modulus is executed with five different models, whereas damping behavior is executed with two different models. The analytically estimated results are matched with the experimental ones, and we conclude that they are in fair agreement with the experimental findings. KEYWORDS Caesalpinia decapetala seed, damping, loss modulus, storage modulus Highlights * Novel Caesalpinia decapetala (CD) epoxy composite is examined using dynamic mechanical analysis test. * 30 wt% CD composites reveal the highest improvement in storage modulus and damping. * Theoretical modeling to evaluate dispersion effectiveness and degree of entanglement. * Storage modulus and damping are validated with numerous theoretical models., 1 | INTRODUCTION Polymer matrix composites, which are very well known for their exceptional strength-to-weight ratio, were frequently used but had several drawbacks. These drawbacks include being non-renewable, non-recyclable, and [...]

Pumice, which is prevalent in Ethiopia, is formed naturally during the quick cooling and solidifying of molten lava. Pumice is a naturally occurring mineral that, due to its high thermal resistance and lightweightness, can be an excellent candidate for reinforcing material for polymers. The present study investigates epoxy-based composites reinforced with pumice particles by varying the pumice content (0,10, 20, and 30 vol%). The densities of all composites reduce in comparison with neat epoxy as the volume proportion of pumice increases credited to the low density pumice particles. Tensile stress-strain curves depict neat epoxy with higher deformation than other pumice particulate-filled composites in the linear elastic area followed by rapid brittle failure. Tensile modulus of all the composites increases in the range of 13%-67% in comparison with neat epoxy. The compressive characteristics of composites are greatly improved by the addition of pumice. Compressive moduli and specific compressive moduli of all composites increase with increasing volume fraction of pumice by 54%-58% and 65%-93%, respectively, in comparison with neat epoxy. The fracture toughness of P-10, P-20, and P-30 composites improved by 18%, 54%, and 59%, respectively, as compared with neat epoxy mainly attributed to the foam-like structure of pumice particles. SEM micrographs are used to analyze the morphology of compression-tested specimens. Property mapping highlights the advantages of utilizing composites from present work over numerous syntactic foams. KEYWORDS composites, compression, epoxy, pumice, tensile Highlights * Novel lightweight pumice particles reinforced epoxy composites are fabricated to study the physical and mechanical properties. * Tensile modulus of all the composites increases in the range of 13%-67% in comparison with neat epoxy. * The compressive characteristics of composites are greatly improved by the addition of pumice. * Property mapping highlights the advantages of utilizing pumice over numerous syntactic foams., 1 | INTRODUCTION Nowadays, businesses all over the world require materials with intricate material qualities that conventional materials such as ceramics, metals, and polymeric materials do not offer. (1) Material [...]

The increasing occurrence of severe vulnerabilities, such as natural catastrophes and man-made attacks, has resulted in a corresponding rise in power outages on a global scale. Given the growing recognition of such exceptional occurrences, there is a pressing need to examine the matters pertaining to resilience and the mitigation of risks. This study presents a comprehensive overview of the current state-of-the-art in power system resiliency, as well as an exploration of the measures required to ensure a sustainable environment.These instances of measures include resilience by enabling localized generation and distribution of electricity,diversification of energy resources, withstanding of severe weather conditions, cyberattacks and enabling communities to proactively address the consequences of power outages. There are multiple approaches to bolstering resiliency, which aim to facilitate recovery from unforeseen circumstances and promote stability in the face of uncertain events. These measures also serve to mitigate the impact of unexpected incidents such as power outages. Integrating unpredictable renewable energy sources like solar and wind power into energy networks is difficult, especially in terms of resilience. Renewable energy output fluctuates owing to weather and time of day, requiring sophisticated grid management, energy storage, and demand-response mechanisms to maintain system balance and resilience. This study elucidates the enhanced principles of power system dependability and resilience, in addition to several ways for establishing a sustainable power ecosystem. It examines the complex dynamics of risk assessment, including equipment failures, natural disasters, and human errors, to determine their likelihood and implications. Moreover, the study thoroughly examines the critical moments that occur after accidents, emphasizing the need of prompt reaction and recovery measures in reducing downtime and restoring regular operations to impacted power networks. This involves determining the fundamental reasons behind the incidents, such as whether they arise from equipment malfunctions, human mistakes, external influences like natural calamities, or cyber assaults. In addition, the report examines the efficacy of current response protocols and emergency procedures in reducing the impact of accidents and restoring regular operations to impacted electrical systems.

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.

The aim of this study is to explore the potential compatibility of copper oxide nano-powders synthesised via hydrothermal method for solar cell applications by triggering a reaction between copper acetate and various reducing agents derived from natural resources, including Arabic gum, molasses, starch, and vinegar. X-ray diffraction analysis revealed the crystalline phases of the synthesised materials, indicating the successful synthesis of copper oxide material, which was confirmed by identifying patterns that matched specific copper oxide phases. Fourier transform infrared spectroscopy was employed to analyse the molecular vibrations and chemical compounds present in the reducing agents. The reducing properties of the selected materials and their capacity to convert copper acetate into copper oxide were validated. Field-emission microscopy and transmission electron microscopy analyses of the synthesised copper oxide nanoparticles (NPs) revealed variations in particle size and morphology. These variations were dependent on the particular reducing agent utilised during synthesis. Moreover, the carrier concentration, mobility, and resistivity were evaluated as the electrical properties of the spin-coated copper oxide thin films. Hall effect analysis determined that the choice of reducing agent significantly influenced the carrier concentration (n) and mobility (µ) of the films. Remarkably, nano copper oxide films synthesised using starch exhibited irregular spherical grains with porous surfaces. Starch-synthesised samples showed the highest conductivity of n = 1.2 × 1019 cm−3 when compared with those synthesised with other reducing agents. This suggests that the porous surfaces in the starch-synthesised films may have contributed to their enhanced conductivity compared to films synthesised with alternative reducing agents. In summary, the findings emphasised the influence of the reducing agent on the size, morphology, and electrical conductivity of the copper oxide NPs.

This study primarily investigates the antibacterial properties, tensile strength, flexural strength, impact strength, hardness, and microstructural characteristics of a composite, utilizing Scanning Electron Microscopy (SEM) for detailed analysis. The composite, crafted through a hand layup technique, optimally blends ramie and hemp fibers within an epoxy matrix. Its antibacterial efficacy was rigorously tested against common bacterial strains, demonstrating significant potential for medical and hygienic applications. The evaluation of tensile strength revealed the composite’s enhanced capability to withstand longitudinal stresses, with a peak strength of 37.81 MPa, achieved by increasing ramie fiber content. In addition, a flexural strength of 39.72 MPa underscored the material’s robust resistance to bending forces, crucial for structural uses. The composite’s impact strength, accessed via the Izod impact test, registered at 0.021 J/m2, indicating its ability to absorb and dissipate energy upon sudden impacts, making it ideal for automotive and protective gear applications. The Rockwell hardness test further quantified the composite’s resistance to surface indentation, vital for wear-resistant surfaces. SEM analysis offered a comprehensive view of the microstructural dynamics between the fibers and the matrix, especially under tensile stress, highlighting the intricacies of fiber–matrix adhesion, crack propagation, and overall composite integrity. Notably, the antibacterial properties were confirmed by an 18 mm inhibition zone, which showcases the composite’s ability to inhibit bacterial growth effectively.

Solar energy systems operate directly connected to the sun. Solar chimney power plants are privileged systems that can provide power output even in cloudy weather and during hours when there is no sun. The design and sizing of this system, which researchers focused on after its first application in the 1980s, is very effective on its performance. In this study, the collector slope and chimney slope that give maximum power output for the Manzanares pilot plant are investigated with a 3D CFD model. Simulations made using the RNG k-e turbulence model and the DO (discrete ordinates) solar ray tracing algorithm provide results that are in high compatibility with experimental data and literature. It is understood that the system provides maximum power at 0.6° collector slope and 1.5° chimney divergence angle. It is seen that the system, which gives a power output of approximately 46 kW in the reference case, exceeds the power output by 4.5 times and reaches 216.853 kW in the design that includes the collector and chimney slope. The effects of the main elements of the system on the performance are also included by changing the collector radius and chimney height while preserving these inclination angles. More than the power output in the reference case, 49.233 kW, can be achieved with the inclined design, with a collector radius of 73.2 m and a chimney height of 155.68 m. Although the effect of increasing the chimney height on power output continues after 1.2 floors, its effect decreases. In the study, it is seen that increasing the chimney height and changing the collector radius provide a greater increase in power output. Furthermore, the scope extends to the incorporation of an Artificial Neural Network (ANN) model, presenting a novel approach to predicting SCPP system performance. The findings ascertain the utilisation of 9 neurons in the hidden layer of the ANN, demonstrating a precise alignment with the study data.

The magnesium alloy composite is a vital material for automotive applications due to its features like high stiffness, superior damping resistance, high strength, and lightweight. Here, the motto of research is to establish the AZ91 alloy nanocomposite with the exposures of 0, 1, 3, and 5 volume percentages (vol%) of nano zirconium dioxide (ZrO2) particles (50nm) through fluid stir metallurgy route associated with 1x105 Pa vacuum die cast process. Exposures on structural morphology, hardness, and impact toughness of composite are analyzed and identified as the nano AZ91 alloy composite enclosed with 5vol% is homogenous particle dispersion, enhanced hardness (97.6HV), and optimum toughness of 21.2J/mm2. However, composite faces machining difficulties due to the hard abrasive particles with higher hardness, resulting in tool wear. This experiment predicts the optimum mill parameters during the end mill operation of magnesium alloy nanocomposite (AZ91/5vol%) by using a tungsten carbide coated end mill cutter to attain the maximum metal removal rate with low surface roughness and tool wear analyzed via the general linear model (GLM) ANOVA approach. The input conditions for end milling operation vary, like feed rate (0.1 -0.4mm/rev), depth of cut (0.05 -0.2mm), and spindle speed (250-1000rpm). During the ANOVA GLM approach, the L16 design experiment is fixed for further interaction analysis. The results predicted by the depth to cut and feed rate were dominant and played a major role in deciding the tool wear, surface roughness, and MRR.

In this work, we conduct acidified aqueous glycerol pre-treatment (AAG) on rice husks (RH) and utilize the response surface methodology (RSM) to assess the impact of pre-treatment parameters. The primary objective of this research is to optimize the parameters to maximize the cellulose content within RH. The parameters under consideration encompassed temperature (ranging from 80 to 110 °C), retention time (spanning 15 to 45 min), and biomass loading (varying from 5 to 10 wt. %). To achieve this optimization, we perform the Box-Behnken Design (BBD) within the framework of RSM. Additionally, we scrutinize the interactive effects of these parameters on cellulose content. Our findings unveiled a remarkable increase in cellulose content, escalating from 40 % in untreated RH to an impressive 75 % in pre-treated RH under the optimized conditions of 110 °C for 45 min with a 5.0 wt. % biomass loading. To further evaluate the effectiveness of the pre-treatment process, we conduct scanning electron microscopy (SEM) and X-ray diffraction (XRD) analyses, shedding light on alterations in surface morphology and crystallinity of RH. This investigation yields valuable insights, presenting novel opportunities for the efficient conversion of readily available rice husks into high-value products, such as biofuels and composites.

Abstract A numerical analysis of a CdTe/Si dual-junction solar cell in terms of defect density introduced at various defect energy levels in the absorber layer is provided. The impact of defect concentration is analyzed against the thickness of the CdTe layer, and variation of the top and bottom cell bandgaps is studied. The results show that CdTe thin film with defects density between 1014 and 1015 cm−3 is acceptable for the top cell of the designed dual-junction solar cell. The variations of the defect concentrations against the thickness of the CdTe layer indicate that the open circuit voltage, short circuit current density, and efficiency (ƞ) are more affected by the defect density at higher CdTe thickness. In contrast, the Fill factor is mainly affected by the defect density, regardless of the thin film’s thickness. An acceptable defect density of up to 1015 cm−3 at a CdTe thickness of 300 nm was obtained from this work. The bandgap variation shows optimal results for a CdTe with bandgaps ranging from 1.45 to 1.7 eV in tandem with a Si bandgap of about 1.1 eV. This study highlights the significance of tailoring defect density at different energy levels to realize viable CdTe/Si dual junction tandem solar cells. It also demonstrates how the impact of defect concentration changes with the thickness of the solar cell absorber layer.

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.

A healthy environment improves the quality of life on Earth, while natural disasters affect the quality of the environment. An area’s Landslide Hazard Zonation (LHZ) provides key information about the susceptibility to natural or manmade disasters. Using the Weighted Overlay Technique, this research aims to develop the landslide susceptibility and zonation mapping of Koh-e-Suleman Range (a hill station around the heritage site). Six causative factors are evaluated: geology, elevation, slope inclination, distance from streams, type of soil, and annual rainfall intensity, considering equal risk influence for all the factors. All causative factor maps were generated to yield equal classes and provide uniformity to the results except for soil types found in the study area. The findings indicate that the study area may comprise four landslide hazard zones with high, medium, low, and very low-intensity susceptibility of landslides. The accuracy of the final LHZ map is verified by comparing the hazard zonation area percentages with the global landslide inventory map from a macro-study of NASA. It was found that the study areas largely fall within low- and very low-hazard zones.

ABSTRACTThe current study examines the effect of NaOH treatment on the hardness, inter-laminar shear strength (ILSS) and water absorption behavior of epoxy composites reinforced with banana pseudostem fibers. Using the hand-lay-up method, six distinct samples are created that are composed of layers of woven and short banana fibers in both a plain and hybrid form. Plain- treated woven composites reveal the highest hardness and ILLS properties followed by the hybrid and short fiber composites. The random orientation of the fiber structure in short fiber composites results in the largest moisture absorption; this behavior is further supported by elucidating the kinetic parameters and diffusion coefficient parameters. SEM analysis confirms the improved surface of the NaOH-treated composite material.

This research aims to provide the groundwork for smartly categorizing hand movements for use with prosthetic hands. The hand motions are classified using surface electromyography (sEMG) data. In reaction to a predetermined sequence of fibre activation, every single one of our muscles contracts. They could be useful in developing control protocols for bio-control systems, such human-computer interaction and upper limb prostheses. When focusing on hand gestures, data gloves and vision-based approaches are often used. The data glove technique requires tedious and unnatural user engagement, whereas the vision-based solution requires significantly more expensive sensors. This research offered a Deep Neural Network (DNN) automated hand gesticulation recognition system based on electromyography to circumvent these restrictions. This work primarily aims to augment the concert of the hand gesture recognition system via the use of an artificial classifier. To advance the recognition system's classification accuracy, this study explains how to build models of neural networks and how to use signal processing methods. By locating the Hilbert Huang Transform (HHT), one may get the essential properties of the signal. When training a DNN classifier, these characteristics are sent into it. The investigational results reveal that the suggested technique accomplishes a better categorization rate (98.5 % vs. the alternatives).