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Group decision-making (GDM) is crucial in various components of graph theory, management science, and operations research. In particular, in an intuitionistic fuzzy group decision-making problem, the experts communicate their preferences using intuitionistic fuzzy preference relations (IFPRs). This approach is a way that decision-makers rank or select the most desirable alternatives by gathering criteria-based information to estimate the best alternatives using a wider range of knowledge and experience. This article proposes a new statistical measure in a fuzzy environment when the data is ambiguous or unreliable to solve a decision-making problem. This study uses the variation coefficient measure combined with intuitionistic fuzzy graphs (IFG) and Laplacian energy (LE) to solve a GDM problem that utilizes intuitionistic fuzzy preference relations (IFPRs) to select a reliable alliance partner. Initially, the Laplacian energy determines the weight of individual standards, and the obtained weight average further estimates the overall criterion weight vector. We establish the authority criteria weights using the variation coefficient measure and then ultimately rank the alternatives for each criterion using the same measure. We examine four distinct companies Alpha, Beta, Delta, and Zeta to conduct a realistic GDM to choose which alliance partner would be ideal. We successfully implemented the suggested technique, determining that Alpha satisfies company standards and is ranked first among other companies. Moreover, this technique is useful for all kinds of Intuitionistic fuzzy group decision-making problems to select optimal ones.
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BACKGROUND: Cubic perovskite titanium stannous oxide (TiSnO3) is a promising material for various applications due to its functional properties. However, understanding how these properties change under external stress is crucial for its development and optimization. METHOD: This study employed density functional theory calculations to investigate the structural, electronic, optical, thermal, and mechanical properties of TiSnO3 under varying degrees of external static isotropic stress (0-120 GPa). RESULTS: The study reveals a significant decrease in the bandgap of TiSnO3 with increasing stress due to lattice modifications and the formation of delocalized electrons. Partial density of states analysis indicates that Sn and O states play a key role in shaping the electronic band structure. TiSnO3 exhibits increased light absorption with stress, accompanied by a blue shift in absorption peaks, whereas, both polarizability and refractive index decrease with increasing stress. Mechanically, all elastic moduli (bulk, shear, and Young's) show an increase under stress, signifying a stiffening response of the material under stress. Similarly, the Pugh ratio suggests a transition from ductile to brittle behaviour at elevated stress levels. Phonon dispersion calculations indicate the instability of the cubic phase at 0 K. However, a phonon gap emerges at 30 GPa and widens with increasing stress. X-ray diffraction further supports these findings by demonstrating a shift in diffraction peaks towards higher angles with increasing stress, consistent with the applied stress. CONCLUSION: In conclusion, this computational study offers a thorough understanding of how external stress influences the properties of TiSnO3, providing valuable insights for potential applications in various fields.
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Exploring high strength materials with a higher concentration of reinforcements in the alloy proves to be a challenging task. This research has explored magnesium-based composites (AZ31B alloy) with tungsten carbide reinforcements, enhancing strength for medical joint replacements via league championship optimisation. The primary objective is to enhance medical joint replacement biomaterials employing magnesium-based composites, emphasising the AZ31B alloy with tungsten carbide reinforcements. The stir casting method is utilised in the manufacture of magnesium matrix composites (MMCs), including varied percentages of tungsten carbide (WC). The mechanical characteristics, such as micro-hardness, tensile strength, and yield strength, have been assessed and compared with computational simulations. The wear studies have been carried out to analyse the tribological behaviour of the composites. Additionally, this study investigates the prediction of stress and the distribution of forces inside bone and joint structures, therefore offering significant contributions to the field of biomedical research. This research contemplates the use of magnesium-based MMCs for the discovery of biomaterials suitable for medical joint replacement. The study focuses on the magnesium alloy AZ31B, with particles ranging in size from 40 to 60 microns used as the matrix material. Moreover, the outcomes have revealed that when combined with MMCs based on AZ31B-magnesium matrix, the WC particle emerges as highly effective reinforcements for the fabrication of lightweight, high-strength biomedical composites. This study uses the league championship optimisation (LCO) approach to identify critical variables impacting the synthesis of Mg MMCs from an AZ31B-based magnesium alloy. The scanning electron microscopy (SEM) images are meticulously analysed to depict the dispersion of WC particulates and the interface among the magnesium (Mg) matrix and WC reinforcement. The SEM analysis has explored the mechanisms underlying particle pull-out, the characteristics of inter-particle zones, and the influence of the AZ31B matrix on the enhancement of the mechanical characteristics of the composites. The application of finite element analysis (FEA) is being used in order to make predictions regarding the distribution of stress and the interactions of forces within the model of the hip joint. This study has compared the physico-mechanical and tribological characteristics of WC to distinct combinations of 0%, 5%, 10% and 15%, and its impact on the performance improvements. SEM analysis has confirmed the findings' improved strength and hardness, particularly when 10%-15% of WC was incorporated. Following the incorporation of 10% of WC particles within Mg-alloy matrix, the outcomes of the study has exhibited enhanced strength and hardness, which furthermore has been evident by utilising SEM analysis. Using ANSYS, structural deformation and stress levels are predicted, along with strength characteristics such as additional hardness of 71 HRC, tensile strength of 140-150 MPa, and yield strength closer to 100-110 MPa. The simulations yield significant insights into the behaviour of the joint under various loading conditions, thus enhancing the study's significance in biomedical environments.
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Aleaciones , Magnesio , Ensayo de Materiales , Aleaciones/química , Magnesio/química , Compuestos de Tungsteno/química , Materiales Biocompatibles/química , Humanos , Resistencia a la Tracción , Articulación de la CaderaRESUMEN
An effort was being made to incorporate waste bagasse ash (WBA) both in carbonized and uncarbonized form into the formulation of Al6063 matrix-based metal matrix composites (MMC's) by partially substituting ceramic particles for them. In the process of developing composites, comparative research on carbonized WBA and uncarbonized bagasse powder was carried out in the role of reinforcement. Microstructure investigations revealed that carbonized WBA particles were properly distributed throughout the aluminum-base metal matrix alloy. They also had the appropriate level of wettability. The reinforcement of carbonized WBA particles in AA6063-based matrix material had a maximum tensile strength of 110 MPa and a maximal hardness of 39 BHN when 3.75 wt % of the particles were used. The deterioration in tensile strength (6.25 wt % of WBA) and the appearance of porosity and blowholes can be enumerated by tensile fractography-based scanning electron microscopy (SEM) analysis. The reinforcement of carbonized WBA particles in AA6063-based matrix material was found to have a maximal percent elongation of 14.42% and the highest fracture toughness of 15 Joules when 1.25 wt % of the particles were employed. For AA6063/3.75 wt % carbonized WBA-based MMC's, the minimum percent porosity was determined to be 5.83, and the minimum thermal expansion was found to be 45 mm3. As the percentage of reinforcement in bagasse-reinforced composites increases, the density of the material, the amount of corrosion loss, and the cost all decrease gradually. The AA6063 matrix, with a composition of 3.75 wt % carbonized WBA-based MMC's, had satisfactory specific strength and corrosion loss. The AA6063 alloy composite's microstructure analysis revealed that carbonized WBA enhanced the material's mechanical characteristics, contributing to its excellent mechanical capabilities. The results of the corrosion test showed that carbonized WBA-reinforced composites exhibited reduced weight loss due to corrosion, whereas uncarbonized bagasse powder was an inappropriate reinforcement. The SEM analysis of AA6063 alloy/3.75 wt % carbonized WBA ash reinforcement-based MMC's exposed to a 3.5 wt % NaCl solution has exhibited the development of corrosion pits as a result of localized attack by the corrosive environment. The thermal expansion test showed that the composite with uncarbonized bagasse powder as reinforcement have a high shrinkage rate in comparison with the composite with 3.75 wt %. The composite's mechanical characteristics and thermal stability were enhanced by the presence of hard phases like SiO2, Al2O3, Fe2O3, CaO, and MgO, as revealed by X-ray diffraction analysis. This made it suitable for use in a variety of applications.
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This study explored the impact of varying weight percentages of TiMoVWCr high-entropy alloy (HEA) powder addition on A356 composites produced using friction stir processing (FSP). Unlike previous research that often focused on singular aspects, such as mechanical properties, or microstructural analysis, this investigation systematically examined the multifaceted performance of A356 composites by comprehensively assessing the microstructure, interfacial bonding strength, mechanical properties, and wear behavior. The study identified a uniform distribution of TiMoVWCr HEA powder in the composition A356/2%Ti2%Mo2%V2%W2%Cr, highlighting the effectiveness of the FSP technique in achieving homogeneous dispersion. Strong bonding between the reinforcement and matrix material was observed in the same composition, indicating favorable interfacial characteristics. Mechanical properties, including tensile strength and hardness, were evaluated for various compositions, demonstrating significant improvements across the board. The addition of 2%Ti2%Mo2%V2%W2%Cr powder enhanced the tensile strength by 36.39%, while hardness improved by 62.71%. Similarly, wear resistance showed notable enhancements ranging from 35.56 to 48.89% for different compositions. Microstructural analysis revealed approximately 1640.59 grains per square inch for the A356/2%Ti2%Mo2%V2%W2%Cr processed composite at 500 magnifications. In reinforcing Al composites with Ti, Mo, V, W, and Cr high-entropy alloy (HEA) particles, each element imparted distinct benefits. Titanium (Ti) enhanced strength and wear resistance, molybdenum (Mo) contributed to improved hardness, vanadium (V) promoted hardenability, tungsten (W) enhanced wear resistance, and chromium (Cr) provided wear resistance and hardness. Anticipating the potential applications of the developed composite, the study suggests its suitability for the aerospace sector, particularly in casting lightweight yet high-strength parts such as aircraft components, engine components, and structural components, underlining the significance of the investigated TiMoVWCr HEA powder-modified A356 composites.
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Herbal medicinal plants have been used for centuries in traditional medicine, and it is interesting to see how modern research has identified the active compounds responsible for their therapeutic effects. The green synthesis of silver nanoparticles using herbal medicinal plants, such as Swertia chirata, is particularly noteworthy due to its antimicrobial properties. In the current study, the Swertia chirata plant was collected for the first time from the region of Murree, Punjab, Pakistan. After collection, extracts were prepared in different solvents (ethanol, methanol, chloroform, and distilled water), and silver nanoparticles were synthesized by reducing silver nitrate (AgNO3). The UV-visible spectrophotometer, SEM, and EDX were used to characterize the synthesized nanoparticles in terms of their size and shape. The phytochemical analysis of crude extract was performed to determine the presence of different kinds of phytochemicals. The antibacterial activity of plant extracts and the silver nanoparticles were then assessed using the agar well diffusion method against various pathogenic bacteria. The results showed that the plant contains several phytochemicals with remarkable antioxidant potential. The antibacterial analysis revealed that silver nanoparticles and the plant extracts exhibited a significant zone of inhibition against human pathogenic bacteria (Escherichia coli, S. capitis, B. subtilis, and Pseudomonas aeruginosa) as compared to the cefixime and norfloxacin. This implies that the nanoparticles have the potential to be used in nano-medicine applications, such as drug delivery systems, as well as for their antibacterial, antifungal, and antiviral activities. Additionally, the development and application of materials and technologies at the nanometer scale opens possibilities for the creation of novel drugs and therapies. Overall, the study highlights the promising potential of herbal medicinal plants found in Murree, Punjab, Pakistan, and green-synthesized silver nanoparticles in various fields of medicine and nanotechnology.
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Deposition of high entropy alloy FeCoNiMnCu on SS-304 was carried out by microwave energy for application in "solid oxide fuel-cell (SOFC) interconnects". The ball-milling has been performed by taking "Fe, Co, Ni, Mn, and Cu" in equal 20 wt. % of before deposited on SS-304 substrate. The deposited steel with 20% Fe 20% Co 20% Ni 20% Mn 20% Cu high entropy alloy (HEA) was exposed to thermal-exposure in the air for up to 10 weeks at 800 °C. The uniform cladding distribution of 20% Fe 20% Co 20% Ni 20% Mn 20% Cu HEA particles can be apparently observed on SS-304 substrate by utilizing Scanning Electron Microscope (SEM), and Optical microscopy analysis. Homogeneity in the interfacial layer was evident by employing Scanning Electron Microscope (SEM) characterization. Results have indicated that after the thermal exposure of deposited steel with 20% Fe 20% Co 20% Ni 20% Mn 20% Cu in the air for up to ten weeks at 800 °C, a "protective Cr2O3 layer", and "high-entropy spinel coating" of (Fe, Co, Ni, Mn, Cu)3O4 have been formed. During microwave cladding, the emergence of harder-phases has contributed to the raised hardness. The wear behavior after coating of 20% Fe 20% Co 20% Ni 20% Mn 20% Cu HEA on SS-304 substrate has significantly enhanced due to the strengthened wear resistance and hardness of the coatings. Findings have exhibited that the formation of (Fe, Co, Ni, Mn, Cu)3O4 phase is a potential coating material for "SOFC interconnects" applications. Moreover, the cladding of SS304 with a composition of 20% Fe, 20% Co, 20% Ni, 20% Mn, and 20% Cu has demonstrated remarkable stability under thermal expansion studies. As the findings have revealed that the composite cladding has efficiently withstand significant variations in volume when subjected to elevated temperatures for a prolonged period of time, thus, exhibiting its superior thermal stability for SOFC-interconnect applications. Furthermore, the SEM images of the cladding surface, surface hardness, and tribocorrosion behavior of the coated material have been observed to identify the 20% Fe 20% Co 20% Ni 20% Mn 20% Cu HEA coating effect on SS-304 steel-substrate.
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The present investigation has employed recycled waste glass powder (WGP) and silicon nitride (Si3N4) as reinforcing-agents within AZ91D-matrix composites. The composites were fabricated by employing the vacuum stir casting technique to mitigate the effects of oxidation and to ensure homogeneity, uniformity, and superior wettability among the AZ91D-matrix and reinforcements. A microscopic study provided confirmation of a uniform dispersion of WGP and Si3N4 particles throughout the AZ91D-matrix. The tensile strength of the AZ91D/WGP/Si3N4 composites rise with the inclusion of WGP particulates by up to 1.5 percent in AZ91D/7.5% Si3N4. However, the tensile strength of the AZ91D/9%Si3N4 composite have showed maximum value as compared to other chosen formulations/combinations in the current investigation. The tensile strength of AZ91D/1.5% WGP/7.5% Si3N4 composites has strengthened up to 12.13 percent with the comparison of base alloy AZ91D-matrix. In A1 formulated composite, the amount of WGP particulate has enhanced the hardness of the AZ91D-alloy by up to 1.5 percent. Findings, nevertheless has exhibited that the A6 formulated composite had superior outcomes in terms of hardness. The incorporation of "reinforcing-constituent particulates" with 1.5%WGP + 7.5%Si3N4 combination within the AZ91D-matrix, has further increased fatigue-strength by around 57.84 percent. A weight-loss of 0.312 mg was being unveiled for the A1 formulated fabricated composite. The weight-loss for the A6 formulated fabricated composite, however, was reported to be 0.294 mg. At 5 N loads, 2 m/s sliding speed, and 1000 m of sliding distance, the developed 1.5%WGP/7.5%Si3N4/AZ91D composites was reported to have a rate of wear, and frictional coefficient of 0.0025 mm3/m and 0.315, respectively. The investigation employing scanning electron microscopy (SEM) identified the presence of corrosion pits on the surfaces that had undergone corrosion. These pits were found to be a result of localised surface assaults occurring in corrosive environments. Additionally, SEM pictures of the worn surfaces indicated the emergence of microcracks, which may be associated to the conditions of cyclic loading. Moreover, the tensile-fractography examination for the developed 1.5%WGP/7.5%Si3N4/AZ91D composites has exhibited the brittle fracture failure, including cracks and debonding phenomena. In addition, the EDS spectra-analysis have revealed an apparent existence of the observed Mg-peak, Si-peak, Al-peak, Ca-peak, and O-peak for the 1.5%WGP/7.5%Si3N4/AZ91D composites. Furthermore, the utilisation of X-ray diffraction analysis effectively determined the existence of hard phases inside the AZ91D-matrix, which significantly contributed to the reported enhancement in wear resistance. The development of harder-phases has included, α-Mg, Al12Mg17, SiO2, Si3N4, MgO, and CaO phases within the composite has been accountable for the enhancement of the tribomechanical, and wear-resistance characteristics of the AZ91D/WGP/Si3N4 composites. The Si3N4 has been discovered to have a substantial impact on enhancing mechanical performance and raising the resistance to wear.
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Sustainable agricultural practices help to manage and use natural resources efficiently. Due to global climate and geospatial land design, soil texture, soil-water content (SWC), and other parameters vary greatly; thus, real time, robust, and accurate soil analytical measurements are difficult to be developed. Conventional statistical analysis tools take longer to analyze and interpret data, which may have delayed a crucial decision. Therefore, this review paper is presented to develop the researcher's insight toward robust, accurate, and quick soil analysis using artificial intelligence (AI), deep learning (DL), and machine learning (ML) platforms to attain robustness in SWC and soil texture analysis. Machine learning algorithms, such as random forests, support vector machines, and neural networks, can be employed to develop predictive models based on available soil data and auxiliary environmental variables. Geostatistical techniques, including kriging and co-kriging, help interpolate and extrapolate soil property values to unsampled locations, improving the spatial representation of the data set. The false positivity in SWC results and bugs in advanced detection techniques are also evaluated, which may lead to wrong agricultural practices. Moreover, the advantages of AI data processing over general statistical analysis for robust and noise-free results have also been discussed in light of smart irrigation technologies. Conclusively, the conventional statistical tools for SWCs and soil texture analysis are not enough to practice and manage ergonomic land management. The broader geospatial non-numeric data are more suitable for AI processing that may soon help soil scientists develop a global SWC database.