Physicomechanical, morphological and tribo-deformation characteristics of lightweight WC/AZ31B Mg-matrix biocomposites for hip joint applications

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.

Hybridization of the swarming and interior point algorithms to solve the Rabinovich-Fabrikant system

In this study, a trustworthy swarming computing procedure is demonstrated for solving the nonlinear dynamics of the Rabinovich-Fabrikant system. The nonlinear system's dynamic depends upon the three differential equations. The computational stochastic structure based on the artificial neural networks (ANNs) along with the optimization of global search swarming particle swarm optimization (PSO) and local interior point (IP) algorithms, i.e., ANNs-PSOIP is presented to solve the Rabinovich-Fabrikant system. An objective function based on the differential form of the model is optimized through the local and global search methods. The correctness of the ANNs-PSOIP scheme is observed through the performances of achieved and source solutions, while the negligible absolute error that is around 10^-05-10^-07 also represent the worth of the ANNs-PSOIP algorithm. Furthermore, the consistency of the ANNs-PSOIP scheme is examined by applying different statistical procedures to solve the Rabinovich-Fabrikant system.

Albargi H, Ahmad A, Sarwar Z, Khaliq Z, Qadir MB, Arshad SN, Tahir R, Ali S, Jalalah M, Irfan M, Harraz FA. Nano-Silica Bubbled Structure Based Durable and Flexible Superhydrophobic Electrospun Nanofibrous Membrane for Extensive Functional Applications

Nanoscale surface roughness has conventionally been induced by using complicated approaches; however, the homogeneity of superhydrophobic surface and hazardous pollutants continue to have existing challenges that require a solution. As a prospective solution, a novel bubbled-structured silica nanoparticle (SiO₂) decorated electrospun polyurethane (PU) nanofibrous membrane (SiO₂@PU-NFs) was prepared through a synchronized electrospinning and electrospraying process. The SiO₂@PU-NFs nanofibrous membrane exhibited a nanoscale hierarchical surface roughness, attributed to excellent superhydrophobicity. The SiO₂@PU-NFs membrane had an optimized fiber diameter of 394 ± 105 nm and was fabricated with a 25 kV applied voltage, 18% PU concentration, 20 cm spinning distance, and 6% SiO₂ nanoparticles. The resulting membrane exhibited a water contact angle of 155.23°. Moreover, the developed membrane attributed excellent mechanical properties (14.22 MPa tensile modulus, 134.5% elongation, and 57.12 kPa hydrostatic pressure). The composite nanofibrous membrane also offered good breathability characteristics (with an air permeability of 70.63 mm/s and a water vapor permeability of 4167 g/m²/day). In addition, the proposed composite nanofibrous membrane showed a significant water/oil separation efficiency of 99.98, 99.97, and 99.98% against the water/xylene, water/n-hexane, and water/toluene mixers. When exposed to severe mechanical stresses and chemicals, the composite nanofibrous membrane sustained its superhydrophobic quality (WCA greater than 155.23°) up to 50 abrasion, bending, and stretching cycles. Consequently, this composite structure could be a good alternative for various functional applications.

The Microstructure and Properties of Ni-Si-La2O3 Coatings Deposited on 304 Stainless Steel by Microwave Cladding

In this investigation, microwave radiation was used alongside a combination of Ni powder, Si powder, and La₂O₃ (Lanthanum oxide) powder to create surface cladding on SS-304 steel. To complete the microwave cladding process, 900 W at 2.45 GHz was used for 120 s. "Response surface methodology (RSM)" was utilized to attain the optimal combination of microwave cladding process parameters. The surface hardness of the cladding samples was taken as a response. The optimal combination of microwave cladding process parameters was found to be Si (wt.%) of 19.28, a skin depth of 4.57 µm, irradiation time of 118 s, and La₂O₃ (wt.%) of 11 to achieve a surface hardness of 287.25 HV. Experimental surface hardness at the corresponding microwave-cladding-process parameters was found to be 279 HV. The hardness of SS-304 was improved by about 32.85% at the optimum combination of microwave cladding process parameters. The SEM and optical microscopic images showed the presence of Si, Ni, and La₂O₃ particles. SEM images of the "cladding layer and surface" showed the "uniform cladding layer" with "fewer dark pixels" (yielding higher homogeneity). Higher homogeneity reduced the dimensional deviation in the developed cladding surface. XRD of the cladded surface showed the presence of FeNi, Ni₂Si, FeNi₃, NiSi₂, Ni₃C, NiC, and La₂O₃ phases. The "wear rate and coefficient of friction" of the developed cladded surface with 69.72% Ni, 19.28% Si, and 11% La₂O₃ particles were found to be 0.00367 mm³/m and 0.312, respectively. "Few dark spots" were observed on the "corroded surface". These "dark spots" displayed "some corrosion (corrosion weight loss 0.49 mg)" in a "3.5 wt.% NaCl environment".

ANFIS-based forming limit prediction of stainless steel 316 sheet metals

Effect of microstructure on the formability of the stainless sheet metals is a major concern for engineers in sheet industries. In the case of austenitic steels, existence of strain-induced martensite ([Formula: see text]-martensite) in their micro structure causes considerable hardening and formability reduction. In the present study, we aim to evaluate the formability of AISI 316 steels with different intensities of martensite via experimental and artificial intelligence methods. In the first step, AISI 316 grade steels with 2 mm initial thicknesses are annealed and cold rolled to various thicknesses. Subsequently, the relative area of strain-induced martensite are measured using metallography tests. Formability of the rolled sheets are determined using hemisphere punch test to obtain forming limit diagrams (FLDs). The data obtained from experiments were further utilized to train and validate an artificial neural fuzzy interfere system (ANFIS). After training the ANFIS, predicted major strains by the neural network are compared to a new set experimental results. The results indicate that cold rolling has unfavorable effects on the formability of this type of stainless steels while significantly strengthens the sheets. Moreover, the ANFIS exhibits satisfactory results in comparison to the experimental measurements.

Ni-Decorated PtS2 Monolayer as a Strain-Modulated and Outstanding Sensor upon Dissolved Gases in Transformer Oil: A First-Principles Study

The first-principles theory is conducted in this paper to investigate the adsorption and electronic properties of a Ni-decorated PtS₂ (Ni-PtS₂) monolayer upon two dissolved gas species (CO and C₂H₂) in the transformer oil, thus illustrating its sensing performance and related potential to evaluate the working condition of the oil-immersed transformers. We then highlight the effect of the biaxial strain on the configuration, charge transfer, and bandgap of the adsorbed systems to expound its potential as a strain-modulated gas sensor. Results indicate that the Ni-PtS₂ monolayer undergoes chemisorption upon two species, with an E _ad value of -1.78 eV for the CO system and -1.53 eV for the C₂H₂ system. The reduced bandgap by 0.164 eV (20.05%) in the CO system and 0.047 eV (5.74%) in the C₂H₂ system imply the large feasibility of the Ni-PtS₂ monolayer to be a resistance-type sensor for CO and C₂H₂ detection, which is also verified by the I-V analysis of these systems. Besides, the applied biaxial strain can exert geometric activations on the Ni-PtS₂ monolayer, and specifically, the compressive force can further reduce the bandgap in two systems, thus promoting its sensing response upon two gases. Our work is meaningful to broaden the exploration of noble transition metal dichalcogenides for gas sensing.

Evolution of ordered nanoporous phases during h-BN growth: controlling the route from gas-phase precursor to 2D material by in situ monitoring

Large-area single-crystal monolayers of two-dimensional (2D) materials such as graphene and hexagonal boron nitride (h-BN) can be grown by chemical vapour deposition (CVD). However, the high temperatures and fast timescales at which the conversion from a gas-phase precursor to the 2D material appears, make it extremely challenging to simultaneously follow the atomic arrangements. We utilise helium atom scattering to discover and control the growth of novel 2D h-BN nanoporous phases during the CVD process. We find that prior to the formation of h-BN from the gas-phase precursor, a metastable (3 × 3) structure is formed, and that excess deposition on the resulting 2D h-BN leads to the emergence of a (3 × 4) structure. We illustrate that these nanoporous structures are produced by partial dehydrogenation and polymerisation of the borazine precursor upon adsorption. These steps are largely unexplored during the synthesis of 2D materials and we unveil the rich phases during CVD growth. Our results provide significant foundations for 2D materials engineering in CVD, by adjusting or carefully controlling the growth conditions and thus exploiting these intermediate structures for the synthesis of covalent self-assembled 2D networks.

On the Critical Heat Flux Assessment of Micro- and Nanoscale Roughened Surfaces

The boiling crisis or critical heat flux (CHF) is a very critical constraint for any heat-flux-controlled boiling system. The existing methods (physical models and empirical correlations) offer a specific interpretation of the boiling phenomenon, as many of these correlations are considerably influenced by operational variables and surface morphologies. A generalized correlation is virtually unavailable. In this study, more physical mechanisms are incorporated to assess CHF of surfaces with micro- and nano-scale roughness subject to a wide range of operating conditions and working fluids. The CHF data is also correlated by using the Pearson, Kendal, and Spearman correlations to evaluate the association of various surface morphological features and thermophysical properties of the working fluid. Feature engineering is performed to better correlate the inputs with the desired output parameter. The random forest optimization (RF) is used to provide the optimal hyper-parameters to the proposed interpretable correlation and experimental data. Unlike the existing methods, the proposed method is able to incorporate more physical mechanisms and relevant parametric influences, thereby offering a more generalized and accurate prediction of CHF (R² = 0.971, mean squared error = 0.0541, and mean absolute error = 0.185).