Munawar Abbas

The chemical reactive flow of an MHD ternary hybrid nanofluid with LTNE effects and microorganisms is briefly examined in this study using the extended Xue, Yamada-Ota, and Hamilton Crosser models. Momentum is estimated with consideration for the Darcy Forchheimer porous medium effect. This model aims to assess the performance of three THNF (trihybrid nanofluid) models: YOM, Xue, and Hamilton-Crosser. The development of cutting-edge biotechnology applications like targeted medication delivery systems and bio-remediation techniques can benefit from the valuable insights that this research provides into how microorganisms behave in intricate fluid environments. Additionally, knowing how these microorganisms interact in non-equilibrium thermal environments in nanofluid systems can be used to design more effective heat transfer systems and optimize thermal management in a variety of industrial processes, ultimately leading to increased energy efficiency and sustainability. The system of ODEs derived from the leading PDEs is solved by the MATLAB solver bvp4c package using suitable similarity variables to produce the numerical solution. The impacts of the appropriate values on the relevant fields have been illustrated graphically. It is crucial to note that the YOM and Xue ternary hybrid nanofluid models have an even greater effect than the HCM. When the interphase heat transfer characteristic increases, the thermal profile of the liquid phase rises and that of the solid phase decreases.

This model has wide-ranging applications in systems where reactive fluxes, nanofluid transport, and microorganism-driven bioconvection interact under complex boundary conditions. Gyrotactic microorganisms help to optimize the mixing and oxygen distribution in microbial culture systems, bioreactors, and biomedical equipment. The model is applicable to cooling technologies, drug delivery, chemical processing, and environmental engineering because it incorporates Stefan blowing, hybrid nanofluids, and chemical reactions. When dealing with moving or thin structures like needles or probes, this is particularly true. Additionally, it aids in the optimization of processes that depend on improved heat and mass transmission as well as the comprehension of heat generation impacts in microscale thermal management. An investigation is conducted to explore the laminar, steady flow of a hybrid nanofluid ( Al 2 O 3 − Cu / H 2 O ) with gyrotactic microorganisms across a moving thin needle. The joint impact of Stefan blowing, MHD, heat radiation, heat generation and a homogeneous reaction are considered in the analysis. Parametric studies shows that the fluid velocity is completely influenced by the Stefan blowing effect but retarded by the magnetic field strength. By enhancing heat source coefficient and radiation parameter, the temperature distribution is elevated.

In the present study, bismuth telluride (Bi₂Te₃) was selected as the base material due to its well-known thermoelectric characteristics. This semiconductor compound plays a crucial role in applications such as energy conversion, cooling technologies, and waste heat recovery systems. Lanthanum is a rare-earth element. To enhance its functional properties, lanthanum (La) was introduced into the Bi₂Te₃ matrix, forming (Bi₂Te₃)1-xLaₓ solid solutions. It is an interesting and promising area of research in the field of obtaining single-crystal thermoelectric materials. The investigation of such doped single crystals represents a promising direction for improving thermoelectric efficiency. Lanthanum (La) has been widely employed as a dopant to optimize carrier concentration, modify the crystal lattice, and improve the thermoelectric performance of Bi₂Te₃-based materials. A detailed analysis of the (Bi₂Te₃)1-xLaₓ system was carried out, including the construction of phase diagrams. It was established that within the composition range x = 0.01–0.05, a solid solution region based on Bi₂Te₃ exists at room temperature. Additionally, a eutectic interaction between Bi₂Te₃ and La was identified at approximately 15 at.% La with a temperature close to 440 °C. Lanthanum doping resulted in measurable changes in the physical properties of Bi₂Te₃ single crystals. The results demonstrate that lanthanum incorporation yields single crystals with enhanced thermoelectric and galvanomagnetic properties, making them attractive for advanced material applications. Keywords: microsolidity, solid solution, density, single crystal, thermoelectric, photovoltaic, optics, electrical converter

The suggested artificial neural networks surrogate model for Ellis’s hybrid nanofluid with Dufour-Soret characteristics and Joule heating under local thermal non-equilibrium conditions has numerous applications in advanced energy and thermal systems. It can increase mass and heat transmission in electronic cooling systems, nuclear reactors, geothermal reservoirs, and microfluidic devices. Furthermore, it is beneficial for optimizing systems involving electrically conducting fluids, such as MHD power generation, solar thermal collectors, and medicinal heat treatments, where accurate prediction of complicated non-linear transport phenomena is required. To examine how an Ellis hybrid nanofluid’s Darcy-Forchheimer flow is affected by LTNE across a spinning disk. The key aim of this study is to provide a new mathematical intelligence approach of the AI-based intelligent Levenberg–Marquardt technique under the influence of artificial neural networks (ILMT-ANNs) for optimizing Soret-Dufour effects and Joule heating in conjunction with Magneto-Marangoni phenomena. For ILMT-ANNs, the numerical data-sheet is separated into 90.8% training, 4.1% testing, and 5.1% validation. The estimated solution is analyzed, and its evaluation with a numerical solution using bvp4c is described. Regression investigation, error histogram, and fitness curves based on mean squared error (MSE) are used to verify the effectiveness and consistency of ILMT-ANNs.

This work aims to investigate the effects of thermal radiation and LTNE on the chemical reactive flow of a ternary hybrid nanofluid over a sheet containing thermo-bioconvection and oxytactic microorganisms. The model, which use artificial neural networks (ANNs) to forecast and optimize viscosity, heat dissipation, and thermal conductivity, is ideal for sophisticated cooling systems, energy storage, and biomedical applications. The ANNs has been trained using the Levenberg-Marquardt technique. The effectiveness of the scheme is supported by a number of statistical measures, such as analysis of error histograms, regression index, and convergence analysis, which show a minimum level of the best performance value ( 6 . 01 × E − 8 to 1 . 77 × E − 7 ) for the comprehensive simulation of the proposed model. Its applications include nuclear reactors, solar energy harvesting, electronic cooling, and chemical processes that require precise heat regulation. The addition of oxytactic microorganisms enhances heat transfer dynamics, boosting system efficiency and sustainability. The numerical findings are shown as tables and graphs on a Bvp4c. The liquid phase thermal profile increases while the solid phase thermal profile decreases as the interphase heat transfer parameter values grow.

This research describes an investigation into the effect of solar radiation and heat generation on propylene glycol-based trihybrid nanofluid using Cattaneo-Christov theory and activation energy in an out spreading solar module sheet installed on an offshore solar oil field. Renewable energy has an extraordinary ability to substitute itself quicker than it is depleted, especially when sourced from natural sources like the wind and sun. The model described here has significant potential for augmenting the thermal efficiency of solar energy systems, particularly for oil rig solar panel sheets that operate under extreme climatic conditions. The Cattaneo-Christov heat and mass flux model, which allows for precise prediction of thermal and concentration relaxation phenomena, can benefit industrial and offshore energy platforms by improving energy conversion efficiency, sophisticated cooling technologies, and intelligent thermal management systems. The resulting partial differential equations are then converted into ordinary differential equations by using similarity factors. The resultant sets of nonlinear ordinary differential equations have been simulated using the Homotopy analysis approach. The concentration profile rises as the activation energy parameter values increase.

This study examines the chemically reactive magnetohydrodynamic (MHD) flow of a hybrid nanofluid composed of single-wall carbon nanotubes (SWCNTs) and multi-wall carbon nanotubes (MWCNTs) suspended in the base fluid blood, flowing within a stenosed artery. The model incorporates thermal radiation, Joule heating and non-uniform internal heat generation. The similarity transformations alter the governing equations into nonlinear ordinary differential equations, which are then resolved numerically using MATLAB’s Bvp4 solver. Comparison of classical and modified Hamilton–Crosser hybrid thermal conductivity models is made to establish their effect on heat and mass transport. Findings indicate that radiation, Eckert number and internal heat generation increase temperature, whereas an increase in Schmidt and chemical-reaction parameters prevents concentration. The modified Hamilton–Crosser model always gives significantly higher values of Nusselt number than the classical model. Such results demonstrate the significance of conductivity model in the application in magnetic nanoparticle therapies, biomedical heat-management and targeted drug delivery.

In this work a rotating trihybrid nanofluid motion is observed within two plates positioned parallel at varying altitude. The lower plate is movable, and the upper plate is fixed. The trihybrid nanofluid is composed of copper, Titanium dioxide with aluminum oxide nanoparticles with water (base fluid). The fluid is moving in Darcy–Forchheimer medium under the effect of an external magnetic field. The Cattaneo–Christove mass and heat flux model is applied to investigate mass and heat transmissions rates. The Cattaneo–Christove model is the extension of classical Fourier and Fick laws. The effects of quadratic thermal radiation are also discussed in the modeling. The PDEs are converted to ODEs and numerically solved by the shooting (ND solve) method. The results have been sketched graphically and in tabular form for better understanding and analysis. The results reveal that the primary and secondary velocity distributions decrease by enhancing Forchheimer number. It has been noted that the temperature profile increases for heat relaxation parameter and temperature ratio parameter. By improving the values of mass relaxation parameter, concentration profile decreases. By enhancing the values of Reynolds number the Nusselt number decreases. By enhancing the values of Schmidt number and chemical reaction parameter the Sherwood number declines. The findings show that when the magnetic parameter is increased from 0.1 to 0.3, the Lorentz force rises noticeably and the skin friction number grows by about 25%.

This study aims to examine the elastic deformation of a Diamond-SiO ₂ -Co ₃ O ₄ /NaAlg based ternary hybrid nanofluid across a thin needle with activation energy, using modified and classical Hamilton-Crosser models. Using an appropriate similarity variable, the constitutive PDEs are transmuted into a system of connected ODEs. The efficient bvp4c method is then utilized to mathematically solve the resultant equations. The Diamond-CoO ₄ -SiO ₂ /NaC ₆ H ₇ O ₆ -based THNF using the classical and modified HCM offers important insights into improving thermal performance in sophisticated heat transfer applications. By accounting for the effects of LTNE phenomena, these models aid in the prediction of the effective thermal conductivity of nanofluids, guaranteeing more precise thermal management solutions. The nuclear reactors, solar thermal collectors, electronic device thermal management, and high-performance cooling systems are just a few of the technical fields where the results can be used because effective heat dissipation is essential. For both modified and classical HCM, the liquid phase thermal distribution and liquid and solid rate of heat transfer upsurge although the solid phase thermal distributions decline as the interphase heat transfer parameter rises.