
This paper inspects the outcome of viscous dissipation on chemical reactive flow of Maxwell trihybrid nanoliquid with Darcy Forchheimer porous medium and Marangoni convection. The current model has considerable applications in progressive chemical and thermal engineering systems that demand improved heat and mass transfer. It has numerous applications, including electronic cooling devices, heat exchangers, chemical reactors, hydrometallurgical leaching systems, mineral slurry transport, and metallurgical activities. The addition of viscous dissipation and Joule heating makes the model applicable to electrically conducting fluids and high-temperature industrial processes such as electrowinning and smelting, while the Maxwell trihybrid nanoliquid increases thermal efficiency. Furthermore, the artificial neural network (ANN) structure allows for rapid prediction and enhancement of flow and heat transfer properties, making the model valuable for the design and control of modern energy and manufacturing systems. To train, test, and validate the model for precise flow behavior and thermal characteristic prediction, a reference dataset is created.The results demonstrate that the LMB-ANN technique provides fast convergence, high accuracy, and robust performance, making it a reliable and effective tool for optimizing complex industrial convection systems, including hydrometallurgical reactors and mineral slurry transport operations. The concentration profile for both trihybrid and hybrid nanofluids decreases as the chemical reaction parameter values increase. Clinical trial Number: Not applicable.
The conventional wastewater treatment is energy intensive, chemical-based and cannot efficiently eliminate specific contaminants from the waste water, leading to the growing popularity of the biologically-induced processes of aeration and degradation; yet, the bioconvection models proposed so far assume that the host fluid is Newtonian and that there is only one type of microorganism involved, although research indicates that activated sludge shows non-Newtonian behavior and that gyrotactic and oxytactic microorganisms usually exist simultaneously within aerobic reactors—an aspect taken care of by the current model using Reiner–Rivlin non-Newtonian hybrid nanofluid flow near a spherical granule. A model is developed considering variable viscosity of the fluid and buoyancy effects due to nanoparticles, microorganisms. Heat and mass transfer are coupled in the model to predict convective flow applicable for advanced wastewater treatments. Using similarity transformation technique, the non-linear partial differential equations were transformed into a set of ordinary differential equations using a group theory approach. Numerical solutions of the ODEs were obtained and tested for convergence to ensure validity of solutions. Parametric studies have been performed for various combinations of non-dimensional numbers such as Sc, Gr, Re, Le, Pr, and Ra. The local Nusselt number (Nu), skin friction coefficient, and Sherwood number are calculated as the output parameters. The aim of the present investigation is to mathematically determine the impact of non-Newtonian fluid flow behavior, double microbial swimming ability, and mixed nanoparticle suspension on the flow field adjacent to a spherical bio-carrier. It is noted that increasing values of Schmidt and Lewis numbers reduce the concentration boundary layer thickness, whereas increasing Grashof and Rayleigh numbers increase the buoyancy effect on velocity and heat transfer; increasing Reynolds and Prandtl numbers reduce the boundary layers and increase thermal gradients and local Nusselt number. What makes the present investigation novel is the modeling of both gyrotaxis and oxytaxis of microorganisms in the Reiner–Rivlin hybrid nanofluids (Fe3O4–Cu–TiO2). To verify stability and asymptotic accuracy of the computed solutions, step size variation experiments were conducted at η = 0.5 for h = 0.1,0.05, and 0.025 against the reference solution computed for h_ref = 0.001 . This study contributes theoretically to the optimization of wastewater treatments based on biological approaches.
In the present work, a novel magnetically recoverable heterogeneous nanocatalyst, designated as M-Clay-APTES-AU-Schiff base@Cu, was prepared through a four-step post-synthetic modification of Cloisite 30B nanoclay. The synthesis commenced with co-precipitation of Fe₃O₄ on the clay surface to impart magnetic recoverability, followed by covalent grafting of 3-aminopropyltriethoxysilane (APTES). Imine-condensation of the surface amine with terephthalaldehyde and 6-aminouracil (AU), in a one-pot reaction, installed a bifunctional Schiff base ligand bearing pendant uracil N, O-donor sites, onto which Cu species (introduced as Cu(II) acetate) were subsequently incorporated; the oxidation state of the surface copper was not independently confirmed. The composition, structure, thermal behavior, surface area, and magnetic response of the resulting material were characterized by FT-IR, XRD, TGA, FE-SEM/EDS, BET, VSM, CHN, and ICP-OES analyses. The catalyst was evaluated in the one-pot synthesis of 2-amino-4H-pyran derivatives (via three-component condensation of aldehydes, malononitrile, and dimedone) and of benzimidazole and benzoxazole derivatives (via condensation of aromatic aldehydes with o-phenylenediamine or 2-aminophenol, respectively). Under optimized conditions in refluxing ethanol, 2-amino-4H-pyrans were obtained in 89–98
Abstract To improve heat and mass transfer efficiency, nanofluid-based thermal engineering needs efficient nanoparticle control mechanisms. Brownian motion and thermophoresis significantly affect heat and mass transfer characteristics and nanoparticle movement. Inspired by these applications, the current work examines the flow and transfer characteristics of a Casson nanofluid moving via a circular porous slider with an applied magnetic field, Brownian motion, thermophoresis and active/passive nanoparticle control. The present research compares active and passive nanoparticle control techniques and investigates the coupled interaction of these mechanisms within a non-Newtonian Casson fluid. The governing nonlinear equations are transformed using appropriate similarity transformations into a system of ordinary differential equations, which are then numerically solved using the Runge-Kutta-Fehlberg fourth-fifth order (RKF-45) technique. Additionally, the transfer properties are analyzed using response surface methodology (RSM) and artificial neural networks (ANNs). The ANN forecasts exhibit outstanding agreement with the numerical data, while the RSM model achieves prediction accuracies of 99.48 and 99.88% for the active and passive cases, respectively. Higher temperature and concentration profiles are produced by active nanoparticle control than by passive control. The results are pertinent to enhanced cooling technologies, biomedical transfer systems, porous lubrication devices and thermal energy management. They also offer new perspectives on nanoparticle transfer processes. Clinical trial: Not applicable.
The proposed model has potential uses in advanced thermal and mass transmission systems that need nanoparticle deposition and improved heat transfer. Its applications include industrial cooling and heating systems, polymer and material processing, chemical reactors, solar thermal devices, electronic cooling, and energy storage systems. The combination of thermophoretic particle deposition, activation energy, surface-tension gradients, viscous dissipation, and heat generation creates a realistic framework for assessing and managing heat and mass transport in high-temperature engineering processes. This work uses the expanded Yamada-Ota model to examine thermophoresis particle deposition in Stagnation point flow of trihybrid nanofluid with non-linear heat source and activation energy in relation to Magneto-Marangoni convective heat transmission. Applying the considerable similarity transformation results in the creation of the nonlinear dimensionless system as ordinary differential equations (ODEs). As the Marangoni convection parameter values increase, solutal and thermal profiles decline. The concentration profile becomes more prominent as the activation energy parameter values increase. Clinical trial This study is not a clinical trial.