Comparative Investigation of Water-Based Al2O3 Nanoparticles Through Water-Based CuO Nanoparticles Over an Exponentially Accelerated Radiative Riga Plate Surface via Heat Transport

AI-based prediction of flow dynamics of blood blended with gold and maghemite nanoparticles in an electromagnetic microchannel under abruptly changes in pressure gradient

In cardiovascular research, electromagnetic fields (EMFs) induced by Riga plates are applied to study and potentially manipulate blood flow dynamics, offering insights for therapies against arterial plaque deposition and for understanding varied blood flow behaviors. This research focuses on predicting the flow patterns of blood infused with gold and maghemite nanoparticles (gold-maghemite/blood) inside an EM microchannel under these electromagnetic influences and abruptly change in pressure gradient. The study models these flows by considering radiation heat emission and Darcy drag forces within porous media. Mathematical representation involves time-variant partial differential equations, resolved through Laplace transform (LT) to yield compact-form expressions for the model variables. The outcomes, including shear stress (SS) and rate of heat transfer (RHT) across the microchannel, are analyzed and displayed graphically, highlighting the effects of modified Hartmann number and electrode width on these parameters. Hybrid nano-blood (HNB) and nano-blood (NB) exhibit distinct thermal characteristics, with HNB transferring more heat within the blood flow. These study implements a cutting-edge AI-powered approach for high-fidelity evaluation of critical flow parameters, achieving unprecedented prediction accuracy. Validation results confirm the algorithm's excellence, with SS predictions reaching 99.552% (testing) and 97.019% (cross-validation) accuracy, while RHT predictions show 100% testing accuracy and 97.987% cross-validation reliability. This convergence of nanotechnology with advanced machine learning paves the way for transformative clinical applications that could redefine standards of care in surgical oncology, interventional cardiology, and therapeutic radiology. This model underpins potential applications such as controlled drug release and magnetic fluid hyperthermia, enhancing procedures like cardiopulmonary bypass, vascular surgery, and diagnostic imaging.

AI-based forecasting of dynamic behaviors of Ag and ZnO nanoparticles-enhanced milk in an electromagnetic channel with exponential heating: dairy decontamination

Electromagnetic plates can be used to heat milk and other dairy products rapidly and uniformly. The use of electromagnetic fields enables precise thermal control, which is crucial for safe pasteurization while retaining the nutritional and sensory qualities of milk. This study investigates the dynamics of Ag-ZnO/milk under electromagnetic fields generated by Riga plates with exponentially decaying wall temperatures. The model includes radiation heat emission, heat sinks, and Darcy drag forces due to the porous medium. The flow is mathematically depicted through unsteady partial differential equations solved using the Laplace transform approach. Results include tabulated and graphical with an exhaustive analysis of flow entities against model parameters. Findings highlight increased milk velocity with a boosted modified Hartmann number and declined velocity with wider electrodes. An AI-powered computing approach enhances the accuracy in envisaging flow metrics, achieving 100% accuracy in training, testing, and validation phases. This research not only advances dairy processing technologies but also paves the way for innovations in food safety, nano-enhanced dairy production, and sustainable manufacturing practices.

Neuro-computational simulation of blood flow loaded with gold and maghemite nanoparticles inside an electromagnetic microchannel under rapid and unexpected change in pressure gradient

In cardiovascular research, electromagnetic fields generated by Riga plates are utilized to study or manipulate blood flow dynamics, which is particularly crucial in developing treatments for conditions such as arterial plaque deposition and understanding blood behavior under varied flow conditions. This research predicts the flow patterns of blood enhanced with gold and maghemite nanoparticles (gold-maghemite/blood) in an electromagnetic microchannel influenced by Riga plates with a temperature gradient that decays exponentially, under sudden changes in pressure gradient. The flow modeling includes key physical influences like radiation heat emission and Darcy drag forces in porous media, with the flow mathematically represented through unsteady partial differential equations solved using the Laplace transform (LT) method. Results, including shear stress (SS) and rate of heat transfer (RHT), are graphically detailed, demonstrating changes in blood velocity profile with modifications in the Hartmann number and the width of electrodes, and differences in temperature and RHT between hybrid nano-blood (HNB) and nano-blood (NB). The key results indicate an increase in blood velocity distribution with higher modified Hartmann number, and a decrease with wider electrodes. Temperature is elevated in both hybrid nano-blood (HNB) and nano-blood (NB). Notably, HNB with gold and maghemite enhances heat transmission in the flow. Furthermore, an artificial intelligence-driven methodology employing an artificial neural network (ANN) has been incorporated to facilitate rapid and precise evaluations of SS and RHT, demonstrating remarkable predictive accuracy. The proposed algorithm exhibits outstanding accuracy, achieving 99.998% on the testing dataset and 96.843% during cross-validation for predicting SS, and 100% on the testing dataset, and 95.008% during cross-validation for predicting RHT. The implementation of nanotechnology with artificial intelligence promises new tools for doctors and surgeons, potentially transforming patient care in fields such as oncology, cardiology, and radiology. This model also facilitates the generation of precise electromagnetic fields to guide drug-loaded magnetic nanoparticles for applications in targeted drug delivery, hyperthermia treatment, MRI contrast enhancement, blood flow monitoring, cancer treatment, and controlled drug release.

Novel numerical and artificial neural computing with experimental validation towards unsteady micropolar nanofluid flow across a Riga plate

Fluid flow across a Riga Plate is a specialized phenomenon studied in boundary layer flow and magnetohydrodynamic (MHD) applications. The Riga Plate is a magnetized surface used to manipulate boundary layer characteristics and control fluid flow properties. Understanding the behavior of fluid flow over a Riga Plate is critical in many applications, including aerodynamics, industrial, and heat transfer operations. The unsteady Micropolar nanofluid (UMNF) flow across a vertically oriented, nonlinearly stretchable Riga sheet is examined in the present study. The effects of variable thermal conductivity, thermophoretic force, and Brownian diffusion on flow and heat transfer are analyzed. The fluid flow has been expressed in the form of a nonlinear system of PDEs (partial differential equations), which are reduced into the non-dimensional form of ordinary differential (ODEs) by employing the similarity transformation approach. The dataset for training the ANNs using the Levenberg-Marquardt backpropagation (LMBP) technique is generated using numerical simulation methods. The influence of physical constraints on the dimensionless temperature, concentration, microrotation, and velocity distributions are graphically displayed and discussed. Numerical results for skin friction, Sherwood, and Nusselt numbers are presented in tabular form. The numerical outcomes are compared to both published numerical and experimental results for validity purposes. It can be noticed that the flow rate is enhanced with the rising influence of the Hartmann number, buoyancy force, and velocity slip parameter. The UMNF flow model is validated, tested, and trained with an average numerical error of 10-9, ensuring high accuracy in energy, velocity, microorganism motility, and concentration predictions.

An influence of temperature jump and Navier's slip-on hybrid nano fluid flow over a permeable stretching/shrinking sheet with heat transfer and inclined MHD

This research article, explores the influence of an inclined magnetic field on the fluid flow over a permeable stretching/shrinking surface with heat transfer. The study use water as a conventional base fluid, with graphene oxide (GO) and Aluminum oxide (Al2O3) nanoparticles submerged to create a nanofluid, the system of governing nonlinear partial differential equations converted into ordinary differential equations via suitable similarity conversions. This allow for the unique solution for stretching sheet/shrinking sheets to be obtained, along with the corresponding temperature solution in terms of the hypergeometric function, several parameters are included in the investigation and their contribution is graphically explained to examine physical characteristics such as radiation, inclined magnetic field, solution domain, volume fraction parameter, and temperature jump. Increasing the volume fraction and thermal radiation increases the thermal boundary layer, increasing the magnetic field parameter and inverse Darcy number increases the temperature and decays the velocity profile. The present work has many useful applications in engineering, biological and physical sciences, as well as in cleaning engine lubricants and thrust-bearing technologies.

Numerical Solution of Radiative and Dissipative Flow on Non-Newtonian Casson Fluid Model via Infinite Vertical Plate with Thermo-Diffusion and Diffusion-Thermo Effects

This research presents mathematically developed model to examine non-Newtonian Casson fluid flow in the existence of radiation, Ohmic dissipation, thermo-diffusion and diffusion-thermo over infinite vertical plate domain. Using similarity transformations, the governing partial derivative related to fluid model is transmuted to ordinary derivative equations and then solved computationally by adopting Runge-Kutta method via shooting quadrature in mathematical software MAPLE. The impacts of various considered effects were assed and solutions for momentum velocity profiles, heat transfer energy and mass transfer concentration profiles are investigated via graphical presentation. The outcomes show that radiation and magnetic field increased heat distribution and improvement in yield stress through an enhancement in Casson term reduces the flow speed. Presence of Cross diffusion terms has remarkable impact on thermal and solutal profiles. Further, numerical significances of engineering quantities such as skin friction, Nusselt number and Sherwood number are provided in tabular form. Finally, to justify the outcomes of this study, a resemblance is taken with earlier published works and found there is good correlation.

A Comprehensive Approach to Derivatization: Elemental Composition, Biochemical, and In Silico Studies of Metformin Derivatives Containing Copper and Zinc Complexes

The current study was designed to synthesize, characterize, and screen the molecular and biological activities of different metformin derivatives that possess potent antidiabetic potential with minimal side-effects. Metformin-based derivatives containing the metal complexes Cu II (MCu1-MCu9) and Zn II (MZn1-MZn9) were generated using aromatic aldehydes and ketones in a template process. The novel metal complexes were characterized through elemental analysis, physical state, melting point, physical appearance, Fourier-transform infrared (FTIR) spectroscopy, UV/visible (UV/Vis) spectroscopy, ¹H nuclear magnetic resonance (NMR) spectroscopy, and ¹³C-NMR spectroscopy. Screening for inhibitory activity against the enzymes α-amylase and α-glucosidase, and molecular simulations performed in Schrödinger were used to assess the synthesized derivatives' biological potential. Met1, Met2, Met3, and Met8 all displayed activities that were on par with the reference in an enzymatic inhibition assay (amylase and glucosidase). The enzyme inhibition assay was corroborated by molecular simulation studies, which also revealed a competitive docking score compared to the gold standard. The Swiss ADME online web server was utilized to compute ADME properties of metformin analogues. Lipinski's rule of five held true across all derivatives, making it possible to determine the percentage of absorption. Metformin derivatives showed significant antidiabetic activities against both targeted enzymes, and the results of this work suggest that these compounds could serve as lead molecules for future study and development.

Nonlinear Radiative Nanofluidic Hydrothermal Unsteady Bidirectional Transport with Thermal/Mass Convection Aspects

The collective effect of thermal and mass convection along with the significance of thermal radiation, heat source/sink, and magneto-nanofluid are considered. A bi-directional stretching device is used to generate the symmetry of the flowing structure. Nonlinear behavior of thermal radiation is considered here. The magnetic field is considered non-uniform and vertically upward. Significances of pedesis motion and Ludwig–Soret are also revealed in an innovative way with heat source/sink effects. The concept of symmetry is used to transmute the transport equations from PDE type to nonlinear ODE type. We solved the transformed setup numerically by adopting Keller-box method criteria with the targeted accuracy rate. Graphical interpretations are explored with code verification. It is important to conclude that friction coefficients decline for incremental values of stretching parameter (0.1≤α≤0.9), magnetic field (0.3≤M≤0.9), and unsteady parameter (0.2≤Λ≤0.9) along with the bidirectional velocity components, and the rate of heat transmission rises with temperature ratio (1.3≤Γ≤1.7) and temperature Biot number (0.3≤BiT≤0.9) amplification. Moreso, the rate of mass transfer is enhanced with growing values of pedesis motion (0.2≤Nb≤0.6), unsteady parameter and concentration Biot number (0.3≤BiC≤0.9) with opposite effect when the Ludwig–Soret parameter (0.3≤Nt≤0.6) is boosted.

Rheology of electromagnetohydrodynamic tangent hyperbolic nanofluid over a stretching riga surface featuring dufour effect and activation energy

The present model deals with the consequence of Dufour, activation energy, and generation of heat on electromagnetohydrodynamic flow of hyperbolic tangent nanofluid via a stretching sheet. This offers a broad significance in several engineering fields. With adequate similarity variables, the regulating governing equations of PDEs are renovated into nonlinear ODEs. The numerical output of the produced ordinary differential equations is conducted with MATLAB bvp4c. The influence of increasing features on temperature, velocity, concentration patterns, drag force coefficient, Sherwood number and Nusselt number is depicted graphically and numerically. Hence, the resultant conclusions are confirmed utilising contrast with earlier output. Interestingly, the activation energy retards the nanofluid's tangential hyperbolic concentration distribution and the rise in temperature of the hyperbolic tangential nanofluid flow is traceable to an increase in the Dufour effect, However, the electromagnetohydrodynamic variable increases the velocity distribution, which influences the Power law index. Conclusively, the rate of heat transfer is inhibited when the thermophoresis parameter, heat source and the Weissenberg number are enhanced.

Efficient Heat Transfer Augmentation in Channels with Semicircle Ribs and Hybrid Al2O3-Cu/Water Nanofluids

Global technological advancements drive daily energy consumption, generating additional carbon-induced climate challenges. Modifying process parameters, optimizing design, and employing high-performance working fluids are among the techniques offered by researchers for improving the thermal efficiency of heating and cooling systems. This study investigates the heat transfer enhancement of hybrid "Al₂O₃-Cu/water" nanofluids flowing in a two-dimensional channel with semicircle ribs. The novelty of this research is in employing semicircle ribs combined with hybrid nanofluids in turbulent flow regimes. A computer modeling approach using a finite volume approach with k-ω shear stress transport turbulence model was used in these simulations. Six cases with varying rib step heights and pitch gaps, with Re numbers ranging from 10,000 to 25,000, were explored for various volume concentrations of hybrid nanofluids Al₂O₃-Cu/water (0.33%, 0.75%, 1%, and 2%). The simulation results showed that the presence of ribs enhanced the heat transfer in the passage. The Nusselt number increased when the solid volume fraction of "Al₂O₃-Cu/water" hybrid nanofluids and the Re number increased. The Nu number reached its maximum value at a 2 percent solid volume fraction for a Reynolds number of 25,000. The local pressure coefficient also improved as the Re number and volume concentration of "Al₂O₃-Cu/water" hybrid nanofluids increased. The creation of recirculation zones after and before each rib was observed in the velocity and temperature contours. A higher number of ribs was also shown to result in a larger number of recirculation zones, increasing the thermal performance.

Fast Solutions for Large Reynold’s Number in a Closed-Loop Thermosyphon with Binary Fluid

In this work, we analyze the asymptotic behavior of the solutions for a thermosyphon model where a binary fluid is considered, a fluid containing a soluble substance, and the Reynold’s number is large. The presented results are a generalization, in some sense, of the results for a fluid with only one component provided in Velázquez 1994 and RodrÍguez-Bernal and Van Vleck 1998. We characterize the conditions under which a fast time-dependent solution exits and it is attracted towards a fast stationary solution as the Reynold’s number tends to infinity. Numerical experiments were performed in order to illustrate the theoretical results. Using numerical simulations, we found fast time-dependent solutions close enough to the fast stationary one for certain values of the parameters.

MHD Flow of a Hybrid Nano-Fluid in a Triangular Enclosure with Zigzags and an Elliptic Obstacle

The current study uses the multi-physics COMSOL software and the Darcy–Brinkman–Forchheimer model with a porosity of ε = 0.4 to conduct a numerical study on heat transfer by Cu-TiO₂/EG hybrid nano-fluid inside a porous annulus between a zigzagged triangle and different cylinders and under the influence of an inclined magnetic field. The effect of numerous factors is detailed, including Rayleigh number (103 ≤ Ra ≤ 106), Hartmann number (0 ≤ Ha ≤ 100), volume percent of the nano-fluid (0.02 ≤ ϕ ≤ 0.08), and the rotating speed of the cylinder (−4000 ≤ w ≤ 4000). Except for the Hartmann number, which decelerates the flow rate, each of these parameters has a positive impact on the thermal transmission rate.