Plant mediated green nanoparticles (NPs) have grabbed substantial consideration as promising alternates to traditional approaches that minimizes the use of toxic chemicals. The phytochemicals like flavonoids, polyphenolics carbohydrates etc. present in plant extracts contain functional groups like -OH/-C=O that bind with metal ions to facilitate chelation, and finally influence NP size and other morphologies and stability. The review presents an overview of green NPs synthesis and their efficacy to remove toxic contaminants such as organic pollutants, drugs, dyes, heavy metals, and other pathogenic microbes from water. The review delves into plant mediated green NP synthesis from stem, root, flower, leaves extract, structural modifications, their stability, and underlying adsorption or photocatalytic mechanisms for water remediation. The review further discusses key challenges with plant mediated NP synthesis including stability and reproducibility due to NP agglomeration along with toxicity which requires LCA sustainability consideration. The review is compilation of recent advancement and future directions needed to transform lab-scale plant mediated NPs to large scale sustainable water remediation techniques.
This numerical study investigate the heat and mass transfer behavior in among heat generation (Q * >0) and absorption (Q * <0) of unsteady incompressible couple–stress magnetohydrodynamic (MHD) hybrid nanofluid flow through a horizontal squeezed channel, taking into account the combined effects of chemical reaction and activation energy. The SiO 2 + Al 2 O 3 /blood hybrid nanofluid offers excellent heat transfer and biocompatibility, making it highly suitable for biomedical, pharmaceutical, and diagnostic applications with great scope in healthcare advancements. This fluid is a non-toxic, customized drug that improves blood circulation and reduces side effects. Applying similarity transformations to the governing PDEs reduces them to a set of ODEs. Using the fourth-order Runge–Kutta scheme, the shooting method, along with relevant boundary conditions, is employed to solve these equations. The effects of various dimensionless parameters on temperature and concentration distributions are sketched to explain. We conclude that in both heat absorption and generation cases, the concentration distribution decreases for all dimensionless parameters but increases with activation energy. In contrast, temperature distribution follows an opposite trend. The skin friction number ( C f ), Nusselt number ( Nu x ), and Sherwood number ( Sh x ) are investigated numerically. When the magnetic parameter increases from 1 to 3, skin friction rises by 4.96% for both heat generation and absorption cases. The Schmidt number is increased by heat generation (Q * >0) and 12.26% heat absorption (Q * <0) as Sc is increased by 1–1.2. As the couple stress parameter rises from 0.1 to 0.3, skin friction decreases sharply by 33.56% in both cases, whereas the Nusselt number increases by 17.24% heat generation (Q * >0) and 20.77% heat absorption (Q * <0). An increase in the Eckert number of Ec = 0.01–0.03 raises the Nusselt number by 14.32% and 17.17%, respectively. The obtained similarity solutions closely match previously published results.
In this work, the unsteady flow and heat transfer properties of a hybrid nanofluid consisting of Ti O 2 – CoF e 2 O 4 nanoparticles dispersed in water over a rotating disk, that is, stretching radially are investigated. The combined effects of thermal radiation, slip boundary conditions, an applied magnetic field, and different nanoparticle shape are highlighted. This issue is crucial for enhancing heat transfer in complex thermal management systems, where conventional fluids usually perform poorly. Unlike previous studies, this work investigates in a novel manner the effects of different nanoparticle shapes (sphere, column, and lamina) at constant volume fraction under realistic operating conditions on flow resistance and thermal performance. The governing Navier–Stokes and energy equations were numerically solved using MATLAB’s BVP4C solver and the Von Kármán similarity transformations. The results show that increasing the radiation parameter improves the temperature profile and makes cooling more efficient, but increasing the Prandtl number makes it less efficient. The Lorentz force causes higher magnetic fields to boost fluid temperatures and lower axial, tangential, and radial velocities. As the slip parameter increases, the fluid speeds decrease and the temperature of the wall increases. These findings demonstrate that spinning disc systems can flow and transfer heat more effectively by selecting the appropriate boundary slip and nanoparticle shape. Effective cooling systems and heat exchangers depend on this. The fluid rotating in front of the disk rotates more slowly when the unsteadiness parameter α ^ has a lower value.
This work explores Eyring-Powell hybrid (TiO2+Au)/blood nanofluid with past an inclined stretching cylinder. With the inclusion of gyrotactic microorganisms, chemical reaction, activation energy and thermal radiation. The results of this study can apply in diverse fields such as biomedical systems, thermal management and environmental applications. In this study, the similarity transformation is used to change the partial equations into ordinary differential equations. The transformed non-linear ordinary differential equations are solved by fifth order Runge-Kutta Fehlberg method with shooting technique. Furthermore, entropy generation is considered for this model, it evaluates energy losses and enhance the overall efficiency and performance of the system. In this study artificial neural network is used to confirms the reliability and accuracy of the obtained data. The Levenberg-Marquardt Backpropagation algorithm was used for training neural networks and Tan-Sigmoid function is considered for hidden layer, while the output layer uses a Purelin function. Notably, increasing suction parameter decrease the velocity profile and increment of activation energy parameter decrease the concentration profile. Increasing the thermal radiation increase the Bejan number. Moreover, thermal radiation increased the Nusselt number 57% from 0.2 to 2.0. The ANN model achieves a best validation performance for Microorganism density is 9.7118e-0.6 at 102 epoch. In the regression analysis for skin friction coefficient yields an R -value approached to unity.
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 this study, we examined Maxwell slippery flow phenomena as a result of a stretchable sheet moving through a porous medium, considering ion slips and Hall implications, along with Brownian motion and radiation implications. Using the proper similarity transformation, the dimensionless governing equations are reduced to a system of ordinary differential equations, which are then tackled through an RSM framework supported by MATLAB's built-in bvp4c solver. The objective of using graphical representations to examine the effects of the derived physical parameters on the distributions of nanoparticle temperature, velocity, and concentration has been to provide a physical explanation for each parameter. Comparing the results to those from older studies that used similar assumptions showed that they were reliable and behaved as predicted. The Hall effect made the flow less stable, but ion-slip made it more stable, because larger ions react to magnetic forces more slowly than electrons. In parametric calculations, the intervals 0.5 <= Ha <= 2.0, 0.1 <= Nb, Nt <= 0.6, 1 <= Pr 7, 1 <= Ln 5, and 0.1 <= Sr <= 0.6 are considered. In the parameter space that was considered, the findings show that surface shear stress increases by 18%-22% as the Hartmann number increases, and that the Nusselt number decreases by around 20%-25% when the Brownian motion and thermophoresis parameters decrease. The Sherwood number may vary by as much as 15%-20%, and the nano-Lewis and Soret numbers have a major impact on mass transfer. Advanced engineering correlations based on regression have been created, providing concise expressions for skin friction, heat, and mass transfer rates, and boasting a high prediction accuracy (R-2 > 0:95).
This study investigates the mechanisms of entropy generation associated with energy and momentum transport in a magnetic nanofluid flowing over a horizontally stretching cylinder embedded in a porous medium. The formulated mathematical problem is reduced into system of non-dimensional equations by the implementation of suitable similarity transformations. The current non-dimensional model is subsequently computed numerically through the MATLAB-based boundary value problem solver, bvp4c. The analysis presents detailed graphical results to illustrate the effects of various physical parameters on the profiles of velocity, temperature, concentration, entropy generation, and Bejan number. Results demonstrate that the stretching cylinder exhibits a thicker boundary layer and higher entropy generation compared to a flat surface. Key thermodynamic quantities include skin-friction factor, Nusselt and Sherwood numbers are communicated with the help of tables to quantify surface shear, heat and mass transfer. Findings of this study are especially valuable for advancing high-performance cooling platforms, including solar collectors, electronic thermal management, and industrial heat-exchange units. The ability to precisely control heat and mass transfer in such systems is not just useful but fundamentally decisive for achieving reliable and energy-efficient operation. This work offers comprehensive insights into the thermodynamic irreversibility and transport behavior in magneto-porous nanofluid systems.
The fundamental mission of this study is to formulate and solve the mathematical model of the stagnation point flow of a hybrid nanofluid with the insertion of second-order velocity slips, magnetohydrodynamic (MHD), and radiation effects over a shrinking sheet, which are critical for enhancing thermal performance in industrial cooling and heat treatment processes. The model is transcribed into non-dimensional formulations using similarity variables and is solved numerically using the bvp4c solver in MATLAB. Dual solutions are executed, and the stable solution is validated via the stability analysis. In certain conditions, the comparison of current and prior findings demonstrates good agreement with nearly 0% relative error. The findings reported that the critical point is extended, and the bifurcation of the boundary layer is prevented by the boost in the magnitude of second-order velocity slips and copper volume fraction. The efficiency of heat transfer improves as the radiation effect and the copper volume fraction increase, particularly when the sheet is shrunk. The boost of copper volume fraction is also simulated to lessen the temperature and the thermal boundary layer thickness. Thus, the present model in this study has proven that the utilization of a hybrid nanofluid could increase the thermal performance of a system, and it could be used as a coolant for a heat treatment process.
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 x E-8 to 1 . 77 x 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 study investigates the magnetohydrodynamic (MHD) flow, heat, and mass transfer of a water-based ferro-nanofluid (Fe 3 O 4 ) through a channel bounded by converging-diverging stretching Riga plates. The Riga plate configuration generates a wall-parallel Lorentz force, offering a unique mechanism for active flow control with reduced energy dissipation compared to traditional MHD systems. The Buongiorno model is employed to incorporate the effects of thermophoresis and Brownian motion, alongside viscous dissipation and thermal radiation. The governing partial differential equations are transformed into a system of nonlinear ordinary differential equations using similarity transformations and solved numerically via the Keller-Box method. The analysis reveals how key dimensionless parameters such as the wall slope ( m ), modified Hartmann number ( Q ), Reynolds number ( Re ), Eckert number ( Ec ), Brownian motion ( Nb ), and thermophoresis ( Nt ) parameters govern the velocity, temperature, and nanoparticle concentration profiles. The study highlights significant implications for enhancing thermal performance and particle distribution control in advanced engineering systems. Key engineering quantities like the skin friction coefficient, Nusselt number, and Sherwood number are also analyzed. Results indicate that the electromagnetic forcing from the Riga plate can enhance flow velocity contrary to traditional MHD damping. Temperature rises with increasing Ec , Nb , and Nt but decreases with stronger radiation ( Rd ). The concentration boundary layer thins with higher Nb and Nt . The novelty of this work lies in the comprehensive analysis of a ferro-nanofluid within an electromagnetically actuated convergent-divergent geometry, a configuration scarcely addressed in prior literature. Key applications include the design of efficient electronic cooling systems, targeted drug delivery platforms, microfluidic pumps, and advanced materials processing equipment where precise thermal and species management is critical.
Prandtl nanofluids are increasingly vital in microfluidic devices and electronic cooling systems due to their enhanced heat transfer characteristics, yet their behavior in porous microchannels with internal heat generation remains unexplored. This study numerically investigates free convection heat and mass transfer of a non-Newtonian Prandtl nanofluid in a vertical porous microchannel, incorporating Brownian motion, thermophoresis, wall suction, and nonlinear internal heat generation. The governing equations are solved using the adaptive collocation-based bvp4c algorithm in MATLAB. Grid independence is achieved with a relative error of O (10-10), yielding a skin friction coefficient of 0.244343857. Results show that increasing the magnetic field parameter suppresses velocity due to Lorentz damping while thickening the thermal boundary layer. The Nusselt number increases significantly with Prandtl number (from 17.71 at Pr = 5 to 34.84 at Pr = 12) and suction velocity (from 11.26 at V0 = 0.2 to 20.13 at V0 = 0.6). These quantitative findings provide benchmarks for optimizing microchannel thermal management systems.
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.
An investigation on the convective heat transportation features of a magnetised Williamson nanofluid over a radiative permeable sheet is presented in this article. The interaction of an irregular heat source/sink along with thermal radiation brings a novel approach to the flow phenomena. The nanofluid, comprising of two-phase model based upon the impact of Brownian and thermophoresis boosts up the thermal combined with solutal profile significantly under the influence of an applied magnetised field. The standard modelled partial differential equations are renovated into a couple of nonlinear ordinary differential equations by implementing suitable similarity transformations. Further, a numerical solution employing the Runge-Kutta fourth-order with an integrating shooting technique is adopted to resolve the resulting system of equations. The influence of pertinent parameters, including the magnetic field strength, thermal radiation parameter, and irregular heat source/sink parameters, is systematically analysed. The enhancement of heat transfer in nanofluid-based systems, influenced by magnetic fields and non-uniform heat sources or sinks, plays a critical role in various industrial and biological applications. This is particularly significant in designing and optimising of heat exchangers, electronic cooling systems, and energy-efficient processes, as well as in drug delivery systems. In an outstanding outcome it is revealed that, the dominance of elastic forces over the viscous forces for the increasing Williamson parameter significantly retards the velocity as well as temperature distribution.
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 work presents a detailed numerical investigation of heat and mass transfer in a square cavity filled with a fluid containing nano-encapsulated phase change materials (NEPCMs), under the combined effects of thermal radiation and an exothermic chemical reaction. The study models the complex interplay between fluid flow, phase change behaviour, radiative heat transfers and reactive species transport. A finite element approach is employed to solve the governing equations, incorporating the enthalpy-porosity method to capture the phase transition dynamics. Key parameters such as the radiation parameter, nanoparticle volume fraction, thermal relaxation, fusion parameter and an exothermic chemical reaction rate are varied to assess their influence on thermal and concentration fields. Additionally, Nusselt numbers at the hot and cold walls are computed and presented in tabular format for analysis. The results reveal that the inclusion of NEPCMs enhances thermal energy storage and transport, while radiation and chemical reactions significantly alter the flow and temperature distributions. This investigation provides valuable insights into the design of advanced thermal management systems involving reactive and radiative transport in PCM-based applications.
This study investigates the unsteady electroosmotic pumping flow of a Carreau-based ternary hybrid nanofluid (Al2O3-MoS2-Cu/blood) under the combined influence of an inclined magnetic field, thermal radiation, and cilia-modulated slip conditions. The system models a biologically inspired microchannel actuated by an externally applied axial electric field. The governing nonlinear partial differential equations are solved using the Chebyshev Collocation Spectral Method (CCSM), implemented in MATHEMATICA, offering superior spectral accuracy and computational efficiency. Numerical results reveal that the THNF achieves up to 11.3% higher thermal conductivity and 9.7% faster heat transport rate compared to hybrid nanofluid counterparts, and up to 18.6% improvement over mono-nanofluids. The electroosmotic parameter is shown to enhance temperature and axial velocity significantly, with a 12% rise in core temperature and a 15% increase in flow rate as the parameter increases from 0.5 to 2.0. Furthermore, the synergistic interaction of Ohmic heating and inclined magnetic field strengthens the thermal field, leading to a 19% boost in surface heat flux.
Improving heat transmission is a modern challenge that affects a wide range of industries, including electronics, heat exchangers, biochemical reactors, and others. Nanofluids (NFs) hold considerable potential as a valuable tool in an effort for increased energy transfer efficiency. Therefore, the objective of this work is to learn the way to use Nanofluids (NFs) to improve heat transmission. This study examines the flow and heat transfer characteristics of Williamson hybrid nonfluids (HNF) containing graphene oxide (GO) and copper (Cu) nanoparticles. The HNF is applied across a thin needle with an applied magnetic field. Viscous dissipation effects and dual slip boundary conditions are imposed to account for energy dissipation and slip effects. Applying similarity transformations, the governing partial differential equations are converted into non-linear ordinary differential equations, numerically solved using the Bvp4c technique in MATLAB. The study identifies that increments in factors such as the magnetic factor M, needle size a, and velocity slip factor beta, lead to a reduction in the velocity profile. The variations in factors such as a and thermal slip factor gamma correspond to an increase in the temperature profile. A 200% increase in M results in approximately a 25% reduction in velocity, whereas the temperature increases by nearly 18% for a comparable rise in the Eckert number Ec. The hybrid nanofluid (Cu-GO/H2_22O) shows enhanced thermal transport compared to its mono-nanofluid counterpart. Skin friction increases with M and We, while the Nusselt number decreases with larger gamma. The investigation focuses on potential applications such as polymer ejection for fiber technology and blood flow dynamics. These results highlight the strong coupling between magnetic effects, non-Newtonian rheology, and dual-slip mechanisms, offering insights for applications involving microscale controlled cooling and precision fluid transport. Graphical and tabular results are presented and discussed, providing a visual and quantitative analysis of the observed trends.
This article investigates the combined effects of magnetohydrodynamics (MHD), slip velocity, surface roughness, and non-Newtonian fluid behavior on the hydrodynamic lubrication performance of secant curved circular plate bearings. The lubricant is modelled using Stokes micro-continuum theory, and both radial and azimuthal roughness patterns are considered. A modified Reynolds-type equation is derived and solved to obtain expressions for pressure distribution, load-carrying capacity, and squeeze time. The results reveal that the presence of a transverse magnetic field significantly enhances pressure generation and load capacity. Quantitatively, the load-carrying capacity increases with increasing Hartmann number and slip parameter, while it decreases with increasing surface roughness amplitude. Bearings with azimuthal roughness patterns consistently exhibit higher pressure and load capacity compared to those with radial roughness. Furthermore, decreasing the curvature parameter leads to a substantial increase in load capacity, indicating improved bearing performance for lower curvature values. The combined influence of MHD effects and slip velocity yields superior squeeze time characteristics, demonstrating notable improvements over the no-slip and non-magnetic cases. These findings highlight the critical role of surface texture, magnetic field strength, and slip conditions in optimizing the performance of fluid-based hydrodynamic lubrication systems.
Accurately modeling transport phenomena in melted nanofluids is a pivotal challenge for advancing technologies like high-density electronic cooling due to the strong coupling between phase change, nanoparticle dynamics, and external fields. This study introduces a novel hybrid framework that synergistically combines spectral collocation methods with multiple linear regression analysis. This framework is applied to the specific case of a magnetized, radiative ternary hybrid nanofluid past a shrinking cylinder. Current results reveal that increases in nanoparticle volume fractions escalates angular velocity while diminishing linear velocity and temperature. The micropolar factor reduces the magnitude of the Nusselt number. Enhancing melting at the cylindrical surface inhibits heat transmission and drag force. Regression analysis further identifies shrinkage and radiation as the primary controllers of thermal efficiency, while the magnetic parameter exerts dominance over drag force in this melting regime. This framework provides a powerful diagnostic tool for designing complex thermal systems where multiple physics interact.
