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.
