Research on contamination of groundwater and drinking water is of major importance. Due to the rapid and significant progress in the last decade in nanotechnology and its potential applications to water purification, such as adsorption of heavy metal ion from contaminated water, a wide number of articles have been published. An evaluating frame of the main findings of recent research on heavy metal removal using magnetic nanoparticles, with emphasis on water quality and method applicability, is presented. A large number of articles have been studied with a focus on the synthesis and characterization procedures for bare and modified magnetic nanoparticles as well as on their adsorption capacity and the corresponding desorption process of the methods are presented. The present review analysis shows that the experimental procedures demonstrate high adsorption capacity for pollutants from aquatic solutions. Moreover, reuse of the employed nanoparticles up to five times leads to an efficiency up to 90%. We must mention also that in some rare occasions, nanoparticles have been reused up to 22 times.

Water quality problems are a persistent global issue since population growth has continually stressed hydrological resources. Heavy metals released into the environment from plating plants, mining, and alloy manufacturing pose a significant threat to the public health. A possible solution for water purification from heavy metals is to capture them by using nanoparticles in micromixers. In this method, conventionally heavy metal capture is achieved by effectively mixing two streams, a particle solution and the contaminated water, under the action of external magnetic fields. In the present study, we investigated the effective mixing of iron oxide nanoparticles and water without the use of external magnetic fields. For this reason, the mixing of particles and the contaminated water was studied for various inlet velocity ratios and inflow angles of the two streams using computational fluid dynamics techniques. The Navier-Stokes equations were solved for the water flow, the discrete motion of particles was evaluated by a Lagrangian method, while the flow of substances of the contaminated water was studied by a scalar transport equation. Results showed that as the velocity ratio between the inlet streams increased, the mixing of particles with the contaminated water was increased. Therefore, nanoparticles were more uniformly distributed in the duct and efficiently absorbed the substances of the contaminated water. On the other hand, the angle between two streams was found to play an insignificant role in the mixing process. Consequently, the results from this study could be used in the design of more compact and cost efficient micromixer devices.

A large number of microfluidic applications are based on effective mixing. In the application of water purification, the contaminated water needs to be effectively mixed with a solution that is loaded with nanoparticles. In this work, the Tesla valve was used as a micromixer device in order to evaluate the effect of this type of geometry on the mixing process of two streams. For this reason, several series of simulations were performed in order to achieve an effective mixing of iron oxide nanoparticles and contaminated water in a duct. In the present work, a stream loaded with Fe₃O₄ nanoparticles and a stream with contaminated water were numerically studied for various inlet velocity ratios and initial concentrations between the two streams. The Navier–Stokes equations were solved for the water flow and the discrete motion of particles was evaluated by the Lagrangian method. Results indicate that the Tesla valve can be used as a micromixer since mixing efficiency reached up to 63% for V_p/V_c = 20 under various inlet nanoparticles rates for the geometry of the valve that was used in this study.

A possible solution for water purification from heavy metals is to capture them by using nanoparticles in microfluidic ducts. In this technique, heavy metal capture is achieved by effectively mixing two streams, a nanoparticle solution and the contaminated water. In the present work, particles and water mixing is numerically studied for various inlet velocity ratios and inflow angles of the two streams. The Navier-Stokes equations are solved for the water flow while the discrete motion of particles is evaluated by a Lagrangian method. Results showed that as the velocity ratio between the inlet streams increases, by increasing the particles solution flow, the mixing of particles with the contaminated water is increased. Thus, nanoparticles are more uniformly distributed in the duct. On the other hand, angle increase between the inflow streams ducts is found to be less significant.

A computational method for optimum magnetic navigation of nanoparticles that are coated with anticancer drug inside the human vascular system is presented in this study. For this reason a $3D$ carotid model is employed. The present model use Computational Fluid Dynamics $\left(CFD\right)$ and Discrete Element Method $\left(DEM\right)$ techniques along with Covariance Matrix Adaptation $\left(CMA\right)$ evolution strategy for the evaluation of the optimal values of the gradient magnetic field. Under the influence of the blood flow the model evaluates the effect of different values of the gradient magnetic field in order to minimize the distance of particles from a pre-described desired trajectory. Results indicate that the diameter of particles is a crucial parameter for an effective magnetic navigation. The present numerical model can navigate nanoparticles with diameter above 500 nm with an efficiency of approximately $99\%$. It is found that the velocity of the blood seems to play insignificant role in the navigation process. A reduction of $25\%$ in the inlet velocity leads the particles only $3\%$ closer to the desired trajectory. Finally, the computational method is more efficient as the diameter of the vascular system is minimized because of the weak convective flow. Under a reduction of $50\%$ in the diameter of the carotid artery the computational method navigate the particles approximately $75\%$ closer to the desired trajectory. The present numerical model can be used as a tool for the determination of the parameters that mostly affect the magnetic navigation method.

Heavy metals can contaminate water through both natural processes and anthropogenic activities. Unlike organic contaminants, heavy metals are toxic, not biodegradable, and possess the ability to accumulate in organisms. Effective mixing between contaminated water and nanoparticles is of great importance in various purification applications of microfluidics, especially when heavy metals are involved. In these terms, a series of simulations were performed to succeed in an effective mixing of iron oxide nanoparticles in the duct. The selected geometry for the simulations was the Tesla valve which was used as a micromixer. In the present work, a stream loaded with nanoparticles and a stream with contaminated water are numerically studied for various inlet velocity ratios of the two streams. Better mixing is achieved, compared with relative works, under V_p/V_c = 10, for an inlet rate of the Fe₃O₄ nanoparticles per second equal to 1000.