Investigation of the motion of magnetic nanoparticles in microfluidics with a micro domain model

Abstract

In this paper the magnetic nanoparticle (MNP) dynamics in a microfluidic device is investigated in the presence of an external magnetic field. The nanoparticles are used for enzyme-substrate reaction measurements, where the enzyme is immobilized to the surface of the nanoparticles. During the measurements the microreactors, called microchambers are filled up with the MNPs where the distribution of the nanoparticles significantly influences the results of the further reaction measurements. In this paper the procedure of the nanoparticle aggregation is investigated numerically in the microchamber in a micro domain simulation space. First the acting forces on the MNPs are examined from the different phenomena. An in-house numerical model is presented where the dynamics of several MNPs are simulated in the micro-size domain. This model is also embedded in the open source CFD software OpenFOAM. The theoretical calculations and the simulations show that the particle-particle interaction due to magnetization plays an important role during the aggregation procedure. The particles in the magnetic field cluster over the time into chains, which phenomenon is in good agreement with the literature. A theoretical model of the chain dynamics is also established, which is compared to the simulation results. The presented micro domain model was later used to improve an Eulerian-Eulerian based two-phase CFD model and solver, which is able to model the complete MNP aggregation procedure in the magnetic field in macroscopic domains.

Aggregation Volume Estimator–Based Offline Programming Guidance of Magnetic Nanoparticles in the Realistic Rat‐Brain Vasculature Model

“…In the simulation, the minimum and maximum volumes are set as the boundaries of the aggregated particle volume (Figure S7, Supporting Information), enabling the aggregated magnetic particles to be of inconstant volume due to the randomness of aggregation. [ 28 ]…”

“…In the simulation, the minimum and maximum volumes are set as the boundaries of the aggregated particle volume (Figure S7, Supporting Information), enabling the aggregated magnetic particles to be of inconstant volume due to the randomness of aggregation. [28] MNP guidance is affected by viscosity and flow velocity (Figure 4a). In default mode, 19.34% of MNPs reached the ACA and 80.67% reached the ACA2.…”

“…In realistic situations, a single‐layer magnetic chain can aggregate with another MNP or single‐layer magnetic chain in the radial direction, [ 28 ] thereby forming a multilayer magnetic chain. To evaluate SMMC volume size, we determined the radial aggregation area ( A radial ) in vitro.…”

An in silico model of the capturing of magnetic nanoparticles in tumour spheroids in the presence of flow

“…Additionally, a cylindrical magnet is positioned below the flow chamber and exerts a magnetic force on the nanoparticles. Many publications Haverkort et al (2009), Lunnoo and Puangmali (2015), Sharma et al (2015), Momeni Larimi et al (2016) and Pálovics and Rencz (2022) use particle-based approaches for the nanoparticles, where the forces are computed for each individual particle. However, tumour spheroids are on the scale of a few hundred micrometres, while nanoparticles are several orders of magnitude smaller.…”

“…However, tumour spheroids are on the scale of a few hundred micrometres, while nanoparticles are several orders of magnitude smaller. Investigating the transport of nanoparticles with a particle-based approach at the scale of the tumour spheroid thus involves up to a billion particles-an enormous computational burden (Pálovics and Rencz, 2022). But, as we are not interested in the fate of the individual particles, there exist much more efficient alternatives: we use a continuum approach for the nanoparticles, employing a diffusion-advection equation directly at the macroscale.…”