Cited by 12Characterization and Applications of Magnetic NanoparticlesNanoparticle-Based Drug DeliveryParticle Dynamics in Fluid Flows

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Simulation and experimental validation of magnetic nanoparticle accumulation in a bloodstream mimicking flow system

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Reinelt, Magdalena, Ahlfs, Johannes, Stein, Rene, Alexiou, Christoph, Bänsch, Eberhard, Friedrich, Ralf P., Lyer, Stefan, Neuss-Radu, Maria, Neuß, Nicolas·2023·Journal of Magnetism and Magnetic Materials

Abstract

In this paper, a mathematical model for the dynamics of superparamagnetic iron oxide nanoparticles (SPIONs) in a laminar flow through a pipe under the influence of an external magnetic field of a single electromagnet is derived. The model consists of a convection–diffusion equation coupled with magnetostatic equations. The accumulation of particles along the boundary is modeled with the help of a surface concentration. Based on experimental data describing the retention of lauric acid coated SPIONs in a tubular flow under the influence of a magnetic field, the model is parametrized and finite element simulations are performed. With the exception of one outlier at low SPION concentration and high flowspeed, the simulation results agree very well with the experimental measurements within the bounds of the measurement error.

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Research works printed but not linked: 28

  1. Gupta, 2005, Synthesis and surface engineering of iron oxide nanoparticles for biomedical applications, Biomaterials, 26, 3995, 10.1016/j.biomaterials.2004.10.012 · DOI
  2. Reszka, 1997, Body distribution of free, liposomal and nanoparticle-associated mitoxantrone in B16-melanoma-bearing mice, J. Pharmacol. Exp. Ther., 280, 232, 10.1016/S0022-3565(24)36380-3 · DOI
  3. Unterweger, 2014, Development and characterization of magnetic iron oxide nanoparticles with a cisplatin-bearing polymer coating for targeted drug delivery, Int. J. Nanomedicine, 9, 3659, 10.2147/IJN.S63433 · DOI
  4. Tietze, 2013, Efficient drug-delivery using magnetic nanoparticles - biodistribution and therapeutic effects in tumour bearing rabbits, Nanomed.-Nanotechnol. Biol. Med., 9, 961, 10.1016/j.nano.2013.05.001 · DOI · Paper page
  5. Gitter, 2011, Quantitative targeting maps based on experimental investigations for a branched tube model in magnetic drug targeting, J. Magn. Magn. Mater., 323, 3038, 10.1016/j.jmmm.2011.06.055 · DOI
  6. Furlani, 2006, Analytical model of magnetic nanoparticle transport and capture in the microvasculature, Phys. Rev. E, 73, 10.1103/PhysRevE.73.061919 · DOI
  7. Lindemann, 2021, FEM based simulation of magnetic drug targeting in a multibranched vessel model, Comput. Methods Programs Biomed., 210, 10.1016/j.cmpb.2021.106354 · DOI
  8. Grief, 2005, Mathematical modelling of magnetically targeted drug delivery, J. Magn. Magn. Mater., 293, 455, 10.1016/j.jmmm.2005.02.040 · DOI
  9. Khashan, 2011, CFD simulation of the magnetophoretic separation in a microchannel, J. Magn. Magn. Mater., 323, 2960, 10.1016/j.jmmm.2011.06.001 · DOI
  10. Gitter, 2013, Investigations on a branched tube model in magnetic drug targeting—Systematic measurements and simulation, IEEE Trans. Magn., 49, 343, 10.1109/TMAG.2012.2224324 · DOI
  11. Nacev, 2011, The behaviors of ferromagnetic nano-particles in and around blood vessels under applied magnetic fields, J. Magn. Magn. Mater., 323, 651, 10.1016/j.jmmm.2010.09.008 · DOI
  12. Daddi-Moussa-Ider, 2019, Membrane penetration and trapping of an active particle, J. Chem. Phys., 150, 10.1063/1.5080807 · DOI
  13. Majee, 2020, Modeling and simulation of blood flow with magnetic nanoparticles as carrier for targeted drug delivery in the stenosed artery, Eur. J. Mech. B Fluids, 83, 42, 10.1016/j.euromechflu.2020.04.004 · DOI
  14. Shaw, 2022, Impact of drug carrier shape, size, porosity and blood rheology on magnetic nanoparticle-based drug delivery in a microvessel, Colloids Surf. A, 639, 10.1016/j.colsurfa.2022.128370 · DOI
  15. Kakavand, 2022, Numerical investigation of capture efficiency of carrier particles in a Y-shaped vessel considering particle-particle interaction and non-Newtonian behavior, J. Drug Deliv. Sci. Technol., 67
  16. Himmelsbach, 2018, Mathematical modelling and analysis of nanoparticle gradients induced by magnetic fields, J. Math. Anal. Appl., 461, 1544, 10.1016/j.jmaa.2017.12.026 · DOI
  17. De Las Cuevas, 2008, Low-gradient magnetophoresis through field-induced reversible aggregation, J. Phys. Chem. C, 112, 945, 10.1021/jp0755286 · DOI
  18. Mühlberger, 2020, Loading of primary human T lymphocytes with citrate-coated superparamagnetic iron oxide nanoparticles does not impair their activation after polyclonal stimulation, Cells, 9, 10.3390/cells9020342 · DOI
  19. Dürr, 2013, A high field gradient magnet for magnetic drug targeting, Magnetohydrodynamics, 49, 552, 10.22364/mhd.49.3-4.56 · DOI
  20. Alexiou, 2006, A high field gradient magnet for magnetic drug targeting, IEEE Trans. Appl. Supercond., 16, 1527, 10.1109/TASC.2005.864457 · DOI
  21. Driscoll, 1984, Magnetic targeting of microspheres in blood flow, Microvasc. Res., 27, 353, 10.1016/0026-2862(84)90065-7 · DOI
  22. Vaidman, 1990, Torque and force on a magnetic dipole, Amer. J. Phys., 58, 978, 10.1119/1.16260 · DOI
  23. Yavuz, 2006, Low-field magnetic separation of monodisperse Fe3O4 nanocrystals, Science, 314, 964, 10.1126/science.1131475 · DOI
  24. Wise, 2015, Magnetophoretic velocities of superparamagnetic particles, agglomerates and complexes, J. Magn. Magn. Mater., 384, 328, 10.1016/j.jmmm.2015.02.031 · DOI
  25. Einstein, 1905, Über die von der molekularkinetischen theorie der wärme geforderte bewegung von in ruhenden flüssigkeiten suspendierten teilchen, Ann. Phys., 322, 549, 10.1002/andp.19053220806 · DOI
  26. Blums, 1995, Some new problems of complex thermomagnetic and diffusion-driven convection in magnetic colloids, J. Magn. Magn. Mater., 149, 111, 10.1016/0304-8853(95)00350-9 · DOI
  27. Nacev, 2012, Towards control of magnetic fluids in patients: Directing therapeutic nanoparticles to disease locations, IEEE Control Syst., 32, 32, 10.1109/MCS.2012.2189052 · DOI
  28. Odenbach, 2001, Invalidation of the kelvin force in ferrofluids, Phys. Rev. Lett., 86, 328, 10.1103/PhysRevLett.86.328 · DOI

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Metadata

Authors
Reinelt, M., Ahlfs, J., Stein, R., Alexiou, C., Bänsch, E., Friedrich, R. P., Lyer, S., Neuss-Radu, M., & Neuß, N.
Affiliations
Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
Corresponding author
Neuß, Nicolas
Venue
Journal of Magnetism and Magnetic Materials
Publisher
Elsevier BV
Published
2023-09
Volume
582
Pages
170984
ISSN
0304-8853 (ISSN-L)
OpenAlex
W4382983135
Cited by
12
References
0
Citations by year
2026: 3 · 2025: 5 · 2024: 4
FWCI
0.95
Type
journal article
Language
en
Open access
Locations
Journal of Magnetism and Magnetic Materials (publishedVersion, cc-by)
Funders
Forschungsstiftung Medizin am Universitätsklinikum Erlangen
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › Characterization and Applications of Magnetic Nanoparticles
  • Physical Sciences › Materials Science › Biomaterials › Nanoparticle-Based Drug Delivery
  • Physical Sciences › Chemical Engineering › Fluid Flow and Transfer Processes › Particle Dynamics in Fluid Flows
Keywords
superparamagnetic iron oxide nanoparticles, magnetohydrodynamics, advection-diffusion equation, magnetostatics, laminar pipe flow, external magnetic field, surface concentration, nanoparticle retention, finite element analysis, model validation

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