Improving the Size Homogeneity of Multicore Superparamagnetic Iron Oxide Nanoparticles
Superparamagnetic iron oxide nanoparticles (SPIONs) have been widely explored for use in many biomedical applications. Methods for synthesis of magnetic nanoparticle (MNP), however, typically yield multicore structures with broad size distribution, resulting in suboptimal and variable performance in...
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MDPI AG
2020-05-01
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| Series: | International Journal of Molecular Sciences |
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| Online Access: | https://www.mdpi.com/1422-0067/21/10/3476 |
| _version_ | 1797567998448369664 |
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| author | Barry J. Yeh Tareq Anani Allan E. David |
| author_facet | Barry J. Yeh Tareq Anani Allan E. David |
| author_sort | Barry J. Yeh |
| collection | DOAJ |
| description | Superparamagnetic iron oxide nanoparticles (SPIONs) have been widely explored for use in many biomedical applications. Methods for synthesis of magnetic nanoparticle (MNP), however, typically yield multicore structures with broad size distribution, resulting in suboptimal and variable performance in vivo. In this study, a new method for sorting SPIONs by size, labeled diffusive magnetic fractionation (DMF), is introduced as an improvement over conventional magnetic field flow fractionation (MFFF). Unlike MFFF, which uses a constant magnetic field to capture particles, DMF utilizes a pulsed magnetic field approach that exploits size-dependent differences in the diffusivity and magnetic attractive force of SPIONs to yield more homogenous particle size distributions. To compare both methods, multicore SPIONs with a broad size distribution (polydispersity index (PdI) = 0.24 ± 0.05) were fractionated into nine different-sized SPION subpopulations, and the PdI values were compared. DMF provided significantly improved size separation compared to MFFF, with eight out of the nine fractionations having significantly lower PdI values (<i>p</i> value < 0.01). Additionally, the DMF method showed a high particle recovery (>95%), excellent reproducibility, and the potential for scale-up. Mathematical models were developed to enable optimization, and experimental results confirmed model predictions (<i>R</i><sup>2</sup> = 0.98). |
| first_indexed | 2024-03-10T19:50:08Z |
| format | Article |
| id | doaj.art-f8c9942adb8d47bda573511edb2b8876 |
| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-03-10T19:50:08Z |
| publishDate | 2020-05-01 |
| publisher | MDPI AG |
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| series | International Journal of Molecular Sciences |
| spelling | doaj.art-f8c9942adb8d47bda573511edb2b88762023-11-20T00:29:29ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672020-05-012110347610.3390/ijms21103476Improving the Size Homogeneity of Multicore Superparamagnetic Iron Oxide NanoparticlesBarry J. Yeh0Tareq Anani1Allan E. David2Department of Chemical Engineering, Samuel Ginn College of Engineering, Auburn University, Auburn, AL 36849, USADepartment of Chemical Engineering, Samuel Ginn College of Engineering, Auburn University, Auburn, AL 36849, USADepartment of Chemical Engineering, Samuel Ginn College of Engineering, Auburn University, Auburn, AL 36849, USASuperparamagnetic iron oxide nanoparticles (SPIONs) have been widely explored for use in many biomedical applications. Methods for synthesis of magnetic nanoparticle (MNP), however, typically yield multicore structures with broad size distribution, resulting in suboptimal and variable performance in vivo. In this study, a new method for sorting SPIONs by size, labeled diffusive magnetic fractionation (DMF), is introduced as an improvement over conventional magnetic field flow fractionation (MFFF). Unlike MFFF, which uses a constant magnetic field to capture particles, DMF utilizes a pulsed magnetic field approach that exploits size-dependent differences in the diffusivity and magnetic attractive force of SPIONs to yield more homogenous particle size distributions. To compare both methods, multicore SPIONs with a broad size distribution (polydispersity index (PdI) = 0.24 ± 0.05) were fractionated into nine different-sized SPION subpopulations, and the PdI values were compared. DMF provided significantly improved size separation compared to MFFF, with eight out of the nine fractionations having significantly lower PdI values (<i>p</i> value < 0.01). Additionally, the DMF method showed a high particle recovery (>95%), excellent reproducibility, and the potential for scale-up. Mathematical models were developed to enable optimization, and experimental results confirmed model predictions (<i>R</i><sup>2</sup> = 0.98).https://www.mdpi.com/1422-0067/21/10/3476magnetic nanoparticleSPIONsize distributionmagnetic attractiondiffusionmagnetic field flow fractionation (MFFF) |
| spellingShingle | Barry J. Yeh Tareq Anani Allan E. David Improving the Size Homogeneity of Multicore Superparamagnetic Iron Oxide Nanoparticles International Journal of Molecular Sciences magnetic nanoparticle SPION size distribution magnetic attraction diffusion magnetic field flow fractionation (MFFF) |
| title | Improving the Size Homogeneity of Multicore Superparamagnetic Iron Oxide Nanoparticles |
| title_full | Improving the Size Homogeneity of Multicore Superparamagnetic Iron Oxide Nanoparticles |
| title_fullStr | Improving the Size Homogeneity of Multicore Superparamagnetic Iron Oxide Nanoparticles |
| title_full_unstemmed | Improving the Size Homogeneity of Multicore Superparamagnetic Iron Oxide Nanoparticles |
| title_short | Improving the Size Homogeneity of Multicore Superparamagnetic Iron Oxide Nanoparticles |
| title_sort | improving the size homogeneity of multicore superparamagnetic iron oxide nanoparticles |
| topic | magnetic nanoparticle SPION size distribution magnetic attraction diffusion magnetic field flow fractionation (MFFF) |
| url | https://www.mdpi.com/1422-0067/21/10/3476 |
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