journal article·2013-04Open access

Multifunctional luminomagnetic FePt@Fe3O4/SiO2/Rhodamine B/SiO2 nanoparticles with high magnetic emanation for biomedical applications

C. G. S. Souza, W. Beck, L. C. Varanda

Journal of Nanoparticle Research· Volume 15· Issue 4

Abstract

Multifunctional luminomagnetic nanoparticles with average particle diameter around 34 nm and enhanced magnetic properties are reported. FePt@Fe3O4 magnetic nuclei with 6.0 ± 0.7 nm in a core–shell nanostructure were synthesized combining the modified polyol and seed-mediated growth processes, coated with silica by reverse micelle route and annealed. Individual silica-coated magnetic core resulted in a mixture of hard and soft magnetic nanostructured material with superparamagnetic behavior and enhanced magnetic emanation. Luminescent dye Rhodamine B (RhB) was incorporated onto the nanoparticle surface followed by coating with an outer silica shell in a layer-by-layer structure. The bifunctional luminomagnetic nanoparticles of FePt@Fe3O4/SiO2/RhB/SiO2 present high-water dispersibility, colloidal stability, and hydrophilic surface with isoelectric point of 2.7. The superparamagnetic behavior was preserved with blocking temperature of 40 K and the saturation magnetization of the final product equal 64.3 emu g−1 was around ten times higher than observed for nanoparticles using pure magnetite core synthesized in the same conditions. Inner and outer silica layers minimize luminescence quenching processes due to avoid contact between dye and both magnetic core and solvent, respectively, resulting in a stable emission for, at least, 1 h. These properties allied with the possibility to use different dye compounds gives a potential bifunctional nanosensor for biomedical applications.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Nanoparticle-Based Drug Delivery · Gold and Silver Nanoparticles Synthesis and Applications · Nanocluster Synthesis and Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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