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Reproducibility and Scalability of Magnetic Nanoheater Synthesis
Jesus G Ovejero1, Alvaro Gallo-Cordova1, Alejandro G Roca1
1Department of Energy Environment and Health, Instituto de Ciencia de Materiales de Madrid, C.S.I.C., Sor Juana Inés de la Cruz 3, Cantoblanco, ES28049 Madrid, Spain.
Nanomaterials (Basel, Switzerland)
|August 27, 2021
Summary
This study scaled up iron oxide nanoparticle synthesis for reproducible quality. Prolonging high-temperature synthesis improved yield, particle size, and reproducibility, enhancing their use in magnetic hyperthermia applications.
Area of Science:
- Materials Science
- Nanotechnology
- Biomedical Engineering
Background:
- Reproducible synthesis of magnetic nanoparticles is crucial for applications.
- Scaling up nanoparticle production presents challenges in maintaining quality and consistency.
Purpose of the Study:
- To explore the scaled-up synthesis of multi-core iron oxide nanoparticles.
- To investigate the effect of prolonged high-temperature steps on nanoparticle characteristics and reproducibility.
- To assess the suitability of synthesized nanoparticles for magnetic hyperthermia.
Main Methods:
- Utilized thermal decomposition in organic media with kilogram-scale reagents.
- Extended the high-temperature synthesis step from minutes to hours.
- Employed statistical analysis to address variability in colloidal crystallization nucleation.
- Characterized synthesized nanoparticles for structural, colloidal, and magnetic properties.
Main Results:
- Prolonging high-temperature synthesis generally increased yield, particle size, and reproducibility.
- Synthesized nanostructures comprised a mix of single- and multi-core nanoparticles.
- Nanoparticle performance in magnetic hyperthermia correlated strongly with crystallite size.
Conclusions:
- Extended high-temperature synthesis is a viable strategy for improving iron oxide nanoparticle production.
- Optimized nanoparticle characteristics enhance their potential for magnetic hyperthermia treatments.
- The study provides a framework for ranking nanoparticle batches based on reproducibility.

