Maximizing Hysteretic Losses in Magnetic Ferrite Nanoparticles via Model-Driven Synthesis and Materials Optimization

This article develops a set of design guidelines for maximizing heat dissipation characteristics of magnetic ferrite MFe[subscript 2]O[subscript 4] (M = Mn, Fe, Co) nanoparticles in alternating magnetic fields. Using magnetic and structural nanoparticle characterization, we identify key synthetic pa...

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Bibliographic Details
Main Authors: Chen, Ritchie, Anikeeva, Polina Olegovna, Christiansen, Michael Gary
Other Authors: Massachusetts Institute of Technology. Department of Materials Science and Engineering
Format: Article
Language:en_US
Published: American Chemical Society (ACS) 2015
Online Access:http://hdl.handle.net/1721.1/92978
https://orcid.org/0000-0002-6420-1616
https://orcid.org/0000-0001-6495-5197
https://orcid.org/0000-0003-0946-0401
Description
Summary:This article develops a set of design guidelines for maximizing heat dissipation characteristics of magnetic ferrite MFe[subscript 2]O[subscript 4] (M = Mn, Fe, Co) nanoparticles in alternating magnetic fields. Using magnetic and structural nanoparticle characterization, we identify key synthetic parameters in the thermal decomposition of organometallic precursors that yield optimized magnetic nanoparticles over a wide range of sizes and compositions. The developed synthetic procedures allow for gram-scale production of magnetic nanoparticles stable in physiological buffer for several months. Our magnetic nanoparticles display some of the highest heat dissipation rates, which are in qualitative agreement with the trends predicted by a dynamic hysteresis model of coherent magnetization reversal in single domain magnetic particles. By combining physical simulations with robust scalable synthesis and materials characterization techniques, this work provides a pathway to a model-driven design of magnetic nanoparticles tailored to a variety of biomedical applications ranging from cancer hyperthermia to remote control of gene expression.