Model Driven Optimization of Magnetic Anisotropy of Exchange-Coupled Core鈥揝hell Ferrite Nanoparticles for Maximal Hysteretic Loss

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• 作者：Qian Zhang ; Idoia Castellanos-Rubio ; Rahul Munshi ; I帽aki Orue ; Beatriz Pelaz ; Katharina Ines Gries ; Wolfgang J. Parak ; Pablo del Pino ; Arnd Pralle
• 刊名：Chemistry of Materials
• 出版年：2015
• 出版时间：November 10, 2015
• 年：2015
• 卷：27
• 期：21
• 页码：7380-7387
• 全文大小：430K
• ISSN：1520-5002

文摘

This study provides a guide to maximizing hysteretic loss by matching the design and synthesis of superparamagnetic nanoparticles to the desired hyperthermia application. The maximal heat release from magnetic nanoparticles to the environment depends on intrinsic properties of magnetic nanoparticles (e.g., size, magnetization, and magnetic anisotropy) and extrinsic properties of the applied fields (e.g., frequency and field strength). Often, the biomedical hyperthermia application limits flexibility in settings of many parameters (e.g., nanoparticle size and mobility, field strength, and frequency). We show that core鈥搒hell nanoparticles combining a soft (Mn ferrite) and a hard (Co ferrite) magnetic material form a system in which the effective magnetic anisotropy can be easily tuned independently of the nanoparticle size. A theoretical framework to include the crystal anisotropy contribution of the Co ferrite phase to the nanoparticle鈥檚 total anisotropy is developed. The experimental results confirm that this framework predicts the hysteretic heating loss correctly when including nonlinear effects in an effective susceptibility. Hence, we provide a guide on how to characterize the magnetic anisotropy of core鈥搒hell magnetic nanoparticles, model the expected heat loss, and thereby synthesize tuned nanoparticles for a particular biomedical application.