journal article·2022-04

Carbothermal treated ferrite nanoparticles with improved magnetic heating efficiency and T1-MRI performance

Xudong Zuo, Haitang Xu, Jiandong Zhang, Yongxing Sui, Tao Fang, Dongmei Zhang

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Abstract

Ferrite nanoparticle based T1-magnetic resonance imaging (T1-MRI) guided magnetic hyperthermia is a promising method for accurate tumor treatment. In previous studies, ultra-small sized ferrite nanoparticles were required to achieve excellent T1-MRI performance. However, an ultra-small size is usually accompanied by weak magnetization, resulting in a low magnetic heating efficiency, which is insufficient for magnetic hyperthermia. Therefore, ferrite nanoparticles with high magnetic heating efficiency and excellent T1-MRI performance capabilities are still highly desired. Here, oxygen vacancies are introduced in Mn 0.6Zn 0.4Al 0.2Fe 1.8O 4 ferrite nanoparticles by applying carbothermal treatments. As oxygen vacancy concentrations increase, the intrinsic loss power increases up to 2.55 nH m 2/kg, which is 33% higher than that of Fe 3O 4 nanoparticles used in magnetic hyperthermia. Specific absorption rate (SAR) calculations indicate that the predominant heat generation mechanism changes from hysteresis loss and relaxation loss to eddy current loss owing to conductivity enhancement by carbothermal treatments. The eddy current loss accounts for 70.6% of the total SAR, and plays a crucial role in increasing magnetic heating efficiency. In addition, Mn 0.6Zn 0.4Al 0.2Fe 1.8O 4 ferrite nanoparticles with oxygen vacancies exhibit a significantly high r1 value of 9.69 mM −1 s −1 and a low r2/r1 ratio of 1.6 on a 3.0 T scanner. This is because oxygen vacancies naturally exhibit oxygen affinity in water molecules. The findings of this study could serve as a methodological reference of preparing ferrite nanoparticles for T1-MRI guided magnetic hyperthermia.
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Research context

OpenAlex topics: Characterization and Applications of Magnetic Nanoparticles · Magnetic Properties and Synthesis of Ferrites · Nanoparticle-Based Drug Delivery

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

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