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Magnetic nanoparticles (MNPs) have been widely studied for bio-sensing applications, where suspended and immobilized MNPs can be magnetically distinguished using their different magnetic properties. We study magnetic properties of suspended and immobilized MNPs when the Néel relaxation time is much shorter than the Brownian. We show in both numerical simulation and experiment that they have different magnetic properties such as AC magnetization curves and harmonic spectra even though the dynamic behavior of both MNP types is primarily dominated by Néel relaxation. This difference is caused by the partial alignment of the easy axes in suspended MNPs when an AC magnetic field is applied. We introduce a distribution function for the angle of easy axis alignment. We also show a method to evaluate the distribution function from the measured AC magnetization curve and clarify the relationship between easy axis alignment and the AC field strength. Using the distribution function, we can quantitatively discuss the effect of easy axis alignment on the magnetic properties of suspended MNPs. The obtained results provide a basis for using MNPs in bio-sensing. [ABSTRACT FROM AUTHOR]

Magnetic nanoparticles (MNPs) have been widely studied for use in biomedical applications such as magnetic particle imaging and magnetic hyperthermia. We studied the effect of easy axis alignment on dynamic magnetization of both immobilized and suspended MNPs. For immobilized samples, easy axes of magnetization were aligned by applying a dc field during immobilization. For suspended samples, the applied ac field was set so that the alignment of the easy axes was caused by the ac field. Magnetization (M–H) curves of MNPs with different degrees of easy axis alignment were measured with an applied ac field. We found that the easy axis alignment of MNPs considerably affects their M–H curve and harmonic spectra, which indicates the importance of this alignment for their biomedical applications. The experimental results were quantitatively explained with numerical simulation that took account of easy axis alignment and core size distribution in the sample. We can express the degree of easy axis alignment using a distribution function of the easy axis angle for both immobilized and suspended cases. The distribution function will be useful for quantitatively evaluating MNP performance in biomedical applications. [ABSTRACT FROM AUTHOR]

We estimated the effective magnetic anisotropy constant K of magnetic nanoparticles (MNPs) from the temperature dependence of the coercive field Hc of the M–H curve for use in biosensing applications. For this purpose, a previous analytical expression for Hc was extended so that it can be applied to nanoparticles with a size distribution. Using the extended expression for Hc, we estimated the K value of multi-core based MNP sample that consists of crystalline aggregates of elementary particles. We prepared three MNP samples. One is Resovist, in which elementary particles and aggregates are mixed. The Resovist sample was magnetically divided into two fractions called MS1 and MS3, which included mainly aggregates and elementary particles, respectively. We discuss the K value of elementary particles and aggregates from the comparison among the three samples. It is suggested that the K value of the aggregates is much smaller than that of the elementary particles. The temperature dependence of K of the aggregates is also discussed. [ABSTRACT FROM AUTHOR]

A new detection system for magnetic particles, which can operate in an unshielded environment, is developed using a fundamental mode orthogonal fluxgate gradiometer. The proposed detection system offers the advantages of cost, size, and weight reduction as compared to contamination detection systems using superconducting quantum interference device sensor. The detection system can be used to detect metallic contamination in foods or lithium ion battery production lines. The system has been investigated numerically to optimize various design parameters of the system. Experimental setup has been developed to evaluate some of the numerically predicted results. Steel balls were successfully detected down to the diameter of 50 μm. [ABSTRACT FROM AUTHOR]