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Tailoring heat dissipation in linear arrays of dipolar interacting magnetic nanoparticles

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Abstract

We perform numerical simulations to analyse the effect of dipolar interaction, particle size D and thermal fluctuations on the magnetic hysteresis in the linear array of magnetic nanoparticles (MNPs). The shape of the hysteresis curve is that of Stoner and Wohlfarth particle for non-interacting MNPs and temperature \(T=0\) K. The area under the magnetic hysteresis curve is minimal with \(D \approx 8\)–16 nm and \(T=300\) K, indicating the predominance of superparamagnetic character. Interestingly, the dipolar interaction of sufficient strength moves the nanoparticles from superparamagnetic to a blocked state even at \(T=300\) K, resulting in an enhanced hysteresis loop area in such cases. Even with negligible dipolar interaction strength (\(\lambda \approx 0.0\)) and \(T=300\) K, the hysteresis loop area is appreciable for ferromagnetic particles (\(D>16\) nm). The coercive field \(\mu ^{}_0H^{}_c\) and the blocking temperature \(T^{}_B\) also depend strongly on the dipolar interaction. They are found to increase with dipolar interaction strength \(\lambda \) and particle size. Our extensive simulations also reveal a significant deviation of \(\mu ^{}_0H^{}_c\) from \(T^{3/4}\) dependence because of dipolar interaction. There is a rapid fall in the amount of heat dissipated \(E^{}_H\) and coercive field with temperature for superparamagnetic nanoparticles (\(D\approx 8\)–16 nm) and small dipolar interaction strength (\(\lambda \le 0.6\)). In contrast, they are significantly large and depend weakly on thermal fluctuations for \(D>16\) nm. Therefore, observations made in the present work can help experimentalists to choose precise values of system parameters to obtain desired hysteresis properties, essential for diverse technological applications such as magnetic hyperthermia, data storage, etc.

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Anand, M. Tailoring heat dissipation in linear arrays of dipolar interacting magnetic nanoparticles. Pramana - J Phys 96, 132 (2022). https://doi.org/10.1007/s12043-022-02373-4

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