Abstract
We have employed a multiscale modeling approach that combines ab-initio electronic structure calculations with atomic and mesoscopic scale modeling to describe the magnetic behavior of assemblies of magnetic nano-particles (MNPs) with core/surface morphology. Our modeling is based on the calculated atomistic parameters and we rescale them after the reduction of the simulated number of the NPs atomic spins to the minimum necessary to represent their magnetic structure in the assemblies. Monte Carlo simulations are them performed to study their macroscopic magnetic behavior. We apply our model to (a) \(\text {CoFe}_{2}\mathrm{O}_{4}\) NPs coated with two different surfactants and (b) bovine serum albumin-coated \(\text {MnFe}_{2}\text {O}_{4}\) MNPs’ clusters. Our approach overcomes current computational limitations. The numerical results produced are in excellent agreement with the experimental findings illustrating the potentials of our strategy to simulate the magnetic behavior of complex magnetic nanoparticle systems and to optimize their magnetic properties for advanced energy and biotechnology nanomaterial applications.
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Acknowledgments
This work was supported by the European Union’s Horizon 2020 Research and Innovation Programme: under grant agreement No. 731976 (MAGENTA). The authors acknowledge the computational time granted from the Greek Research & Technology Network (GRNET) in the Greek National HPC facility ARIS (http://hpc.grnet.gr) under project MNBIE (pr005030).
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Vasilakaki, M., Ntallis, N., Trohidou, K.N. (2020). Application of Multiscale Computational Techniques to the Study of Magnetic Nanoparticle Systems. In: Wyrzykowski, R., Deelman, E., Dongarra, J., Karczewski, K. (eds) Parallel Processing and Applied Mathematics. PPAM 2019. Lecture Notes in Computer Science(), vol 12044. Springer, Cham. https://doi.org/10.1007/978-3-030-43222-5_26
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DOI: https://doi.org/10.1007/978-3-030-43222-5_26
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