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Deconvolution of ferromagnetic resonance spectrum of magnetic nanoparticle assembly using genetic algorithm

The ferromagnetic resonance (FMR) spectra of dilute random assemblies of magnetite nanoparticles with cubic magnetic anisotropy and various aspect ratios are calculated using the stochastic Landau–Lifshitz equation at a finite temperature, T = 300 K, taking into account the thermal fluctuations of t...

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Autores principales: Usov, N. A., Serebryakova, O. N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8873211/
https://www.ncbi.nlm.nih.gov/pubmed/35210469
http://dx.doi.org/10.1038/s41598-022-07105-7
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author Usov, N. A.
Serebryakova, O. N.
author_facet Usov, N. A.
Serebryakova, O. N.
author_sort Usov, N. A.
collection PubMed
description The ferromagnetic resonance (FMR) spectra of dilute random assemblies of magnetite nanoparticles with cubic magnetic anisotropy and various aspect ratios are calculated using the stochastic Landau–Lifshitz equation at a finite temperature, T = 300 K, taking into account the thermal fluctuations of the particle magnetic moments. Particles of non-spherical shape in the first approximation are described as elongated spheroids with a given semiaxes ratio a/b, where a and b are the long and transverse semiaxes of a spheroid, respectively. A representative database of FMR spectra is created for assemblies of randomly oriented spheroidal magnetite nanoparticles with various transverse diameters D = 5–25 nm, moderate aspect ratios a/b = 1.0–1.8, and magnetic damping constants κ = 0.1, 0.2. The basic FMR spectra of assemblies with D = 25 nm at different aspect ratios can be considered as representatives of assemblies of single-domain magnetite nanoparticles with transverse diameters D > 25 nm. The database is calculated at exciting frequency f = 4.9 GHz (S-band) to clarify the details of the FMR spectrum that depend on the particle magnetic anisotropy nature. The data obtained make it possible to analyze arbitrary combined FMR spectra constructed as weighted linear combinations of FMR spectra of the base assemblies. In addition, using a genetic algorithm, the corresponding inverse problem is solved. The latter consists in determining the volume fractions of the base assemblies in some arbitrary nanoparticle assembly, which is represented by its FMR spectrum.
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spelling pubmed-88732112022-02-25 Deconvolution of ferromagnetic resonance spectrum of magnetic nanoparticle assembly using genetic algorithm Usov, N. A. Serebryakova, O. N. Sci Rep Article The ferromagnetic resonance (FMR) spectra of dilute random assemblies of magnetite nanoparticles with cubic magnetic anisotropy and various aspect ratios are calculated using the stochastic Landau–Lifshitz equation at a finite temperature, T = 300 K, taking into account the thermal fluctuations of the particle magnetic moments. Particles of non-spherical shape in the first approximation are described as elongated spheroids with a given semiaxes ratio a/b, where a and b are the long and transverse semiaxes of a spheroid, respectively. A representative database of FMR spectra is created for assemblies of randomly oriented spheroidal magnetite nanoparticles with various transverse diameters D = 5–25 nm, moderate aspect ratios a/b = 1.0–1.8, and magnetic damping constants κ = 0.1, 0.2. The basic FMR spectra of assemblies with D = 25 nm at different aspect ratios can be considered as representatives of assemblies of single-domain magnetite nanoparticles with transverse diameters D > 25 nm. The database is calculated at exciting frequency f = 4.9 GHz (S-band) to clarify the details of the FMR spectrum that depend on the particle magnetic anisotropy nature. The data obtained make it possible to analyze arbitrary combined FMR spectra constructed as weighted linear combinations of FMR spectra of the base assemblies. In addition, using a genetic algorithm, the corresponding inverse problem is solved. The latter consists in determining the volume fractions of the base assemblies in some arbitrary nanoparticle assembly, which is represented by its FMR spectrum. Nature Publishing Group UK 2022-02-24 /pmc/articles/PMC8873211/ /pubmed/35210469 http://dx.doi.org/10.1038/s41598-022-07105-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Usov, N. A.
Serebryakova, O. N.
Deconvolution of ferromagnetic resonance spectrum of magnetic nanoparticle assembly using genetic algorithm
title Deconvolution of ferromagnetic resonance spectrum of magnetic nanoparticle assembly using genetic algorithm
title_full Deconvolution of ferromagnetic resonance spectrum of magnetic nanoparticle assembly using genetic algorithm
title_fullStr Deconvolution of ferromagnetic resonance spectrum of magnetic nanoparticle assembly using genetic algorithm
title_full_unstemmed Deconvolution of ferromagnetic resonance spectrum of magnetic nanoparticle assembly using genetic algorithm
title_short Deconvolution of ferromagnetic resonance spectrum of magnetic nanoparticle assembly using genetic algorithm
title_sort deconvolution of ferromagnetic resonance spectrum of magnetic nanoparticle assembly using genetic algorithm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8873211/
https://www.ncbi.nlm.nih.gov/pubmed/35210469
http://dx.doi.org/10.1038/s41598-022-07105-7
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