Investigation of magnetic anisotropy in Co nanoparticles using ferromagnetic resonance technique

Sendilkumar, A.; Kasture, Manasi; Patel, Pitamber; Ramana, Chepuri V.; Prasad, B. L. V.; Srinath, S.

doi:10.1088/1742-6596/200/7/072088

Cited by 3 publications

(6 citation statements)

References 7 publications

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“…This technique has been sufficiently developed for bulk single-crystals and thin magnetic films [2][3][4] . A significant number of theoretical and experimental studies have also been devoted to the investigation of FMR spectra of assemblies of magnetic nanoparticles [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23] . However, it should be noted that the theory of ferromagnetic resonance is well developed for isolated single-domain magnetic nanoparticles with various types of magnetic anisotropy 1-3 .…”

mentioning

confidence: 99%

“…Moreover, the FMR spectra of sufficiently small nanoparticles are greatly influenced by thermal fluctuations of the particle magnetic moments 7,8,19,20 . Finally, strong magneto-dipole (MD) interaction in a dense nanoparticle assembly affects the dynamics of the particle magnetic moments 14,18,22,23 . Under the influence of all these factors, the experimental FMR spectrum of an assembly of magnetic nanoparticles turns out to be very smoothed and broad 18,19,21,22 .At present the evolution of the FMR spectra of individual non-interacting nanoparticles, depending on changes in their sizes and anisotropy constants, the temperature of the assembly, and other factors has been well studied theoretically [5][6][7][8][9][10][11]15,17,20 .…”

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confidence: 99%

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

Usov

Serebryakova

2022

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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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confidence: 99%

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confidence: 99%

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

Usov

Serebryakova

2022

Sci Rep

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“…The FMR spectra of sufficiently small nanoparticles are greatly influenced by thermal fluctuations of the particle magnetic moments [7,8,19,20]. Finally, strong magneto-dipole (MD) interaction in a dense nanoparticle assembly affects the dynamics of the particle magnetic moments [14,18,22,23]. Under combined action of these factors, the experimental FMR spectrum of an assembly of magnetic nanoparticles turns out to be very smoothed and broad [18,19,21,22].…”

Section: Introductionmentioning

confidence: 99%

“…This technique has been sufficiently developed for bulk single-crystals and thin magnetic films [2][3][4]. A significant number of theoretical and experimental studies were also devoted to the investigation of FMR spectra of assemblies of magnetic nanoparticles [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]. It should be noted, however, that the theory of ferromagnetic resonance is well developed for isolated single-domain magnetic nanoparticles with various types of magnetic anisotropy [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

Deconvolution of Ferromagnetic Resonance Spectrum of Magnetic Nanoparticle Assembly Using Genetic Algorithm

Usov

Serebryakova

2021

Preprint

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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 k = 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 clearly the details of the FMR spectrum that depend on the nature of the particle magnetic anisotropy. 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.PACS: 75.20.-g; 75.50.Tt; 75.40.Mg

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Preparation of Pure Cobalt Nanoparticles by Electric Arc Discharge Method in Ethylene Glycol

et al. 2013

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Synthesis of Cobalt nanoparticles often entails toxic and expensive physical-chemistry methods. Fabrication of pure cobalt nanoparticles (NPs) using a simple and low-cost electric arc discharge method in ethylene glycol (EG) is suggested for the first time. The effect of different arc discharge currents (10, 20 and 30 A) on the size and optical absorption of the NPs are studied. Dynamic light scattering (DLS) and UV-visible spectroscopy result indicate that at an arc current of 10 A NPs of about 92.95 nm are produced and increasing the arc current leads to larger NPs. UV-visible spectroscopy data shows that the solvent gets more and more transparent with time. Sonication proves that this effect is related to agglomeration of the NPs. Formation of the pure Co NPs are evidenced by means of X-ray diffraction (XRD) measurements which gives an average size of about 21 nm using Scherrer's relation. Magnetization measurements of the samples are carried out by Alternating Gradient Force Magnetometer (AGFM). The results demonstrate the ability of the arc discharge method for direct formation of Co NPs in EG medium.

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Investigation of magnetic anisotropy in Co nanoparticles using ferromagnetic resonance technique

Cited by 3 publications

References 7 publications

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

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

Deconvolution of Ferromagnetic Resonance Spectrum of Magnetic Nanoparticle Assembly Using Genetic Algorithm

Preparation of Pure Cobalt Nanoparticles by Electric Arc Discharge Method in Ethylene Glycol

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