High-frequency ferromagnetic resonance on ultrafine cobalt particles

We report on high-frequency (300-700 GHz) ferromagnetic resonance (HF-FMR) measurements on cobalt superparamagnetic particles with strong uniaxial effective anisotropy. We derive the dynamical susceptibility of the system on the basis of an independent-grain model by using a rectangular approach. Numerical simulations give typical line shapes depending on the anisotropy, the gyromagnetic ratio, and the damping constant. HF-FMR experiments have been performed on two systems of ultrafine cobalt particles of different sizes with a mean number of atoms per particles of 150 +/- 20 and 310 +/- 20. In both systems, the magnetic anisotropy is found to be enhanced compared to the bulk value, and increases as the particle size decreases, in accordance with previous determinations from magnetization measurements. Although no size effect has been observed on the gyromagnetic ratio, the transverse relaxation time is two orders of magnitude smaller than the bulk value indicating strong damping effects, possibly originating from surface spin disorders.

High-field ferromagnetic resonance in fine particles

We investigate high-field ferromagnetic resonance of superparamagnetic particles with uniaxial anisotropy, In this case, since the field is large enough to saturate the magnetization, the thermal orientational fluctuations of the magnetic moment of the particle are negligible. Thus, we derive the dynamic susceptibility of the system on the basis of an independent particle model. High-field ferromagnetic resonance has been performed on fine cobalt particles, The analysis of the spectra obtained at different frequencies allows us to estimate the effective magnetic anisotropy, the gyromagnetic ratio, and the transverse relaxation time. (C) 1998 Elsevier Science B.V. All rights reserved.

High-field ferromagnetic resonance in fine particles

We investigate high-field ferromagnetic resonance of superparamagnetic particles with uniaxial anisotropy, In this case, since the field is large enough to saturate the magnetization, the thermal orientational fluctuations of the magnetic moment of the particle are negligible. Thus, we derive the dynamic susceptibility of the system on the basis of an independent particle model. High-field ferromagnetic resonance has been performed on fine cobalt particles, The analysis of the spectra obtained at different frequencies allows us to estimate the effective magnetic anisotropy, the gyromagnetic ratio, and the transverse relaxation time. (C) 1998 Elsevier Science B.V. All rights reserved.

HHT在电磁信号处理中的应用

In modem signal Processing，non－linear，non－Gaussian and non－stable signals are usually the analyzed and Processed objects，especially non－stable signals. The convention always to analyze and Process non－stable signals are： short time Fourier transform，Wigner－Ville distribution，wavelet Transform and so on. But the above three algorithms are all based on Fourier Transform，so they all have the shortcoming of Fourier Analysis and cannot get rid of the localization of it. Hilbert－Huang Transform is a new non－stable signal processing technology，proposed by N. E. Huang in 1998. It is composed of Empirical Mode Decomposition (referred to as EMD) and Hilbert Spectral Analysis (referred to as HSA). After EMD Processing，any non－stable signal will be decomposed to a series of data sequences with different scales. Each sequence is called an Intrinsic Mode Function (referred to as IMF). And then the energy distribution plots of the original non－stable signal can be found by summing all the Hilbert spectrums of each IMF. In essence，this algorithm makes the non－stable signals become stable and decomposes the fluctuations and tendencies of different scales by degrees and at last describes the frequency components with instantaneous frequency and energy instead of the total frequency and energy in Fourier Spectral Analysis. In this case，the shortcoming of using many fake harmonic waves to describe non－linear and non－stable signals in Fourier Transform can be avoided. This Paper researches in the following parts： Firstly，This paper introduce the history and development of HHT，subsequently the characters and main issues of HHT. This paper briefly introduced the basic realization principles and algorithms of Hilbert－Huang transformation and confirms its validity by simulations. Secondly, This paper discuss on some shortcoming of HHT. By using FFT interpolation, we solve the problem of IMF instability and instantaneous frequency undulate which are caused by the insufficiency of sampling rate. As to the bound effect caused by the limitation of envelop algorithm of HHT, we use the wave characteristic matching method, and have good result. Thirdly, This paper do some deeply research on the application of HHT in electromagnetism signals processing. Based on the analysis of actual data examples, we discussed its application in electromagnetism signals processing and noise suppression. Using empirical mode decomposition method and multi-scale filter characteristics can effectively analyze the noise distribution of electromagnetism signal and suppress interference processing and information interpretability. It has been founded that selecting electromagnetism signal sessions using Hilbert time-frequency energy spectrum is helpful to improve signal quality and enhance the quality of data.