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15 May 2003

Volume 93, Issue 10, pp. 5855-8792

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Reversal-field memory in magnetic hysteresis

H. G. Katzgraber, F. Pázmándi, C. R. Pike, Kai Liu, R. T. Scalettar, K. L. Verosub, and G. T. Zimányi

J. Appl. Phys. 93, 6617 (2003); http://dx.doi.org/10.1063/1.1557354 (3 pages)

Online Publication Date: 9 May 2003

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We report results demonstrating a singularity in the hysteresis of magnetic materials, the reversal-field memory effect. This effect creates a nonanalyticity in the magnetization curves at a particular point related to the history of the sample. The microscopic origin of the effect is associated with a local spin-reversal symmetry of the underlying Hamiltonian. We show that the presence or absence of reversal-field memory distinguishes two widely studied models of spin glasses (random magnets). © 2003 American Institute of Physics.
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75.60.Ej Magnetization curves, hysteresis, Barkhausen and related effects
75.10.Nr Spin-glass and other random models
75.60.Jk Magnetization reversal mechanisms
85.70.Li Other magnetic recording and storage devices (including tapes, disks, and drums)
75.50.Ss Magnetic recording materials

Micromagnetic and Preisach analysis of the First Order Reversal Curves (FORC) diagram

Alexandru Stancu, Christopher Pike, Laurentiu Stoleriu, Petronel Postolache, and Dorin Cimpoesu

J. Appl. Phys. 93, 6620 (2003); http://dx.doi.org/10.1063/1.1557656 (3 pages) | Cited 44 times

Online Publication Date: 9 May 2003

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The First Order Reversal Curve (FORC) diagrams of interacting single-domain ferromagnetic particle systems have been found experimentally to contain negative regions. In this paper, we use micromagnetic and phenomenological (Preisach-type) models to help explain the occurrence of these negative regions. In Preisach-type modeling, the position of the negative region is correlated with the sign of the mean-field interactions. In micromagnetic modeling, the position of the negative region is correlated with the spatial arrangement of the particles in the model. © 2003 American Institute of Physics.
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75.40.Mg Numerical simulation studies
75.50.Tt Fine-particle systems; nanocrystalline materials
75.60.Ej Magnetization curves, hysteresis, Barkhausen and related effects
75.60.Ch Domain walls and domain structure

Hysteresis modeling of anisotropic and isotropic nanocrystalline hard magnetic films

D. R. Cornejo, A. Azevedo, and S. M. Rezende

J. Appl. Phys. 93, 6623 (2003); http://dx.doi.org/10.1063/1.1557355 (3 pages) | Cited 2 times

Online Publication Date: 9 May 2003

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In the Hauser model, the magnetic state of a system is obtained by minimizing the so-called total energy function for a statistical set of magnetic domains. In this article, this energetic model of ferromagnetic materials is used in order to calculate hysteresis loops of isotropic and anisotropic nanocrystalline SmCo films at room temperature. A qualitative very good agreement between the calculated and experimental curves is obtained, mainly in the anisotropic case. Also, it has been verified that, under suitable approximations, the free parameters of the model can tie with intrinsic characteristics of the reversal magnetization process. © 2003 American Institute of Physics.
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75.70.Ak Magnetic properties of monolayers and thin films
75.50.Tt Fine-particle systems; nanocrystalline materials
75.50.Ww Permanent magnets
75.50.Cc Other ferromagnetic metals and alloys
75.60.Ej Magnetization curves, hysteresis, Barkhausen and related effects
75.60.Ch Domain walls and domain structure
75.70.Kw Domain structure (including magnetic bubbles and vortices)
75.30.Gw Magnetic anisotropy
75.60.Jk Magnetization reversal mechanisms

Modeling the interrelating effects of plastic deformation and stress on magnetic properties of materials

C. C. H. Lo, E. Kinser, and D. C. Jiles

J. Appl. Phys. 93, 6626 (2003); http://dx.doi.org/10.1063/1.1557356 (3 pages) | Cited 4 times

Online Publication Date: 9 May 2003

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A model has been developed that describes the interrelating effects of plastic deformation and applied stress on hysteresis loops based on the theory of ferromagnetic hysteresis. In the current model the strength of pinning sites for domain walls is characterized by the pinning coefficient keff given by keff=k0+k′σ. The term k0 depicts pinning of domain walls by dislocations and is proportional to ρn, where ρ is the number density of dislocation which is related to the amount of plastic strain, and the exponent n depends on the strength of pinning sites. The second term k′σ∝−3/2λs/2mσ, where m is magnetization and λs is magnetostriction constant, describes the changes in pinning strength on a domain wall induced by an applied stress σ. The model was capable of reproducing the stress dependence of hysteresis loop properties such as coercivity and remanence of a series of nickel samples which were pre-strained to various plastic strain levels. An empirical relation was found between the parameter k0 and the plastic strain, which can be interpreted in terms of the effects on the strength of domain wall pinning of changes in dislocation density and substructure under plastic deformation. © 2003 American Institute of Physics.
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81.40.Rs Electrical and magnetic properties related to treatment conditions
75.80.+q Magnetomechanical effects, magnetostriction
75.60.Ej Magnetization curves, hysteresis, Barkhausen and related effects
81.40.Lm Deformation, plasticity, and creep
62.20.F- Deformation and plasticity

Preisach modeling of magnetization and magnetostriction processes in laminated SiFe alloys

L. Dupré, M. De Wulf, D. Makaveev, V. Permiakov, and J. Melkebeek

J. Appl. Phys. 93, 6629 (2003); http://dx.doi.org/10.1063/1.1557357 (3 pages)

Online Publication Date: 9 May 2003

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In this article, magnetization loops under mechanical stress and magnetostriction loops under quasistatic magnetic excitation conditions are discussed. In both cases, the hysteresis loops are modeled using the Preisach theory. The identification procedure of the material parameters is described. The article discusses first the shape of the Preisach distribution function for the study of magnetostriction loops. Next, a Preisach model is proposed for the description of magnetization loops under mechanical stress starting from the magnetization loop obtained without applying mechanical stress. A setup has been constructed for the measurement of magnetization loops under compressive or tensile stress. Also, a measuring system based on a single sheet tester and on optical displacement measurement techniques is used to establish the magnetostrictive behavior of laminated SiFe alloys. It is shown that a good correspondence between the calculated and measured magnetization and magnetostriction loops is obtained. © 2003 American Institute of Physics.
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75.50.Bb Fe and its alloys
75.80.+q Magnetomechanical effects, magnetostriction
75.60.Ej Magnetization curves, hysteresis, Barkhausen and related effects

Rotational magnetization losses in vector models

Edward Della Torre

J. Appl. Phys. 93, 6632 (2003); http://dx.doi.org/10.1063/1.1557358 (3 pages)

Online Publication Date: 9 May 2003

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Unlike the case of an oscillating magnetic field, power losses in a magnetic material eventually start decreasing as the magnitude of a rotating field increases. In some hysteresis models, the loss increases monotonically as the magnitude of a rotating field increases. The simplified vector Preisach model and the reduced vector Preisach model do not suffer from this error. For magnetization-dependent reversible models, such as the Della Torre-Oti-Kadar, and for state-dependent models such as the complete moving model, the loss per cycle has two components. The first is computed from the Preisach integrals, and the second is computed from the change in the stored energy in the reversible component. It is noted that the latter loss can occur even if there are no Barkhausen jumps. This article discusses the details of how the model accomplishes this. © 2003 American Institute of Physics.
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75.60.Ej Magnetization curves, hysteresis, Barkhausen and related effects
75.60.Jk Magnetization reversal mechanisms

Reversible magnetization and Lorentzian function approximation

B. Azzerboni, E. Cardelli, E. Della Torre, and G. Finocchio

J. Appl. Phys. 93, 6635 (2003); http://dx.doi.org/10.1063/1.1557698 (3 pages) | Cited 4 times

Online Publication Date: 9 May 2003

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The paper proposes the use of a Lorentzian function to describe the irreversible component of the magnetization of soft materials with hysteresis using the Everett’s integral. We will derive an analytical formula to compute the irreversible magnetization, and compute the reversible component by the measurements of the major loop. We shall compare the numerical results with experiments on not-oriented-grain magnetic irons. © 2003 American Institute of Physics.
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75.60.Ej Magnetization curves, hysteresis, Barkhausen and related effects
75.60.Jk Magnetization reversal mechanisms
75.50.Bb Fe and its alloys
02.60.-x Numerical approximation and analysis

Combined Preisach–Mayergoyz-neural-network vector hysteresis model for electrical steel sheets

Dimitre Makaveev, Luc Dupré, Marc De Wulf, and Jan Melkebeek

J. Appl. Phys. 93, 6638 (2003); http://dx.doi.org/10.1063/1.1557699 (3 pages) | Cited 2 times

Online Publication Date: 9 May 2003

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Three versions of a vector hysteresis model for electrical steel sheets are presented, based on the function approximation capabilities of feed-forward neural networks and the memory mechanism of vector hysteresis proposed by Mayergoyz. The first model handles arbitrary vector magnetization patterns, but requires a very extended data set for the training of the neural network. The second model is suitable for convex induction loci and allows a reduction of the required training set. The third model handles the features of the considered magnetization pattern in an alternative way and relaxes the convexity requirement. The choice of the specific model, its parameters, and the network training set depends on the types of magnetization patterns concerned. Arbitrary high accuracy can be reached by extending the complexity of the model and/or the size of the training set. Experimental results for the third model are presented and show the good accuracy of the approach. Standard neural network algorithms are used. © 2003 American Institute of Physics.
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75.60.Ej Magnetization curves, hysteresis, Barkhausen and related effects
75.50.Bb Fe and its alloys
07.05.Mh Neural networks, fuzzy logic, artificial intelligence

Proposal for a standard problem for Preisach based models

Francisco J. Morentín, Oscar Alejos, José M. Muñoz, Luis Torres, and Luis López-Díaz

J. Appl. Phys. 93, 6641 (2003); http://dx.doi.org/10.1063/1.1557359 (3 pages) | Cited 3 times

Online Publication Date: 9 May 2003

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Preisach based models have been usually considered as very convenient tools to simulate both the static and the transient behavior of the irreversible magnetization. In the present work, a very simple physical system consisting of a square array of aligned magnetic particles has been considered in order to be characterized by means of Preisach parameters. A uniform magnetic field is applied in the direction of the easy axis of the particles so that the system has only one dimension. Results reveal that, despite the simplicity of this system, it cannot be successfully defined by means of Preisach parameters. The distribution of interaction fields in the system does not follow a simple Gaussian function. A distribution composed of three balancing peaks is found instead. © 2003 American Institute of Physics.
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75.60.Ej Magnetization curves, hysteresis, Barkhausen and related effects
75.40.Cx Static properties (order parameter, static susceptibility, heat capacities, critical exponents, etc.)

First order approximation for interactions in particulate single-domain particle systems

Dorin Cimpoesu, Petronel Postolache, and Alexandru Stancu

J. Appl. Phys. 93, 6644 (2003); http://dx.doi.org/10.1063/1.1557700 (3 pages) | Cited 5 times

Online Publication Date: 9 May 2003

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In most cases the interparticle interactions are essential in the evaluation of the magnetic properties of the ferromagnetic particulate systems. Usually, in first approximation, a mean interaction field linearly dependent on the magnetic moment of the sample is considered and other interactions are neglected. Using micromagnetic simulations on a system of interacting uniaxial single-domain particles we have shown that both the mean interaction field and interaction fields distribution dispersion depend on the magnetic moment of the sample. When the magnetic moment of the sample is small the statistical interactions are more important than the mean field ones and cannot be neglected. © 2003 American Institute of Physics.
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75.50.Tt Fine-particle systems; nanocrystalline materials
75.40.Mg Numerical simulation studies
75.60.Ej Magnetization curves, hysteresis, Barkhausen and related effects
75.60.Ch Domain walls and domain structure

Numerical modelling in the time domain of dynamic hysteresis of soft materials in cylindrical coordinates

Ermanno Cardelli, Edward Della Torre, and Enrico Pinzaglia

J. Appl. Phys. 93, 6647 (2003); http://dx.doi.org/10.1063/1.1557701 (3 pages) | Cited 1 time

Online Publication Date: 9 May 2003

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This paper deals with the numerical analysis of soft magnetic materials with hysteresis in dynamic axial symmetric problems. We present a procedure based on a 1D Finite Difference Time Domain (FDTD) algorithm where there are implemented magnetization dependent Preisach based models. Experimental measurements of the virgin curve and the major loop are used to identify the models. The numerical scheme in the time domain proposed is discussed and a probe of its intrinsic stability is given. Numerical codes based on the above algorithm are used to show some of the possibilities of this numerical tool for the dynamic magnetic analysis. © 2003 American Institute of Physics.
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75.40.Mg Numerical simulation studies
75.60.Ej Magnetization curves, hysteresis, Barkhausen and related effects
02.70.Bf Finite-difference methods

Computing the surface impedance in nonlinear materials with hysteresis

F. Bertoncini, E. Cardelli, S. Di Fraia, and B. Tellini

J. Appl. Phys. 93, 6650 (2003); http://dx.doi.org/10.1063/1.1557711 (3 pages) | Cited 3 times

Online Publication Date: 9 May 2003

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A numerical model in time domain for describing the energetic magnetic behavior of hysteretic materials is here proposed. Parallelogram shaped hysteresis loops have been used for simplifying the calculation. Equivalent major loops have been defined starting from the measured ones. Measurements have been done in our laboratory on different magnetic material cores. Both soft Mn–Zn ferrites and not oriented magnetic irons have been tested. Comparison with other numerical procedures based either on rectangular shaped hysteresis loops, or on the implementation of a scalar Preisach model is presented and discussed. © 2003 American Institute of Physics.
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75.40.Mg Numerical simulation studies
75.50.Gg Ferrimagnetics
75.60.Ej Magnetization curves, hysteresis, Barkhausen and related effects
75.70.Rf Surface magnetism

Modeling the irreversible response within the ferromagnetic phase of La0.7Sr0.3MnO3

R. M. Roshko and L. Xi

J. Appl. Phys. 93, 6653 (2003); http://dx.doi.org/10.1063/1.1557360 (3 pages) | Cited 3 times

Online Publication Date: 9 May 2003

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The magnetic response of a ferromagnetically ordered perovskite La0.7Sr0.3MnO3 with a critical temperature TC=325 K has been measured as a function of applied field ha over the interval −4 kOe⩽ha⩽+4 kOe, and as a function of temperature T over the interval 5 K⩽T⩽350 K which spans the ordered phase, and analyzed within the framework of a model which reduces all magnetic systems to an ensemble of temperature dependent, asymmetric double well subsystems. The model is able to replicate the field and temperature dependence of the measured zero field cooled moment, the field cooled moment, the isothermal remanent moment, the thermoremanent moment, the initial magnetizing curve, the magnetizing remanence, the major hysteresis loop, and the demagnetizing remanence, and yields the spectrum of double well dissipation barriers and level splittings which represent the Barkhausen excitations between metastable domain configurations. © 2003 American Institute of Physics.
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75.40.Mg Numerical simulation studies
75.60.Ej Magnetization curves, hysteresis, Barkhausen and related effects
75.47.Gk Colossal magnetoresistance
75.47.Lx Magnetic oxides
75.50.Dd Nonmetallic ferromagnetic materials
75.30.Kz Magnetic phase boundaries (including classical and quantum magnetic transitions, metamagnetism, etc.)
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