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In this work, Artificial Neural Network was used to model the hysteresis behavior of lead zirconate titanate-lead zinc niobate (Pb(Zr1/2Ti1/2)O3−Pb(Zn1/3Nb2/3)O3or (1-x)PZT-(x)PZN mixed ferroelectric systems. The hysteresis loops were measured with varying electric filed parameters and the composition x of the mixed ferroelectrics. A knowledge-based technique, i.e. the Artificial Neural Network (ANN), was employed in modeling the hysteresis to construct the database of how field parameters and the mixed composition affect dynamic hysteresis behavior. The input data to the ANN were composition x, field amplitude E0and field frequency f, where the output data was the hysteresis area. The inputs-outputs were divided into training, validating and testing datasets for the ANN. Multilayer perceptron with back propagation training algorithm was applied in this work. Exhaustive search was used to obtain the best network algorithm that gives minimum error in the training process. With the best network, unseen input datasets were fed into the network to predict hysteresis area. From the results, the predicted and the actual data match very well over an extensive range of field parameters, where the scattering plot between the predicted and the actual area has R-squared greater than 0.99. This therefore indicates ANN capabilities in modeling dynamic-hysteresis phenomena across (1-x)PZT-(x)PZN systems even they have different ratios of structural phases at microscopic level. [ABSTRACT FROM PUBLISHER]

Ferromagnetic hysteresis behavior is a lagging relation between magnetization and external magnetic field. This understanding is useful for designing highly efficient magnetic applications e.g., magnetic recording devices. A magnetic phase and hysteresis properties fluctuate clearly when encountered with thermal noise. This creates difficulties in predicting and modeling; and poses a very challenging problem. In this study, we propose to fit parameters and select the suitable kernel functions of Support Vector Machine, of which the main tasks are i) managing the relationship among hysteresis properties, temperature, magnetic field, and magnetic frequency, and ii) classifying the symmetries of hysteresis. The results present a new novel of classifying symmetric behavior of hysteresis with high accuracy. [ABSTRACT FROM AUTHOR]

In this work, the Preisach technique was employed to characterize temperature dependent hysteresis loops extracted from the Ising model considered under the mean-field (MF) framework. In constructing the Preisach densities for these MF loops, a stochastic process was used to optimize the hysterons’ weight. Then, from the obtained Preisach densities, series of the MF hysteresis loops were accurately re-constructed, and the temperature independence of densities was observed. In addition, an increase of reversible polarization and a decline of irreversible polarization with increasing temperature were evident. These phenomena were examined and found to be caused by the enhancement of thermal fluctuation at higher temperature, which alleviates the spin flipping viscosity and lessens the phase-lag in hysteresis characteristic. [ABSTRACT FROM AUTHOR]

In this work, Monte Carlo simulation was used to study the size dependence of the dynamic hysteresis properties of 2 dimensional ferroelectric system. The DIFFOUR model and Metropolis algorithm were used to investigate the size effect on hysteresis properties. From the simulation, it was found that the competition between the electric field parameters and the system size plays a crucial role on the phase-lag between the polarization and the electric field signals, which defines particular hysteresis properties. In describing the hysteresis behavior qualitatively, finite size scaling formalism, in a power law form, was used to predict relations among the field parameters, system size, and hysteresis. The purpose was to establish phenomenological knowledge of how dynamic perturbations affect the hysteresis in finite ferroelectric system. Comparison with related experiments was also discussed. [ABSTRACT FROM PUBLISHER]

In this work, the effect of random vacancy defects on the electrical properties of ferroelectric thin-films was studied. The Monte Carlo simulation, based on the ferroelectric DIFFOUR model, was performed in the lattice system with free and periodic boundary conditions. The Metropolis algorithm was considered in choosing the proper states under the presence of the electric field. From the results, the hysteresis area at a given field was found to depend on the thickness of thin films and the vacancy defects of system. For instance, in thicker films, the larger hysteresis area was observed, which is resulted from the stronger ferroelectric interaction. On the other hand, the hysteresis area decreases with increasing vacancy concentration, due to the reduction of ferroelectric interaction on the average. To understand the hysteresis behaviors, the scaling exponents of associated parameters in the power law scaling form were considered. The results were discussed and compared with these from literatures. [ABSTRACT FROM AUTHOR]

This paper proposed an application of Artificial Neural Network (ANN) to concurrently model ferroelectric hysteresis properties of Barium Titanate in both single-crystal and bulk-ceramics forms. In the ANN modeling, there are 3 inputs, which are type of materials (single or bulk), field amplitude and frequency, and 1 output, which is hysteresis area. Appropriate number of hidden layer and hidden node were achieved through a search of up to 2 layers and 30 neurons in each layer. After ANN had been properly trained, a network with highest accuracy was selected. Query file of unseen input data was then input to the selected network to obtain the predicted hysteresis area. From the results, the target and predicted data were found to match very well. This therefore suggests that ANN can be successfully used to concurrently model ferroelectric hysteresis property even though the considered ferroelectrics are with different domains, grains and microscopic crystal structures. [ABSTRACT FROM AUTHOR]

In this study, the artificial neural network (ANN) was used to model ferromagnetic Ising hysteresis obtained from mean-field analysis as a case study. ANNs were trained to predict the effect of external perturbations, which are the temperature, the field amplitude and the field frequency, on the hysteresis properties, which are the hysteresis area, the remanence magnetization and the coercivity. The input data to the ANN were split into training data, testing data and validating data. Search were carried out to identify number of hidden layer and number of hidden nodes to find the best architecture with highest accuracy. After the networks had been trained, they were used to predict hysteresis properties of the unseen testing patterns of input. The predicted and the actual data were found to match very well over an extensive range. This therefore suggests a success in modeling ferromagnetic hysteresis properties using the ANN technique. [ABSTRACT FROM AUTHOR]

In this work, Monte Carlo simulation was used to model the ferroelectric behavior of mixed normal and relaxor ferroelectrics using the single polarization-flip algorithm. The purpose is to investigate the dependence of ferroelectric properties on the field frequency, the temperature and the normal ferroelectric concentration in the relaxor ferroelectrics. Results obtained from both static and dynamic simulation stress the significant effect of the larger ferroelectric interaction caused by the normal ferroelectric contents. For instance, with increasing normal ferroelectric concentrations, the transition between zero and nonzero polarization phases shifts to a higher temperature due to stronger ferroelectric interaction. In addition, the stronger ferroelectric interaction also causes less polarization switching, where the hysteresis gets larger in size at low frequencies, but smaller at high frequencies. This strong ferroelectric interaction also shifts the frequency at maximum phase-lag between polarization and field signal to a lower frequency. These results are in good agreement with experiments, where applicable. [ABSTRACT FROM AUTHOR]

Effects of electric field-frequency, electric field-amplitude, and mechanical stress on the hysteresis area were investigated on soft PZT ceramic. At stress-free condition, the investigation found the area scales with frequency and field-amplitude in power-law form, 〈A〉 ∝ ƒ-0.25 E0; however, with different set of exponents in comparing to those in the investigation on thin films structure. On the other hand, with compressive stresses turning on, the same set of the exponents with the stress-free condition is found to confirm universality. In addition, the scaling form of the area to triple parameters; i.e., frequency, field-amplitude, and stress in a power law form, 〈A〉 - 〈Aσ = 0〉 = 〈 A - Aσ = 0〉 ∝ ƒ- 0.25 E0 σ0.44, was obtained. [ABSTRACT FROM AUTHOR]

Abstract: In this work, Monte Carlo simulation was used to model the dynamic hysteresis behavior of ferromagnetic Ising thin-films using the spin-flip algorithm. The purpose is to investigate the thickness dependence of ferromagnetic hysteresis properties while varying frequency and amplitude of the external field. From the results, with increasing the films thickness, the calculated hysteresis properties significantly change due to the stronger ferromagnetic coupling in thicker films. In addition, the universal power law relations among the hysteresis properties, the thickness and the field parameters were found. The scaling exponents were also reported which agree well with a previous experiment on ferromagnetic thin-films. [Copyright &y& Elsevier]

The effects of frequency f, field amplitude E0, and mechanical stress σ on the hysteresis area and their scaling relations were investigated on soft PZT bulk ceramics. The hysteresis area was found to depend on the frequency and field amplitude with a same set of exponents to the power-law scaling for both with and without stresses, indicating the universality. The inclusion of stresses into the power law was also obtained in the form of ≤A-Aσ=0>∝f-0.25E0σ0.44, which indicates the difference of the energy dissipation between the under stress and stress-free conditions and reveals how the hysteresis area decays with increasing stresses [ABSTRACT FROM AUTHOR]

Abstract: In this study, the magnetic hysteresis properties of the Ising model in an oscillating external magnetic field were evaluated using mean field analysis. The average magnetization over a full oscillating field-cycle, as a function of the field amplitude, field frequencies and temperature, was investigated. The dynamic phase transition boundaries between the dynamic ferromagnetic and paramagnetic phases were defined on the field amplitude and temperature plane for each field frequency, in order to study the effect of frequency on the hysteresis dynamic phase transition. For the results, the hysteresis behaviors across the dynamic phase transition boundary were observed using varying field frequencies. The frequency dispersion of the hysteresis area, the remanence and the coercivity were categorized into three distinct types. These phenomena can be explained through an understanding of the role of frequency in the alteration of the dynamic phase boundaries, something which results in anomalous hysteresis properties as a function of frequency. [Copyright &y& Elsevier]