A detailed crystal-field analysis, based on the Racah' theory, was carried out for the so-called A, B and G1 isolated charge-compensation centers of Er3+ ion doped in CaF2 crystal. Three sets of crystal-field parameters were obtained by a least-squares fitting of the optical data of Er3+ ion diluted in epitaxial Ca1−xErxF2+x thin film. This theoretical analysis confirms the expected $C_{4\nu}$ site symmetry for the A center and the $C_{3\nu}$ site symmetry for the G1 center. For the B center, however, the site symmetry is not exactly $C_{3\nu}$ in contrast to what is believed.

Charge diffusion in thin ${\rm Al}_2{\rm O}_3$ layers has been investigated by Atomic Force Microscopy (AFM). The layers were made by anodic oxidation of Al plates, in order to obtain plane and homogeneous amorphous oxides of known thicknesses. Under dry-nitrogen atmosphere, the charges are deposited by contact electrification: a deposit voltage is applied between the Al substrate of the layer and the metallized AFM tip brought to contact with the oxide. This process is perfectly controllable and reproducible, the quantity of charges deposited being proportional to the deposit voltage. Afterwards the tip is lifted up and scans the surface of the oxide in order to observe the diffusion of the deposited charges. Two behaviors were observed for the diffusion process depending on the thickness and on the deposit voltage. These results are interpreted by introducing an inhomogeneous trap distribution in the layer, the diffusion process being considered mainly as diffusion by hopping transport in the bulk.

The toroidal technique is used in the determination of the complex, frequency dependent magnetic susceptibility, $\chi (\omega) = \chi'(\omega) - {\rm i} \chi''(\omega)$, of four magnetic fluids consisting of colloidal suspensions of magnetite in water with corresponding saturation magnetisation of 134 G, 107 G, 90 G and 30 G. Plots of the susceptibility components against f (Hz) over the frequency range 10 Hz to 1 MHz, are shown to have approximate Debye-type profiles with the presence of Brownian relaxation being indicated by the frequency, fmax, of the maximum of the loss-peak in the $\chi''(\omega)$ profiles. Corresponding calculations of particle hydrodynamic radius indicate the presence of aggregation. An estimate of the aggregate size distribution in the samples is determined by fitting the measured susceptibility profiles to susceptibility profiles generated by the Debye equations modified by Frohlich, Cole-Cole, Normal and Lognormal distribution functions. The fits obtained from the four fitting functions are found to be similar and thus it is concluded that none of these functions offers any particular advantage over the other functions.

On the basis of one-dimensional paracrystalline model, we have calculated the linear disorder when oligonucleotide single crystals of DNA are irradiated by X-rays. For this purpose, the noticeable broadening of the meridional reflection at 3.2 Å was used as a marker to quantify the disorder, induced in the linear array of base pairs as one travels along the helical axis of DNA molecule.

An electrodynamic field is coupled to a magnetic equivalent circuit. The electrodynamic problem is formulated by the electric vector potential and discretised by finite elements. The magnetic lumped parameter model is described in terms of unknown fluxes and magnetomotive forces. The coupled system matrix has a mixed and hybrid nature. In this presentation, the method is applied to simulate eddy current distributions in laminated material and losses in a dielectric heater.

The paper presents the application of Radial-basis-function (RBF) neural networks to speed up deterministic search algorithms used for the design and optimization of superconducting LHC magnets. The optimization of the iron yoke of the main dipoles requires a number of numerical field computations per trial solution as the field quality depends on the excitation of the magnets. This results in computation times of about 30 minutes for each objective function evaluation (on a DEC-Alpha 600/333) and only the most robust (deterministic) optimization algorithms can be applied. Using a RBF function approximator, the achieved speed-up of the search algorithm is in the order of 25% for problems with two parameters and about 18% for problems with three and five design variables.

In a finite element code using magnetic vector potential as unknown, the fixed point method needs the relationship which gives the magnetic field H from the magnetic flux density B. In this paper, we present two methods to obtain the magnetic behaviour H(B) of a ferromagnetic material. The first uses centred cycles to calculate directly the inverse Preisach model. The second uses the Regula-Falsi method and the classical direct Preisach model (where B, H, and M are collinear). We conclude giving some elements of comparison.

This paper deals with the solution of linear inverse problems in magnetostatics. The case the authors have broached is finding the current density on the basis of magnetic field values. Solving this kind of equation is an ill-posed problem. Exact magnetic field values and measured values lead to different cases, each of which is presented. To solve them, the authors use the conjugate gradient method with iterative regularization. They present numerical results for the design of magnets, gradient and shim coils, and numerical results for the problem of recovering current density values from measured field values.

This search deals with the control of a process in order to take into account non linearities without parameters identification. Neural networks properties are exploited for the modelling of non linear features, and a formalism is proposed to design a neural model which can be used directly as a controller. We apply this formalism to the modelling of a non linear mechanical load torque feature coupled to an induction machine in order to design a speed controller. A partial and a global neural method are presented. In order to overcome modelling errors or any process changes, an adaptive on line method is proposed. At last, simulation and experimental results are presented.

In this paper, the stochastic magnetic field lines diffusion is studied. The stochastic behavior of the magnetic field lines is described by the generalized mapping to the second order which is derived from the magnetic field lines equations. The diffusion coefficient is calculated analytically using the Fourier paths technique and the characteristic function formalism. Both, they give exactly the same result of the diffusion coefficient. A numerical determination of the diffusion coefficient is also done.