Abstract Spin-Hall oscillators (SHO) are promising sources of spin-wave signals for magnonics applications, and can serve as building blocks for magnonic logic in ultralow power computation devices. Thin magnetic layers used as “free” layers in SHO are in contact with heavy metals having large spin-orbital interaction, and, therefore, could be subject to the spin-Hall effect (SHE) and the interfacial Dzyaloshinskii-Moriya interaction ( i -DMI), which may lead to the nonreciprocity of the excited spin waves and other unusual effects. Here, we analytically and micromagnetically study magnetization dynamics excited in an SHO with oblique magnetization when the SHE and i -DMI act simultaneously. Our key results are: (i) excitation of nonreciprocal spin-waves propagating perpendicularly to the in-plane projection of the static magnetization; (ii) skyrmions generation by pure spin-current; (iii) excitation of a new spin-wave mode with a spiral spatial profile originating from a gyrotropic rotation of a dynamical skyrmion. These results demonstrate that SHOs can be used as generators of magnetic skyrmions and different types of propagating spin-waves for magnetic data storage and signal processing applications.
A new three-dimensional Finite Elements procedure for the analysis of electron guns inside TWT is presented, illustrating its main features. In this procedure cathodic emission is modeled according to Child?s law, operating in space charge limited mode. Corrections taking into account cathode geometric shape and relativistic beams are considered allowing us to obtain accurate evaluation of emission currents from the knowledge of the field distribution near the cathode. Electron trajectories are obtained by solving a Vlasov-Poisson system of equations together with the relativistic dynamical equations of motion. This coupled electro-mechanical problem is solved iteratively by assuming stationary conditions. In the analysis an external magnetic field can also be introduced in order to obtain a better focalization of the electron beam.
In this paper, the problem of estimating the core losses for inductive components is addressed. A novel methodology is applied to estimate the core losses of an inductor in a DC-DC converter in the time-domain. The methodology addresses both the non-linearity and dynamic behavior of the core magnetic material and the non-uniformity of the field distribution for the device geometry. The methodology is natively implemented using the LTSpice simulation environment and can be used to include an accurate behavioral model of the magnetic devices in a more complex lumped circuit. The methodology is compared against classic estimation techniques such as Steinmetz Equation and the improved Generalized Steinmetz Equation. The validation is performed on a practical DC-DC Buck converter, which was utilized to experimentally verify the results derived by a model suitable to estimate the inductor losses. Both simulation and experimental test confirm the accuracy of the proposed methodology. Thus, the proposed technique can be flexibly used both for direct core loss estimation and the realization of a subsystem able to simulate the realistic behavior of an inductor within a more complex lumped circuit.
Power converters often features inductive devices in their architectures. Accurate simulation of the converters requires a well-defined response of the magnetic cores. A computationally efficient approach for the numerical modelling of hysteretic magnetic materials is presented in this work. The approach exploits the simplicity of the identification procedure for the Preisach model of hysteresis and the reduced computational costs of Neural Networks. The model for hysteresis is implemented both in direct and inverse form. Validation is performed against independent dataset, with evident computational speedup, which can be a valuable asset for magnetic cores simulations in the design of complex power systems featuring multiple converters such as the ones used in avionic applications.
This Letter studies the dynamical behavior of spin-Hall nanoscillators from a micromagnetic point of view. The model parameters have been identified by reproducing recent experimental data quantitatively. Our results indicate that a strongly localized mode is observed for in-plane bias fields such as in the experiments, while predict the excitation of an asymmetric propagating mode for large enough out-of plane bias field similarly to what observed in spin-torque nanocontact oscillators. Our findings show that spin-Hall nanoscillators can find application as spin-wave emitters for magnonic applications where spin waves are used for transmission and processing information on nanoscale.
Electron guns are used as electron beam source in a wide variety of devices including traveling wave tubes (TWT), klystrons and particle accelerators. Usage of more complex geometries and insertion of control grid allow the designer to obtain a better performance but it requires specialized 3D numerical simulators to carry out the design process. In this paper we present the COLLGUN simulator, a 3D tool for the design of TWT's electron gun. The complete simulator consists of three main modules: a dedicated fully 3D Finite Element mesh generator, a 3D FE Vlasov solver, including space-charge effects, with an integrated electron trajectory tracer and a graphic post-processing module for result restitution. Several examples of 3D simulation of electron guns have been analyzed to test the simulator.
The present work documents the study on the usage of Neural Networks to compute the parameters used in solar panel modelling. The approach followed starts from a dataset obtained by a process of model identification via numerical solution of nonlinear equations. After a preliminary analysis pointing out the intrinsic difficulty in the classic identification of the parameters via NN, by taking advantage of closed form relations, a hybrid neural system, composed by neural network based identifiers and explicit equations, was implemented. The generalization capabilities of the neural identifier were investigated, showing the effectiveness of this approach.
