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Millimeter wave components, such as circulators and isolators, frequently use magnetic fields to break symmetry of the signal propagation and provide unidirectional signal transmission. While effective, these components have not seen the level of miniaturization of other millimeter wave components, primarily due to the discrete nature of the magnets used in the components. Using circulators in the 40-50 GHz range as a motivating application, requirements arise for the deposited films, namely immunity to eddy currents, sufficient magnetization to act as self-biasing magnets, and out-of-plane orientation of the self-biasing field. Based on these required properties, hexaferrite materials are selected for their strong magnetocrystalline anisotropy (MCA) and low conductance. The difficulty of integrating these components monolithically with monolithic microwave integrated circuits (MMIC) originates from the incompatibility of crystal structure with standard semiconductor materials and process conditions. Additive manufacturing using a composite of strontium hexaferrite (SrFe12O19) particles and photoresist has been chosen as a method to overcome the difficulties of integrating hexaferrite material to semiconductor substrates. Due to their large internal anisotropy field, the particles of strontium hexaferrite tend to rotate to the field direction instead of changing magnetization direction under application of an external magnetic field (less than the anisotropy field). We have developed a method for 3D printing composites of high strontium hexaferrite concentration (up to 20% by volume) in a liquid photoresist, SU8. Rotation of hexaferrite particles in polymer matrix and thus magnetic anisotropy has been demonstrated in the composite, which is subsequently cured to hold the physical position and orientation of the particles. The anisotropy of the self-biasing field provided by the films has been experimentally characterized, and a ferromagnetic resonance (FMR) frequency ~43 GHz has been observed. We have also characterized the viscosity of the particle-laden polymer at different particle concentrations. 3D printing of this composite with poling will make it possible to directly print magnetic components that require out-of-plane anisotropic magnetization.

Magnetic circuit components have long been the largest and most difficult components to miniaturize. Printed circuit board (PCB) fabrication methods cannot achieve small diameter, high aspect-ratio vias for high winding turn numbers to achieve high inductance, and microelectronics methods cannot achieve the high-quality and thick ferrite core materials. In this paper, we present an alternative breakthrough method of printed circuit fabrication to significantly reduce the effective via diameter for embedded magnetic devices, boosting the inductance per unit area. To reduce the effective via diameter, high-density via plugs are ex-situ fabricated and shaped, and then embedded into PCB substrate in the same process as standard magnetic core embedding. The structure of the plug is such that precise placement within the substrate, or alignment to the plug with the winding pattern, is not necessary. Devices presented in this paper use via plugs with an effective diameter of 40 μm and a theoretically unlimited aspect ratio, though refinements in the plug fabrication process are expected to reduce the via diameter down to 10μm. The process is experimentally demonstrated with a 14-turn racetrack shaped transformer; novel diagnostic methods using magneto-optic garnet films to image current paths are also demonstrated.

In this article, an approach combining semi-empirical equations and the method of images is proposed for round conductor layer windings with un-gapped core. The new equation for proximity effect can convert the constant field strength from the magneto-motive force (MMF) across the core window into a frequency-dependent uniform background magnetic field strength, which can take partly the interaction between conductors into account. Geometric factors are introduced by fitting the finite element method (FEM) results to improve the accuracy. The method of images is used to calculate the field strength in order to counteract the impact of the 2-D edge effect. The new method is compared with the 2-D FEM, analytical methods, and is also validated by measurements with EE core transformers. The proposed method shows good accuracy (< 10% error) compared with 2-D FEM for both high and low porosity factor windings. Therefore, it can handle more winding configurations than other 1-D analytical methods.

This paper proposes two novel methods for upscaling the macroscopic magnetic field strength from the local solutions of B-conforming magnetoquasistatic multiscale problems. Unlike the volume average method classically used, these methods yield accurate values of the macroscale magnetic field for problems with strong locally-confined eddy currents which enables B-conforming multiscale formulations of eddy currents problems at higher frequencies. acceptedVersion

Power cables have complex geometries in order to reduce their AC resistance. The cross-section of a cable consists of several conductors that are electrically insulated from each other to counteract the current displacement caused by the skin effect. Furthermore, the individual conductors are twisted over the cable's length. This geometry has a non-standard symmetry - a combination of translation and rotation. Exploiting this property allows formulating a dimensionally reduced boundary value problem. Dimension reduction is desirable, otherwise the electromagnetic modeling of these cables becomes impracticable due to tremendous computational efforts. We investigate 2D eddy current boundary value problems which still allow the analysis of 3D effects, such as the twisting of conductor layers., 4 pages, 6 figures

International audience; This paper proposes a circuit model to calculate the current along printed coils used in Resonant Wireless Power Transfer. It considers a system composed of a metamaterial and two coplanar coils, transmitter and receiver, respectively. First, a circuit model for the system is presented. Then, an analytical model is proposed to calculate the self-inductance of printed inductors, their characteristic resistance, and the mutual inductance between coils. The proposed formulation for calculating the mutual inductance between inductors is based on Neumann’s formula. The practical results validate the model precision, obtaining a maximum deviation of approximately 8%, 3%, and 3%, respectively. Due to the generality of this approach, it can also be applied to more complex structures such as metasurfaces. The proposed 3-D models proved to be ideal for modeling the printed inductor. Furthermore, this model proved to be computationally more efficient for analyzing large systems when compared to commercial full-wave simulation software, with a reduction in the computational time larger than three orders of magnitude.

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This study proposes a novel topology optimization (TO) method for permanent magnet (PM) motors based on a variational autoencoder (VAE) and a neural network (NN). The VAE is trained to embed various shapes generated from the TO into the latent space. The NN is trained to predict the characteristics of the PM motor from its latent representation derived using the VAE. After training, TO is performed in the latent space based on the prediction using the NN. We adopt the Monte Carlo dropout to maintain prediction reliability using the NN during optimization, where prediction deviation is evaluated and used to eliminate unreliable solutions. The proposed method yields Pareto solutions within 80 s in a single-thread CPU machine, which is considerably faster than numerical analysis-based optimization, such as finite-element analysis.