110 citations · 582 across the 25 of their papers we have counts for
26 papers
Tailoring the material properties, nanostructure and grain alignment of Alnico magnets through micromagnetic simulations
Anda Elena Stanciu, Johann Fischbacher, Markus Gusenbauer +9
Alnico magnets have gained renewed interest in the search for rare-earth free permanent magnets due to their high thermal stability and magnetisation. However, the limited coercivi…
Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures
Heisam Moustafa, Alexander Kovacs, Johann Fischbacher +5
Graph neural networks (GNN) are a promising tool to predict magnetic properties of large multi-grain structures, which can speed up the search for rare-earth free permanent magnets…
FORC Diagram Features of Co Particles due to Reversal by Domain Nucleation
Leoni Breth, Johann Fischbacher, Alexander Kovacs +7
First Order Reversal Curve (FORC) diagrams are a popular tool in geophysics and materials science for the characterization of magnetic particles of natural and synthetic origin. Ho…
Description of collective magnetization processes with machine learning models
Alexander Kornell, Lukas Exl, Leoni Breth +11
This work introduces a latent space method to calculate the demagnetization reversal process of multigrain permanent magnets. The algorithm consists of two deep learning models bas…
Exploring the hysteresis properties of nanocrystalline permanent magnets using deep learning
Alexander Kovacs, Lukas Exl, Alexander Kornell +11
We demonstrate the use of model order reduction and neural networks for estimating the hysteresis properties of nanocrystalline permanent magnets from microstructure. With a data-d…
Full-Spin-Wave-Scaled Finite Element Stochastic Micromagnetism: Mesh-Independent FUSSS LLG Simulations of Ferromagnetic Resonance and Reversal
Harald Oezelt, Luman Qu, Alexander Kovacs +11
In this paper, we address the problem that standard stochastic Landau-Lifshitz-Gilbert (sLLG) simulations typically produce results that show unphysical mesh-size dependence. The r…
Magnetostatics and micromagnetics with physics informed neural networks
Alexander Kovacs, Lukas Exl, Alexander Kornell +8
Partial differential equations and variational problems can be solved with physics informed neural networks (PINNs). The unknown field is approximated with neural networks. Minimiz…
Conditional physics informed neural networks
Alexander Kovacs, Lukas Exl, Alexander Kornell +11
We introduce conditional PINNs (physics informed neural networks) for estimating the solution of classes of eigenvalue problems. The concept of PINNs is expanded to learn not only…
Microstructure Role in Permanent Magnet Eddy Current Losses
Salvatore Perna, Thomas Schrefl, Claudio Serpico +2
The impact of granular microstructure in permanent magnets on eddy current losses are investigated. A numerical homogenization procedure for electrical conductivity is defined. The…
Extracting local switching fields in permanent magnets using machine learning
Markus Gusenbauer, Harald Oezelt, Johann Fischbacher +4
Microstructural features play an important role for the quality of permanent magnets. The coercivity is greatly influenced by crystallographic defects, which is well known for MnAl…
Computational Design of the Rare-Earth Reduced Permanent Magnets
A. Kovacs, J. Fischbacher, M. Gusenbauer +6
Multiscale simulation is a key research tool for the quest for new permanent magnets. Starting with first principles methods, a sequence of simulation methods can be applied to cal…
Micromagnetics of rare-earth efficient permanent magnets
Johann Fischbacher, Alexander Kovacs, Markus Gusenbauer +4
The development of permanent magnets containing less or no rare-earth elements is linked to profound knowledge of the coercivity mechanism. Prerequisites for a promising permanent…
Learning magnetization dynamics
Alexander Kovacs, Johann Fischbacher, Harald Oezelt +5
Deep neural networks are used to model the magnetization dynamics in magnetic thin film elements. The magnetic states of a thin film element can be represented in a low dimensional…
Magnetic microstructure machine learning analysis
Lukas Exl, Johann Fischbacher, Alexander Kovacs +6
We use a machine learning approach to identify the importance of microstructure characteristics in causing magnetization reversal in ideally structured large-grained NdFe$_{14}…
Probability distribution of substituted Titanium in RT12 (R = Nd, Sm, T = Fe, Co) structures
Connor Skelland, Thomas Ostler, Samuel Westland +11
We investigated the atomic fill site probability distributions across supercell structures of RT12-xTi (R=Nd, Sm, T=Fe, Co). We use a combined molecular dynamics and Boltzmann dist…
Tuning magnetocrystalline anisotropy of FeSn by alloying
Olga Yu. Vekilova, Bahar Fayyazi, Konstantin P. Skokov +8
The electronic structure, magnetic properties and phase formation of hexagonal ferromagnetic FeSn-based alloys have been studied from first principles and by experiment. The…
Preconditioned nonlinear conjugate gradient method for micromagnetic energy minimization
Lukas Exl, Johann Fischbacher, Alexander Kovacs +3
Fast computation of demagnetization curves is essential for the computational design of soft magnetic sensors or permanent magnet materials. We show that a sparse preconditioner fo…
On the limits of coercivity in permanent magnets
J. Fischbacher, A. Kovacs, H. Oezelt +14
The maximum coercivity that can be achieved for a given hard magnetic alloy is estimated by computing the energy barrier for the nucleation of a reversed domain in an idealized mic…
Transition Jitter in Heat Assisted Magnetic Recording by Micromagnetic Simulation
Harald Oezelt, Alexander Kovacs, Johann Fischbacher +3
In this paper we apply an extended Landau-Lifschitz equation, as introduced by Baňas et al. for the simulation of heat-assisted magnetic recording. This equation has similarities w…
Micromagnetic Simulations for Coercivity Improvement through Nano-Structuring of Rare-Earth Free L1-FeNi Magnets
Alexander Kovacs, Johann Fischbacher, Harald Oezelt +6
In this work we investigate the potential of tetragonal L1 ordered FeNi as candidate phase for rare earth free permanent magnets taking into account anisotropy values from rece…
Switching field distribution of exchange coupled ferri-/ferromagnetic composite bit patterned media
Harald Oezelt, Alexander Kovacs, Johann Fischbacher +6
We investigate the switching field distribution and the resulting bit error rate of exchange coupled ferri-/ferromagnetic bilayer island arrays by micromagnetic simulations. Using…
Thermal activation in permanent magnets
Simon Bance, Johann Fischbacher, Alexander Kovacs +3
The coercive field of permanent magnets decays with temperature. At non-zero temperature the system can overcome a finite energy barrier through thermal fluctuations. Using finite…
Numerical optimization of writer geometries for bit patterned magnetic recording
A. Kovacs, H. Oezelt, S. Bance +6
A fully-automated pole-tip shape optimization tool, involving write head geometry construction, meshing, micromagnetic simulation and evaluation, is presented. Optimizations have b…
Micromagnetics of shape anisotropy based permanent magnets
Simon Bance, Johann Fischbacher, Thomas Schrefl +3
In the search for rare-earth free permanent magnets, various ideas related to shape anisotropy are being pursued. In this work we assess the limits of shape contributions to the re…