122 citations · 237 across the 9 of their papers we have counts for
9 papers
Modelling magnetic material properties with uncertainty-aware neural networks
Clemens Wager, Heisam Moustafa, Alexander Kovacs +10
Machine learning is increasingly used to accelerate materials discovery across large compositional and structural design spaces, but limited and heterogeneous data make reliable un…
Impact of Lattice Distortions on Magnetocrystalline Anisotropy and Magnetization in (NdPr)FeB Alloys
Haruki Okumura, Takashi Miyake, Taro Fukazawa +6
NdFeB -- a widely used permanent magnet -- has magnetocrystalline anisotropy constants that differ between the bulk and interface regions. This study explores the effe…
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…
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…
Data Assimilation Method for Experimental and First-Principles Data: Finite-Temperature Magnetization of (Nd,Pr,La,Ce)(Fe,Co,Ni)B
Yosuke Harashima, Keiichi Tamai, Shotaro Doi +8
We propose a data-assimilation method for evaluating the finite-temperature magnetization of a permanent magnet over a high-dimensional composition space. Based on a general framew…
Optimal uni-axial ferromagnetism in (La,Ce)FeB for permanent magnets
Munehisa Matsumoto, Masaaki Ito, Noritsugu Sakuma +3
Prospects for light-rare-earth-based permanent magnet compound RFeB (R=LaCe with ) are inspected from first principles referring to the lat…
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…
Grain-size dependent demagnetizing factors in permanent magnets
Simon Bance, Bernhard Seebacher, Thomas Schrefl +10
The coercive field of permanent magnets decreases with increasing grain size. The grain size dependence of coercivity is explained by a size dependent demagnetizing factor. In Dy f…