Showing physics.comp-phShow all
2 papers · 1 filter
physics.comp-ph2025
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…
physics.comp-ph2024
Physics aware machine learning for micromagnetic energy minimization: recent algorithmic developments
Sebastian Schaffer, Thomas Schrefl, Harald Oezelt +2
In this work, we explore advanced machine learning techniques for minimizing Gibbs free energy in full 3D micromagnetic simulations. Building on Brown's bounds for magnetostatic se…