5 papers
Modelling magnetic material properties with uncertainty-aware neural networks
Clemens Wager, Heisam Moustafa, Alexander Kovacs +10
Machine learning is increasingly applied to accelerate the discovery of novel materials by exploring large compositional and structural design spaces. Yet, the scarcity of high-qua…
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…
Modeling liquid-mediated interactions for close-to-substrate magnetic microparticle transport in dynamic magnetic field landscapes
Markus Gusenbauer, Rico Huhnstock, Alexander Kovacs +3
Understanding the on-chip motion of magnetic particles in a microfluidic environment is key to realizing magnetic particle-based Lab-on-a-chip systems for medical diagnostics. In t…
Effect of interface on magnetic exchange coupling in Co/Ru/Co trilayer: from ab-initio simulations to micromagnetics
Sergiu Arapan, Jan Priessnitz, Alexander Kovacs +5
Interfaces play a substantial role for the functional properties of structured magnetic materials and magnetic multilayers. Modeling the functional behavior of magnetic materials r…