Magnets are key elements in modern society. Their application ranges from sensors in automotive and security applications to green technology where soft and hard magnets play a significant role in energy transfer and the emerging field of spintronics. The main objective of this project is the simulation of magnetic devices and magnets based on rigorous simulations starting from the atomistic level in order to obtain the required parameter for the underlying continuous model.
In order to bridge the length scale from atoms to dimensions of real sensor dimensions we will develop reduced complexity models for magnetism, based on eigenmode analysis and data space approximation using low-rank tensors. This models will be used for the design of spintronic sensors and rare earth reduced permanent magnets.
Another focus will be rare event switching in thermal driven magnetization dynamics. This will be used to design recording media for heat assisted magnetic recording, optimizing for reliable switching and high signal to noise ratios. A particular challenge will be to incorporate fast time varying properties such as fast heating due to the laser pulse, which we aim to solve with non-stationary forward flux sampling.
This work is co-funded by Austrian Science Fund (FWF) and the county of Lower Austria.
Exl, L.; Fischbacher, J.; Kovacs, A.; Oezelt, H.; Gusenbauer, M.; Schrefl, T. (2019). Preconditioned nonlinear conjugate gradient method for micromagnetic energy minimization. Computer Physics Communications, 235: 179-186
Exl, L.; Mauser, N. J.; Schrefl, T.; Suess, D. (2017). The extrapolated explicit midpoint scheme for variable order and step size controlled integration of the Landau-Lifschitz-Gilbert equation. Journal of Computational Physics, 346: 14-24
Fischbacher, J.; Kovacs, A.; Oezelt, H.; Gusenbauer, M.; Suess, D.; Schrefl, T. (2017). Effective uniaxial anisotropy in easy-plane materials through nanostructuring. Applied Physics Letters, 111(19): 192407
Fischbacher, J.; Kovacs, A.; Oezelt, H.; Schrefl, T.; Exl, L.; Fidler, J.; Suess, D.; Sakuma, N.; Yano, M.; Kato, A.; Shoji, T.; Manabe, A. (2017). Nonlinear conjugate gradient methods in micromagnetics. AIP Advances, 7(4): 045310