Harald Özelt

Ing. Dr. Harald Özelt, MSc

Center for Modelling and Simulation

Projects (Extract Research Database)

Publications (Extract Research Database)

Kovacs, A.; Fischbacher, J.; Oezelt, H.; Kornell, A.; Ali, Q.; Gusenbauer, M.; Yano, M.; Sakuma, N.; Kinoshita, A.; Shoji, T.; Kato, A.; Hong, Y.; Grenier, S.; Devillers, T.; Dempsey, N. M.; Fukushima, T.; Akai, H.; Kawashima, N.; Miyake, T.; Schrefl, T. (2023). Physics-Informed Machine Learning Combining Experiment and Simulation for the Design of Neodymium-Iron-Boron Permanent Magnets with Reduced Critical-Elements Content. Frontiers in Materials 2023, Vol. 9: 1-19

Zhao, P.; Gusenbauer, M.; Oezelt, H.; Wolf, D.; Gemming, T.; Schrefl, T.; Nielsch, K.; Woodcock, T. G. (2023). Nanoscale chemical segregation to twin interfaces in t -MnAl-C and resulting effects on the magnetic properties. Journal of Materials Science & Technology, Vol. 134: 22-32

Kovacs, A.; Exl, L.; Kornell, A.; Fischbacher, J.; Hovorka, M.; Gusenbauer, M.; Breth, L.; Oezelt, H.; Yano, M.; Sakuma, N.; Kinoshita, A.; Shoji, T.; Kato, A.; Schrefl, T. (2022). Conditional physics informed neural networks. Communications in Nonlinear Science and Numerical Simulation, Vol. 104: 106041

Kovacs, A.; Exlc, L.; Kornell, A.; Fischbacher, J.; Hovorka, M.; Gusenbauer, M.; Breth, L.; Oezelt, H.; Praetorius, D.; Suess, D.; Schrefl, T. (2022). Magnetostatics and micromagnetics with physics informed neural networks. Journal of Magnetism and Magnetic Materials, Vol. 548: 168951

Oezelt, H.; Qu, L.; Kovacs, A.; Fischbacher, J.; Gusenbauer, M.; Beigelbeck, R.; Praetorius, D.; Yano, M.; Shoji, T.; Kato, A.; Chantrell, R.; Winklhofer, M.; Zimanyi, G.; Schrefl, T. (2022). Full- Spin-Wave-Scaled Stochastic Micromagnetism for Mesh-Independent Simulations of Ferromagnetic Resonance and Reversal. npj Computational Materials, Vol. 8: 35

Zhao, P.; Gusenbauer, M.; Oezelt, H.; Wolf, D.; Gemming, T.; Schrefl, T.; Nielsch, K.; Woodcock, T. G. (2022). Nanoscale chemical segregation to twin interfaces in t-MnAl-C and resulting effects on the magnetic properties. Journal of Materials Science & Technology, Vol. 134: 22-32

Gusenbauer, M.; Kovacs, A.; Özelt, H.; Fischbacher, J.; Zhao, P.; Woodcock, T.G.;Schrefl, T. (2021). Insights into MnAl-C nano-twin defects by micromagnetic characterization. Journal of Applied Physics, 129(9): 093902

Gusenbauer, G.; Oezelt, H.; Fischbacher, J.; Kovacs, A.; Zhao, P.; Woodcock, T. G.; Schrefl, T. (2020). Extracting local switching fields in permanent magnets using machine learning. npj Computational Materials, 6: 89ff

Kovacs, A.; Fischbacher, J.; Gusenbauer, M.; Oezelt, H.; Herper, H. C.; Vekilova, O. Y.; Nieves, P.; Arapan, S.; Schrefl, T. (2020). Computational design of rare-earth reduced permanent magnets. Engineering, 6: 148

Arapan, S.; Nieves, P.; Cuesta-López, S.; Gusenbauer, M.; Oezelt, H.; Schrefl, T.; Delczeg-Czirjak, E. K.; Herper, H. C.; Eriksson, O. (2019). Influence of antiphase boundary of the MnAl t-phase on the energy product. Physical Review Materials, Vol. 3, iss. 6: 064412

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

Gusenbauer, M.; Fischbacher, J.; Kovacs, A.; Oezelt, H.; Bance, S.; Zhao, P.; Woodcock, T.G.; Schrefl, T. (2019). Automated meshing of electron backscatter diffraction data and application to finite element micromagnetics. Journal of Magnetism and Magnetic Materials, Volume 486: 165256

Kovacs, A.; Fischbacher, J.; Gusenbauer, M.; Oezelt, H.; Herper, H. C.; Vekilova, O. Yu.; Nieves, P.; Arapan, S.; Schrefl, T. (2019). Computational Design of Rare-Earth Reduced Permanent Magnets. Engineering, November 2019: in press

Kovacs, A.; Fischbacher, J.; Oezelt, H.; Gusenbauer, M.; Exl, L.; Bruckner, F.; Suess, D.; Schrefl, T. (2019). Learning Magnetization Dynamics. Journal of Magnetism and Magnetic Materials, 491: 165548

Exl, L.; Fischbacher, J.; Kovacs, A.; Oezelt, H.; Gusenbauer, M.; Yokota, K.; Shoji, T., Hrkac, G.; Schrefl, T.; (2018). Magnetic microstructure machine learning analysis. JPhys Materials, 2: 014001/https://doi.org/10.1088/2515-7639/aaf26d

Fischbacher, J.; Kovacs, A.; Gusenbauer, M.; Oezelt, H.; Exl, L.; Bance, S.; Schrefl, T. (2018). Micromagnetics of rare-earth efficient permanent magnets. Journal of Physics D: Applied Physics, Vol. 51, no. 19: 193002-193019

Fischbacher, J.; Kovacs, A.; Oezelt, H.; Gusenbauer, M.; Schrefl, T.; Exl, L.; Givord, D.; Dempsey, N. M.; Winklhofer, M.; Hrkac, G.; Chantrell, R.; Sakuma, N.; Yano, M.; Kato, A.; Shoji, T.; Manabe, A. (2017). On the limits of coercivity in permanent magnets. Applied Physics Letters, 111(7): 072404

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

Kovacs, A.; Fischbacher, J.; Oezelt, H.; Schrefl, T.; Kaidatzis, A.; Salikhov, R.; Farle, M.; Giannopoulus, G.; Niarchos, D. (2017). Micromagnetic Simulations for Coercivity Improvement Through Nano-Structuring of Rare-Earth-Free L10-FeNi Magnets. IEEE Transactions on Magnetics, 53(11): DOI: 10.1109/TMAG.2017.2701418

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Lectures (Extract Research Database)

Reduced Order Model for Large Multigrain Systems

67th Annual Conference on Magnetism and Magnetic Materials (MMM 2022), 03/11/2022

Machine learning as building block for macromagnetic simulations

CMAM 2022, 31/08/2022

Machine Learning for Relating Structure and Coercivity of Permanent Magnets

Virtual REPM 2021, 09/06/2021

Macromagnetic Simulations by Micromagnetic Superposition

MMM2020 (Magnetism and Magnetic Materials), 06/11/2020

Renormalization of the intrinsic magnetic propertiesfor stochastic micromagnetics

Working Group on "Micromagnetics of Permanent Magnets", Wien, Österreich, 14/10/2019

Micromagnetic characterization of MnAl-C using trained neural networks

JEMS2019, Uppsala, Schweden, 29/08/2019

Ferromagnetic resonance simulations for stochastic Landau-Lifshitz-Gilbert equation

The Joint European Magnetic Symposia (JEMS), Uppsala, Sweden, 29/08/2019

Exchange-Coupled Ferri-/Ferromagnetic Composite Nanomagnets

Rigorosum Harald Özelt, Wien, Österreich, 16/01/2019

Vortex Motion in Amorphous Ferrimagnetic Thin Film Elements

61st Annual Conference on Magnetism and Magnetic Materials - MMM 2016, New Orleans, Louisiana, USA, 31. Oct. - 4. Nov. 2016, 03/11/2016

Micromagnetic simulations for switching field distribution of ferri- /ferromagnetic composite bit patterned media

1st IEEE Conference Advances in Magnetics - AIM 2016, Bormio, Italy, March 14-16 2016, 15/03/2016

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