
Dipl.-Ing.(FH) Johann Fischbacher, MSc
- johann.fischbacher@donau-uni.ac.at
- +43 2622 23420-57
- +43 2622 23420-99 (Fax)
- To contact form
- TFZ Wiener Neustadt, Section E - Floor 2
- University for Continuing Education Krems
- Center for Modelling and Simulation
- Viktor Kaplan Straße 2 - Bauteil E
- 2700 Wiener Neustadt
- Austria
Publications (Extract Research Database)
Breth, L.; Fischbacher, J.; Kovacs, A.; Özelt, H.; Schrefl, T.; Brückl, H.; Czettl, C.; Kührer, S.; Pachlhofer, J., Schwarz, M. (2023). FORC diagram features of Co particles due to reversal by domain nucleation. Journal of Magnetism and Magnetic Materials 571 (2023) 170567 Available online 24 February 2023 0304-8853/© 2023 Elsevier B.V. All rights reserved.Contents lists available at ScienceDirect Journal of Magnetism and Magnetic Materials, Vol. 571: 1-6
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
Yamano, H.; Kovacs, A.; Fischbacher, J.; Danno, K.; Umetani, Y.; Shoji, T.; Schrefl, T. (2023). Efficient optimization approach for designing power device structure using machine learning. Japanese Journal of Applied Physics, Vol. 1: 1-17
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
Mohapatra, J.; Fischbacher, J.; Gusenbauer, M.; Xing, M. Y.; Elkins, J.; Schrefl, T.; Liu, J. P. (2022). Coercivity limits in nanoscale ferromagnets. Phys. Rev. B, Vol. 105, Iss. 21: 214431
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
Ener, S.; Skokov, K. P.; Palanisamy, D.; Devillers, T.; Fischbacher, J.; Eslavac, G.; Maccaria, F.; Schäfer, L.; Diop, L.; Radulov, I.; Gault, B.; Hrkac, G.; Dempsey, N.; Schrefl, T.;Raabe, D.; Gutfleisch, O. (2021). Twins – A weak link in the magnetic hardening of ThMn12-type permanent magnets. Acta Materialia, Vol. 214: 116968
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
Tsuchiura, H.; Yoshioka, T.; Novák, P.; Fischbacher, J.; Kovacs, A.; Schrefl, T. (2021). First-principles calculations of magnetic properties for analysis of magnetization processes in rare-earth permanent magnets". Science and Technology of Advanced Materials (STAM), Vol. 22, no. 1: 748-757
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
Schönhöbel, A.M.; Madugundo, R.; Barandiarán, J.M.; Hadjipanayis, G.C.; Palanisamy, D.; Schwarz, T.; Gault, B.; Raabe, D.; Skokov, K.; Gutfleisch, O.; Fischbacher, J.; Schrefl, T. (2020). Nanocrystalline Sm-based 1:12 magnets. Acta Materialia, Vol. 200: 652-658
Skelland, C.; Westmoreland, S.C.; Ostler, T.; Evans, R.F.L.; Chantrell, R.W.; Yano, M.; Shoji, T.; Kato, A.; Ito, M.; Winklhofer, M.; Zimanyi, G.; Schrefl, T.; Fischbacher, J.; Hrkac, G. (2020). Atomistic study on the pressure dependence of the melting point of NdFe12. AIP Advances, Vol. 10, iss. 2: 025130
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
Skelland, C.; Ostler, T.; Westmoreland, S.C.; Evans, R.F.L.; Chantrell, R.W.; Yano, M.; Shoji, T.; Kato, A.; Winkelhofer, M., Zimanyi, G.; Fischbacher, J.; Schrefl, T.; Hrkac, G. (2019). The Effect of Interstitial Nitrogen Addition on the Structural Properties of Supercells of NdFe12-xTix. IEEE Transactions on Magnetics, Vol. 55, iss. 10: 6700205
Vekilova, O. Y.; Fayyazi, B.; Skokov, K. P.; Gutfleisch, O.; Echevarria-Bonet, C.; Barandiarán, J. M.; Kovacs, A.; Fischbacher, J.; Schrefl, T.; Eriksson, O.; Herper, H. C. (2019). Tuning the Magnetocrystalline Anisotropy of Fe3Sn by Alloying. Physical Review B, 99: 024421
Lectures (Extract Research Database)
Machine Learning for Relating Structure and Coercivity of Permanent Magnets
Virtual REPM 2021, 09/06/2021
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
Micromagnetic simulation of surface anisotropy effects in SmFe_12-type permanent magnets
JEMS2019 Joint European Magnetic Symposia, Uppsala, Schweden, 26/08/2019
Micromagnetic simulation of surface anisotropy effects in SmFe12 type permanent magnets
Joint European Magnetic Symposia, Uppsala, Sweden, 26/08/2019
Micromagnetic Simulation of Partially Ordered L1_0 FeNi Permanent Magnets
MANA 2018 - Micromagnetics: Analysis, Numerics, Applications, TU Wien, Resselgasse 4, 1040 Wien, Österreich, 08/11/2018
Micromagnetic Simulation of Partially Ordered L1_0 FeNi Permanent Magnets
21st International Conference on Magnetism (ICM2018) Moscone Center, San Francisco, USA, 16/07/2018
Micromagnetic Simulation of Partially Ordered L1_0 FeNi Permanent Magnets
Santorini Workshop Future Perspectives on Novel Magnetic Materials, Santorini Palace Hotel, Santorini, Griechenland, 30/05/2018
AF-10-Influence of Alignment Depenent Grain Boundary Composition Changes on Coercivity and Magnetic Reversal of Nd2Fe14B Megnets
Konferenz MMM 2017 in Pittsburgh, 07/11/2017
Self demagnetizing effects in NdFe12 based magnets at high temperature
61st Annual Conference on Magnetism and Magnetic Materials, New Orleans, Louisiana, 31.10.-4.11.2016, 03/11/2016