Dipl.-Ing.(FH) Dr. Markus Gusenbauer

Center for Modelling and Simulation

Projects (Extract Research Database)

Running projects

Magnetism at interfaces: from quantum to reality

Duration: 01/11/2022–31/10/2025
Principle investigator for the project (University for Continuing Education Krems): Markus Gusenbauer
Funding: FWF

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Towards the digital twin of a permanent magnet: an enhanced description of microstructure and state

Duration: 01/03/2022–28/02/2026
Principle investigator for the project (University for Continuing Education Krems): Markus Gusenbauer
Funding: FWF

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Completed projects

The Effect of Interfaces on Magnetisation Reversal in MnAl-C

Duration: 01/10/2017–30/11/2020
Principle investigator for the project (University for Continuing Education Krems): Markus Gusenbauer
Funding: FWF
Program: DACH

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Publications (Extract Research Database)

Ali, Q.; Fischbacher, J.; Kovacs, A.; Özelt, H.; Gusenbauer, M.; Moustafa, H.; Böhm, D.; Breth, L.; Schrefl, T. (2024). Defect manipulation for the coercivity enhancement of Nd-Fe-B permanent magnets. Physica B: Condensed Matter, Vol. 678: 415759

Moustafa, H.; Kovacs, A.; Fischbacher, J.; Gusenbauer, M.; Ali, Q.; Breth, L.; Hong, Y.; Rigaut, W.; Devillers, T.; Dempsey, N. M.; Schrefl, T.; Özelt, H. (2024). Reduced Order Model for Hard Magnetic Films. AIP Advances, Vol. 14, iss. 2: 025001-1 bis 025001-5

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

Ali, Q.; Fischbacher, J.; Kovacs, A.; Oezelt, H.; Gusenbauer, M.; Yano, M.; Sakuma, N.; Kinoshita, A.; Shoji, T.; Kato, A.; Schrefl, T. (2023). Benchmarking for systematic coarse-grained micromagnetics. In: HMM, proceedings in 13th International Symposium on Hysteresis Modeling and Micromagnetics (HMM 2023): 1, HMM, WIen

Gusenbauer, M.; Oezelt, H.; Kovacs, A.; Fischbacher, J.; Zhao, P.; Woodcock, T.-G.; Schrefl, T. (2023). Magnetization reversal of large granular magnetic materials. In: HMM, proceedings in 13th International Symposium on Hysteresis Modeling and Micromagnetics (HMM 2023): 1, HMM, Wien

Kovacs, A.; Fischbacher, J.; Oezelt, H.; Ali, Q.; Gusenbauer, M.; Schrefl, T. (2023). Finite Hex Element Adaptive Mesh Refinement of Demagnetizing Field Computation. In: HMM, proceedings in 13th International Symposium on Hysteresis Modeling and Micromagnetics (HMM 2023): 1, HMM, Wien

Oezelt, H.; Kovacs, A.; Breth, L.; Gusenbauer, M.; Schaffer, S.; Exl, L.; Schrefl. T. (2023). Machine learning based optimization of hard-/soft magnetic nanostructures. In: HMM, proceedings in 13th International Symposium on Hysteresis Modeling and Micromagnetics (HMM 2023): 1, HMM, Wien

Ali, Q.; Fischbacher, J.; Kovacs, A.; Oezelt, H.; Gusenbauer, M.; Moustafa, H.; Böhm, D.; Breth, L.; Schrefl, T. (2023). Defect Manipulation for the Coercivity Enhancement of Nd-Fe-B Permanent Magnets. SSRN, 2023: 4628986, Elesevier

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

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

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Lectures (Extract Research Database)

Magnetization reversal of large granular magnetic materials

HMM 2023, 05/06/2023

Micromagnetic modelling of soft-in-hard FeCo-FePt nanocomposites

13th International Symposium on Hysteresis Modeling and Micromagnetics (HMM 2023), 05/06/2023

Multiscaling strategies in computational magnet design

Going Green – CARE INNOVATION 2023, 11/05/2023

Coercivity analysis of twin boundaries with demagnetization negligible models in arbitrary field direction

JEMS 2022, 26/07/2022

Machine Learning for Relating Structure and Coercivity of Permanent Magnets

Virtual REPM 2021, 09/06/2021

Bridging the gap between biomedical applications and material sciences

3rd Workshop on Modelling of Biological Cells, Fluid Flow and Microfluidics, 11/02/2020

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

Automated micromagnetic simulations from Electron Backscatter Diffraction data

JEMS 2018, 05/09/2018

Sensing the blood cell damage in a magnetically actuated circular pump

IEEE Sensors 2017, 01/11/2017

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