Univ.-Doz.Dipl.-Ing.Dr. Thomas Schrefl
- thomas.schrefl@donau-uni.ac.at
- +43 2622 23420-20
- +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
Projects (Extract Research Database)
Running projects
Multi-property Compositionally Complex Magnets for Advanced Energy Applications
Duration: 01/06/2023–31/05/2026
Principle investigator for the project (University for Continuing Education Krems): Thomas Schrefl
Funding: EU
Duration: 01/04/2023–31/03/2025
Principle investigator for the project (University for Continuing Education Krems): Thomas Schrefl
Funding: EU
Duration: 01/07/2022–30/06/2026
Principle investigator for the project (University for Continuing Education Krems): Thomas Schrefl
Funding: EU
Magnet design through physics informed machine learning
Duration: 01/09/2020–31/08/2027
Principle investigator for the project (University for Continuing Education Krems): Thomas Schrefl
Funding: Private (Stiftungen, Vereine etc.)
Duration: 01/01/2019–31/12/2021
Principle investigator for the project (University for Continuing Education Krems): Thomas Schrefl
Funding: FFG
Program: Produktion der Zukunft
Completed projects
Simumag - GFF Horizon Europe Start-up funding
Duration: 01/01/2022–30/03/2022
Principle investigator for the project (University for Continuing Education Krems): Thomas Schrefl
Funding: Bundesländer (inkl. deren Stiftungen und Einrichtungen)
Duration: 01/03/2018–28/02/2022
Principle investigator for the project (University for Continuing Education Krems): Thomas Schrefl
Funding: EU
Program: Horizon 2020
Nanostructured multiphase permanent magnets
Duration: 01/04/2019–31/12/2020
Principle investigator for the project (University for Continuing Education Krems): Thomas Schrefl
Funding: sonstige öffentlich-rechtliche Einrichtungen (Körperschaften, Stiftungen, Fonds)
Atomistic Simulation of rare-earth reduced permanent magnets
Duration: 01/11/2017–31/12/2019
Principle investigator for the project (University for Continuing Education Krems): Thomas Schrefl
Funding: Unternehmen
NOVel, critical materials free, high Anisotropy phases for permanent MAGnets, by design
Duration: 01/04/2016–30/09/2019
Principle investigator for the project (University for Continuing Education Krems): Thomas Schrefl
Funding: EU
Program: H2020
Multiscale simulations of magnetic nanostructures
Duration: 01/01/2015–30/06/2019
Principle investigator for the project (University for Continuing Education Krems): Thomas Schrefl
Funding: FWF
Program: FWF
Nanostructured multiphase permanent magnets
Duration: 01/04/2018–31/03/2019
Principle investigator for the project (University for Continuing Education Krems): Thomas Schrefl
Funding: Sonstige
NanoStructured Multiphase Permanent Magnets
Duration: 01/04/2017–31/03/2018
Principle investigator for the project (University for Continuing Education Krems): Thomas Schrefl
Funding: andere internationale Organisationen
CREST III Simulation of hard magnet magnetic materials
Duration: 01/04/2016–31/03/2017
Principle investigator for the project (University for Continuing Education Krems): Thomas Schrefl
Funding: andere internationale Organisationen
Program: CREST
Nano-Structured Multi-Phase Permanent Magnets II
Duration: 01/04/2016–31/03/2017
Principle investigator for the project (University for Continuing Education Krems): Thomas Schrefl
Funding: andere internationale Organisationen
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
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
Heistracher, P.; Abert, C.; Bruckner, F.; Schrefl, T.; Suess, D. (2022). Proposal for a micromagnetic standard problem: domain wall pinning at phase boundaries. Journal of Magnetism and Magnetic Materials, Vol. 548: 168875
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
Cuadrado, R.; Evans, R. F. L.; Shoji, T.; Yano, M.; Kato, A.; Ito, M.; Hrkac, G.; Schrefl, T.; Chantrell, R.W. (2021). First principles and atomistic calculation of the magnetic anisotropy of Y2Fe14B. JOURNAL OF APPLIED PHYSICS, 130: 023901
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
Exl, L.; Mauser, N. J.; Schaffer, S.; Schrefl, T.; Suess, D.; (2021). Prediction of magnetization dynamics in a reduced dimensional feature space setting utilizing a low-rank kernel method. JOURNAL OF COMPUTATIONAL PHYSICS, 444: 110586
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
Perna, S.; Schrefl, T.; Serpico, C.; Fischbacher, J.; Del Pizzo, A. (2021). Microstructure Role in Permanent Magnet Eddy Current Losses. IEEE TRANSACTIONS ON MAGNETICS, 57: 6300405
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
Exl, L.; Mauser, N.; Schrefl, T.; Suess, D. (2020). Learning time-stepping by nonlinear dimensionality reduction to predict magnetization dynamics. Communications in Nonlinear Science and Numerical Simulation, Vol. 84: 105205
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
Lectures (Extract Research Database)
Generative deep learning for permanent magnet microstructures
67th Annual Conference on Magnetism and Magnetic Materials (MMM 2022), 03/11/2022
How to Create an Effective Scientific Video Presentation
67th Annual Conference on Magnetism and Magnetic Materials (MMM 2022), 02/11/2022
Materials Informatics for the Design of Rare-Earth Reduced Permanent Magnets
Magnetic Materials and Applications 22, 26/10/2022
Magnetization processes in SmFeO3
DPG Frühjahrstagung, 06/09/2022
Machine Learning Analysis of Multiphase Magnetic Microstructures
CIMTEC 2022, 23/06/2022
Physics informed neural networks for computational magnetism
MMM-Intermag 2022, 10/01/2022
Inverse design of Nd-substituted permanent magnets
Physics and the green economy, 25/11/2021
Tutorial: An introduction to machine learning for solving micromagnetic problems
The 2021 Around-the-Clock Around-the-Globe Magnetics Conference, 24/08/2021
Deep learning magnetization dynamics
IEEE Advances in Magnetism 2021, 16/06/2021
New trends for machine learning in permanent magnet design
The 26th International Workshop on Rare Earth and Future Permanent Magnets and Their Application, 10/06/2021