Thomas Schrefl

Univ.-Doz.Dipl.-Ing.Dr. Thomas Schrefl

Head of Center - Center for Modelling and Simulation

Projects (Extract Research Database)

Publications (Extract Research Database)

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

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

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

Tang, X.; Li, J.; Miyazaki, Y.; Sepehri-Amin, H.; Ohkubo, T.; Schrefl, T.; Hono, K. (2020). Relationship between the Thermal Stability of Coercivity and the Aspect Ratio of Grains in Nd-Fe-B Magnets: Experimental and Numerical Approaches. Acta Materialia, 183: 408-417

Westmoreland, S. C.; Skelland, C.; Shoji, T.; Yano, M.; Kato, A.; Ito, M.; Hrkac, G.; Schrefl, T.; Evans, R.; Chantrel, R. W. (2020). Atomistic simulations of a-Fe/Nd2Fe14B magnetic core/shell nanocomposites with enhanced energy product for high temperature permanent magnet applications. AIP, Vol. 127: 133901

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

Dirba, I.; Li, J.; Sepehri-Amin, H.; Ohkubo, T.; Schrefl, T.; Hono, K. (2019). Single-Crystalline SmFe12-Based Microparticles with High Roundness Fabricated by Jet-Milling. Journal of Alloys and Compounds, 804: 155-162

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

Nieves, P.; Arapan, S.; Maudes-Raedo, J.; Marticorena-Sánchez, R.; Del Brío, N. L.; Kovacs, A.; Echevarria-Bonet, C.; Salazar, D.; Weischenberg, J.; Zhang, H.; Vekilova, O. Yu.; Serrano-López, R.; Barandiaran, J. M.; Skokov, K.; Gutfleisch, O.; Eriksson, O.; Herper, H. C.; Schrefl, T.; Cuesta-López, S. (2019). Database of Novel Magnetic Materials for High-Performance Permanent Magnet Development. Computational Materials Science, 168: 188-202

Sepehri-Amin, H.; Dirba, I.; Tang, X.; Ohkubo, T.; Schrefl, T.; Gutfleisch, O.; Hono, K. (2019). Development of High Coercivity Anisotropic Nd-Fe-B/Fe Nanocomposite Powder Using Hydrogenation Disproportionation Desorption Recombination Process. Acta Materialia, 175: 276-285

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

Soderznik, M.; Li, J.; Liu, L.; Sepehri-Amin, H.; Ohkubo, T.; Sakuma, N.; Shoji, T.; Kato, A.; Schrefl, T.; Hono, K. (2019). Magnetization reversal process of anisotropic hot-deformed magnets observed by magneto-optical Kerr effect microscopy. Journal of Alloys and Compounds, 771: 51/

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

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/

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Lectures (Extract Research Database)

Machine learning, micromagnetics and magnet design

University of York, Computational Magnetism, 02/12/2020

Finding weak spots in permanent magnets through micromagnetism and machine learning

CMD2020GEFES, 02/09/2020

Computational Design of Bulk Permanent Magnet

TMS2020, 25/02/2020

Bridging the gap between biomedical applications and material sciences

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

Advancing permanent magnets by machine learning

Meeting of CRC/TRR 270 - Hysteresis design of magnetic materials for efficient energy conversion, 05/02/2020

Computer based optimization of permanent magnets

Seminar, CEA, Grenoble, 17/12/2019

Learning Magnetization Dynamics

64th Annual Conference on Magnetism and Magnetic Material, Las Vegas, USA, 07/11/2019

Machine learning for permanent magnet optimization

2019 - Sustainable Industrial Processing Summit & Exhibition, Paphos, Cryprus, 26/10/2019

Micromagnetic optimization of permanent magnetic materials

27th International Conference on Materials and Technology, Portoroz, Slovenia, 17/10/2019

Computational optimization of permanent magnets

Ruhr Symposium 2019, Duisburg, Germany, 09/10/2019

Modelling of microstructure for optimum hard magnetic properties

MMA’19: Magnetic Materials and Applications, Milano, Italy, 18/09/2019

Ferromagnetic resonance simulations for stochastic Landau-Lifshitz-Gilbert equation

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

Micromagnetic characterization of MnAl-C using trained neural networks

JEMS2019, Uppsala, Schweden, 29/08/2019

Bridging the gap between academic software and industry needs - different business models for engaging with industry

EMMC Workshop, Cambridge, UK, 21/05/2019

Microstructure optimization for rare-earth efficient permanent magnets

DPG Spring Meeting, Regensburg, Germany, 01/04/2019

Magnetic materials modelling – Bridging the gap between academic software and industry needs

EMMC International Workshop 2019, Vienna, Austria, 27/02/2019

Simulation of permanent magnets across the length scales

Functional Materials Colloquium, TU Darmstadt, 26/10/2018

Automated micromagnetic simulations from Electron Backscatter Diffraction data

JEMS 2018, 05/09/2018

Computational design of rare-earth reduced permanent magnets

Rare-earth and future permanent magnets and their applications REPM2018, Beijing, China, 28/08/2018

Energy Barriers in Nano-structured Permanent Magnets

Conference on Mathematical Aspects of Materials Science, Portland Oregon, USA, 10/07/2018

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