Researcher Portfolio

Dr.-Ing. Kühbach, Markus Tobias

Humboldt Univ, Struct Res & Electron Microscopy Grp, Dept Phys, Consortium FAIRmat, Newtonstr 15, D-12489 Berlin, Germany, Institute of Physical Metallurgy and Metal Physics, RWTH Aachen University, Aachen 52074, Germany, NOMAD, Fritz Haber Institute, Max Planck Society, Theory and Simulation, Microstructure Physics and Alloy Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society

Researcher Profile

Position: Institute of Physical Metallurgy and Metal Physics, RWTH Aachen University, Aachen 52074, Germany

Position: Theory and Simulation, Microstructure Physics and Alloy Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society

Position: Humboldt Univ, Struct Res & Electron Microscopy Grp, Dept Phys, Consortium FAIRmat, Newtonstr 15, D-12489 Berlin, Germany

Position: NOMAD, Fritz Haber Institute, Max Planck Society

Researcher ID: https://pure.mpg.de/cone/persons/resource/persons181390

External references

WorldCat Search for Kühbach, Markus Tobias

Google Scholar Search for Kühbach, Markus Tobias

Publications

: Gault, B., Saksena, A., Sauvage, X., Bagot, P., Aota, L. S., Arlt, J., Belkacemi, L. T., Boll, T., Chen, Y.-S., Daly, L., Djukic, M., Douglas, J., Duarte, M. J., Felfer, P. J., Forbes, R., Fu, J., Gardner, H., Gemma, R., Gerstl, S. S. A., Gong, Y., Hachet, G., Jakob, S., Jenkins, B. M., Jones, M. E., Khanchandani, H., Kontis, P., Krämer, M., Kühbach, M., Marceau, R. K. W., Mayweg, D., Moore, K., Nallathambi, V., Ott, B., Poplawsky, J. D., Prosa, T., Pundt, A., Saha, M., Schwarz, T., Shang, Y., Shen, X., Vrellou, M., Yu, Y., Zhao, Y., & Zou, B. (2024). Towards Establishing Best Practice in the Analysis of Hydrogen and Deuterium by Atom Probe Tomography. Microscopy and Microanalysis, 30(6), 1205-1220. doi:10.1093/mam/ozae081. [PubMan] : Saxena, A., Polin, N., Kühbach, M. T., Katnagallu, S., Kontis, P., Gault, B., & Freysoldt, C. (2024). A Machine Learning based Workflows to Quantify Atom Probe Tomography Data. Talk presented at Workshop "Frontiers of APT Physics, Data Processing, Analysis and Reconstruction“. Arlington, VA, USA. 2024-08-01 - 2024-08-02. [PubMan] : Kühbach, M. T., London, A. J., Wang, J., Schreiber, D. K., Mendez Martin, F., Ghamarian, I., Bilal, H., & Ceguerra, A. V. (2022). Community-Driven Methods for Open and Reproducible Software Tools for Analyzing Datasets from Atom Probe Microscopy. Microscopy and Microanalysis, 28(4), 1038-1053. doi:10.1017/S1431927621012241. [PubMan] : Zhou, X., Wei, Y., Kühbach, M. T., Zhao, H., Vogel, F., Kamachali, R. D., Thompson, G. B., Raabe, D., & Gault, B. (2022). Revealing in-plane grain boundary composition features through machine learning from atom probe tomography data. Acta Materialia, 226: 117633. doi:10.1016/j.actamat.2022.117633. [PubMan] : Zhou, X., Wei, Y., Kühbach, M. T., Zhao, H., Vogel, F., Kamachali, R. D., Thompson, G. B., Raabe, D., & Gault, B. (2022). Revealing in-plane grain boundary composition features through machine learning from atom probe tomography data. Acta Materialia, 226: 117633. doi:10.1016/j.actamat.2022.117633. [PubMan] : Kühbach, M. T., Bajaj, P., Zhao, H., Çelik, M. H., Jägle, E. A., & Gault, B. (2021). On strong-scaling and open-source tools for analyzing atom probe tomography data. npj Computational Materials, 7(1): 21. doi:10.1038/s41524-020-00486-1. [PubMan] : Kühbach, M. T., Kasemer, M., Gault, B., & Breen, A. J. (2021). Open and strong-scaling tools for atom-probe crystallography: high-throughput methods for indexing crystal structure and orientation. Journal of Applied Crystallography, 54(Pt 5), 1490-1508. doi:10.1107/S1600576721008578. [PubMan] : Kühbach, M. T., London, A. J., Wang, Jing, J., Schreiber, D. K., Mendez Martin, F., Ghamarian, I., Bilal, H., & Ceguerra, A. V. (2021). Community-Driven Methods for Open and Reproducible Software Tools for Analyzing Datasets from Atom Probe Microscopy. Microscopy and Microanalysis, 1-16. doi:10.1017/S1431927621012241. [PubMan] : Kühbach, M. T., & Roters, F. (2020). Quantification of 3D spatial correlations between state variables and distances to the grain boundary network in full-field crystal plasticity spectral method simulations. Modelling and Simulation in Materials Science and Engineering, 28: 055005. doi:10.1088/1361-651X/ab7f8c. [PubMan] : Kühbach, M. T. (2020). transcoder tool added first implementation of Python reader for *.APT files.. [PubMan] : Wei, Y., Peng, Z., Kühbach, M., Breen, A. J., Legros, M., Larranaga, M., Mompiou, F., & Gault, B. (2019). 3D nanostructural characterisation of grain boundaries in atom probe data utilising machine learning methods. PLoS One, 14(11): e0225041. doi:10.1371/journal.pone.0225041. [PubMan] : Diehl, M., & Kühbach, M. (2019). Coupled experimental-computational analysis of primary static recrystallization in low carbon steel. Modelling and Simulation in Materials Science and Engineering, 28(1): 014001. doi:10.1088/1361-651X/ab51bd. [PubMan] : Diehl, M., Kühbach, M., Kertsch, L., Traka, K., & Raabe, D. (2019). Coupled Experimental–Computational Analysis of Primary Static Recrystallization in Low Carbon Steel. Talk presented at Seminar of the Department of Mechanical Science and Engineering of the University of Illinois. Urbana-Champaign, Il, USA. 2019-09-27. [PubMan] : Kühbach, M., Bajaj, P., Breen, A. J., Jägle, E. A., & Gault, B. (2019). On Strong Scaling Open Source Tools for Mining Atom Probe Tomography Data. Microscopy and Microanalysis, 25(S2 ), 298-299. doi:10.1017/S1431927619002228. [PubMan] : Kühbach, M., Breen, A. J., Herbig, M., & Gault, B. (2019). Building a Library of Simulated Atom Probe Data for Different Crystal Structures and Tip Orientations Using TAPSim. Microscopy and Microanalysis, 25(2), 320-330. doi:10.1017/S1431927618016252. [PubMan] : Latypov, M. I., Kühbach, M., Beyerlein, I. J., Stinville, J. C., Tóth, L. S., Pollock, T. M., & Kalidindi, S. R. (2018). Application of chord length distributions and principal component analysis for quantification and representation of diverse polycrystalline microstructures. Materials Characterization, 145, 671-685. doi:10.1016/j.matchar.2018.09.020. [PubMan] : Diehl, M., Kühbach, M., & Raabe, D. (2018). Experimental–computational analysis of primary static recrystallizazion in DC04 steel. Talk presented at 9th International Conference on Multiscale Materials Modeling. Osaka, Japan. 2018-10-28 - 2018-11-02. [PubMan] : Diehl, M., Kühbach, M., & Raabe, D. (2018). Experimental–computational analysis of primary static recrystallizazion in DC04 steel. Poster presented at 9th International Conference on Multiscale Materials Modeling, Osaka, Japan. [PubMan] : Kühbach, M., Roters, F., Imran, M., Bambach, M., Breen, A. J., Gault, B., Bajaj, P., & Zhao, H. (2018). Scalable Quantifying of Evolving Descriptive Spatial Statistics in Full-Field Crystal Plasticity and Atom Probe Tomography. Talk presented at Institut für Metallkunde und Metallphysik, RWTH Aachen University. Aachen, Germany. 2018-06-30. [PubMan] : Kühbach, M., Breen, A. J., Herbig, M., Gault, B., & Raabe, D. (2018). Building a Library of Simulated Atom Probe Data for Different Crystal Structures and Pillar Orientations Using TAPSim. Poster presented at APT&M 2018 International Conference on Atom-Probe Tomography & Microscopy, Washington, DC, USA. [PubMan] : Schwarze, C., Kamachali, R. D., Kühbach, M., Mießen, C., Tegeler, M., Barrales-Mora, L. A., Steinbach, I., & Gottstein, G. (2018). Computationally Efficient Phase-field Simulation Studies Using RVE Sampling and Statistical Analysis. Computational Materials Science, 147, 204-216. doi:10.1016/j.commatsci.2018.02.005. [PubMan] : Imran, M., Kühbach, M., Roters, F., & Bambach, M. (2017). Development of a Model for Dynamic Recrystallization Consistent with the Second Derivative Criterion. Materials, 10(11): 1259, pp. 1-18. doi:10.3390/ma10111259. [PubMan] : Diehl, M., Kühbach, M., Broß, C., & Raabe, D. (2017). Experimental-Numerical Analysis of Primary Recrystallization in DC04 Low Carbon Steel. Poster presented at Gordon Research Conference on Physical Metallurgy: Frontiers of Quantification and Predictive Capability in Physical Metallurgy, University of New England, Biddeford, ME, USA. [PubMan] : Haase, C., Kühbach, M., Barrales-Mora, L. A., Wong, S. L., Roters, F., Molodov, D. A., & Gottstein, G. (2015). Recrystallization behavior of a high-manganese steel: Experiments and simulations. Acta Materialia, 100, 155-168. doi:10.1016/j.actamat.2015.08.057. [PubMan]