Publications of Markus Kühbach

Li, Y.; Wei, Y.; Saxena, A.; Kühbach, M.; Freysoldt, C.; Gault, B.: Machine learning enhanced atom probe tomography analysis. Progress in Materials Science 156, 101561 (2026)

Gault, B.; Saksena, A.; Sauvage, X.; Bagot, P.; Aota, L. S.; Arlt, J.; Belkacemi, L. T.; Boll, T.; Chen, Y.-S.; Daly, L. et al.; 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.: Towards Establishing Best Practice in the Analysis of Hydrogen and Deuterium by Atom Probe Tomography. Microscopy and Microanalysis 30 (6), pp. 1205 - 1220 (2024)

Saxena, A.; Kühbach, M.; Katnagallu, S.; Kontis, P.; Gault, B.; Freysoldt, C.: Analyzing Linear Features in Atom Probe Tomography Datasets using Skeletonization. Microscopy and Microanalysis 30 (Supplement_1), ozae044.022 (2024)

Zhou, X.; Wei, Y.; Kühbach, M. T.; Zhao, H.; Vogel, F.; Kamachali, R. D.; Thompson, G. B.; Raabe, D.; Gault, B.: Revealing in-plane grain boundary composition features through machine learning from atom probe tomography data. Acta Materialia 226, 117633 (2022)

Kühbach, M. T.; Bajaj, P.; Zhao, H.; Çelik, M. H.; Jägle, E. A.; Gault, B.: On strong-scaling and open-source tools for analyzing atom probe tomography data. npj Computational Materials 7 (1), 21 (2021)

Kühbach, M. T.; Kasemer, M.; Gault, B.; Breen, A. J.: 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), pp. 1490 - 1508 (2021)

Kühbach, M. T.; London, A. J.; Wang, Jing, J.; Schreiber, D. K.; Mendez Martin, F.; Ghamarian, I.; Bilal, H.; Ceguerra, A. V.: Community-Driven Methods for Open and Reproducible Software Tools for Analyzing Datasets from Atom Probe Microscopy. Microscopy and Microanalysis, pp. 1 - 16 (2021)

Kühbach, M. T.; Roters, F.: 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 (2020)

Wei, Y.; Peng, Z.; Kühbach, M.; Breen, A. J.; Legros, M.; Larranaga, M.; Mompiou, F.; Gault, B.: 3D nanostructural characterisation of grain boundaries in atom probe data utilising machine learning methods. PLoS One 14 (11), e0225041 (2019)

Diehl, M.; Kühbach, M.: Coupled experimental-computational analysis of primary static recrystallization in low carbon steel. Modelling and Simulation in Materials Science and Engineering 28 (1), 014001 (2019)

Kühbach, M.; Bajaj, P.; Breen, A. J.; Jägle, E. A.; Gault, B.: On Strong Scaling Open Source Tools for Mining Atom Probe Tomography Data. Microscopy and Microanalysis 25 (S2 ), pp. 298 - 299 (2019)

Kühbach, M.; Breen, A. J.; Herbig, M.; Gault, B.: Building a Library of Simulated Atom Probe Data for Different Crystal Structures and Tip Orientations Using TAPSim. Microscopy and Microanalysis 25 (2), pp. 320 - 330 (2019)

Latypov, M. I.; Kühbach, M.; Beyerlein, I. J.; Stinville, J. C.; Tóth, L. S.; Pollock, T. M.; Kalidindi, S. R.: Application of chord length distributions and principal component analysis for quantification and representation of diverse polycrystalline microstructures. Materials Characterization 145, pp. 671 - 685 (2018)

Schwarze, C.; Kamachali, R. D.; Kühbach, M.; Mießen, C.; Tegeler, M.; Barrales-Mora, L. A.; Steinbach, I.; Gottstein, G.: Computationally Efficient Phase-field Simulation Studies Using RVE Sampling and Statistical Analysis. Computational Materials Science 147, pp. 204 - 216 (2018)

Imran, M.; Kühbach, M.; Roters, F.; Bambach, M.: Development of a Model for Dynamic Recrystallization Consistent with the Second Derivative Criterion. Materials 10 (11), 1259, pp. 1 - 18 (2017)

Haase, C.; Kühbach, M.; Barrales-Mora, L. A.; Wong, S. L.; Roters, F.; Molodov, D. A.; Gottstein, G.: Recrystallization behavior of a high-manganese steel: Experiments and simulations. Acta Materialia 100, pp. 155 - 168 (2015)

Saxena, A.; Polin, N.; Kühbach, M. T.; Katnagallu, S.; Kontis, P.; Gault, B.; Freysoldt, C.: A Machine Learning based Workflows to Quantify Atom Probe Tomography Data. Workshop "Frontiers of APT Physics, Data Processing, Analysis and Reconstruction“, Arlington, VA, USA (2024)

Diehl, M.; Kühbach, M.; Kertsch, L.; Traka, K.; Raabe, D.: Coupled Experimental–Computational Analysis of Primary Static Recrystallization in Low Carbon Steel. Seminar of the Department of Mechanical Science and Engineering of the University of Illinois, Urbana-Champaign, Il, USA (2019)

Diehl, M.; Kühbach, M.; Raabe, D.: Experimental–computational analysis of primary static recrystallizazion in DC04 steel. 9th International Conference on Multiscale Materials Modeling , Osaka, Japan (2018)

Kühbach, M.; Roters, F.; Imran, M.; Bambach, M.; Breen, A. J.; Gault, B.; Bajaj, P.; Zhao, H.: Scalable Quantifying of Evolving Descriptive Spatial Statistics in Full-Field Crystal Plasticity and Atom Probe Tomography. Institut für Metallkunde und Metallphysik, RWTH Aachen University, Aachen, Germany (2018)