Exploration of materials fatigue influence factors using interpretable machine learning von Frie, Christian, Riza Durmaz, Ali, Eberl, Chris

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Reduction of testing effort for fatigue tests: Application of Bayesian optimal experimental design von Frie, Christian, Kolyshkin, Anton, Mordeja, Sven, Riza Durmaz, Ali, Eberl, Chris

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A deep learning approach for complex microstructure inference von Durmaz, Ali Riza, Müller, Martin, Lei, Bo, Thomas, Akhil, Britz, Dominik, Holm, Elizabeth A., Eberl, Chris, Mücklich, Frank, Gumbsch, Peter

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Materials fatigue prediction using graph neural networks on microstructure representations von Thomas, Akhil, Durmaz, Ali Riza, Alam, Mehwish, Gumbsch, Peter, Sack, Harald, Eberl, Chris

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Influence of Transformation Temperature on the High‐Cycle Fatigue Performance of Carbide‐Bearing and Carbide‐Free Bainite von Gulbay, Oguz, Ackermann, Marc, Gramlich, Alexander, Durmaz, Ali Riza, Steinbach, Ingo, Krupp, Ulrich

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Author Correction: Materials fatigue prediction using graph neural networks on microstructure representations von Thomas, Akhil, Durmaz, Ali Riza, Alam, Mehwish, Gumbsch, Peter, Sack, Harald, Eberl, Chris

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An ontology-based text mining dataset for extraction of process-structure-property entities von Durmaz, Ali Riza, Thomas, Akhil, Mishra, Lokesh, Murthy, Rachana Niranjan, Straub, Thomas

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Addressing materials’ microstructure diversity using transfer learning von Goetz, Aurèle, Durmaz, Ali Riza, Müller, Martin, Thomas, Akhil, Britz, Dominik, Kerfriden, Pierre, Eberl, Chris

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Thermal characterization of epitaxial grown polycrystalline silicon von Liebchen, Robert, Breitschädel, Oliver, Durmaz, Ali Riza, Griesinger, Andreas

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Microstructure quality control of steels using deep learning von Durmaz, Ali Riza, Potu, Sai Teja, Romich, Daniel, Möller, Johannes J., Nützel, Ralf

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Efficient reconstruction of prior austenite grains in steel from etched light optical micrographs using deep learning and annotations from correlative microscopy von Bachmann, Björn-Ivo, Müller, Martin, Britz, Dominik, Durmaz, Ali Riza, Ackermann, Marc, Shchyglo, Oleg, Staudt, Thorsten, Mücklich, Frank

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Optically Pumped Magnetometer Measuring Fatigue-Induced Damage in Steel von Koss, Peter A., Durmaz, Ali Riza, Blug, Andreas, Laskin, Gennadii, Pawar, Omkar Satish, Thiemann, Kerstin, Bertz, Alexander, Straub, Thomas, Elsässer, Christian

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Automated Quantitative Analyses of Fatigue-Induced Surface Damage by Deep Learning von Thomas, Akhil, Durmaz, Ali Riza, Straub, Thomas, Eberl, Chris

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Fatigue lifetime prediction with a validated micromechanical short crack model for the ferritic steel EN 1.4003 von Natkowski, Erik, Durmaz, Ali Riza, Sonnweber-Ribic, Petra, Münstermann, Sebastian

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Micromechanical fatigue experiments for validation of microstructure-sensitive fatigue simulation models von Durmaz, Ali Riza, Natkowski, Erik, Arnaudov, Nikolai, Sonnweber-Ribic, Petra, Weihe, Stefan, Münstermann, Sebastian, Eberl, Chris, Gumbsch, Peter

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MaterioMiner -- An ontology-based text mining dataset for extraction of process-structure-property entities von Durmaz, Ali Riza, Thomas, Akhil, Mishra, Lokesh, Murthy, Rachana Niranjan, Straub, Thomas

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Microstructure quality control of steels using deep learning von Durmaz, Ali Riza, Potu, Sai Teja, Romich, Daniel, Möller, Johannes, Nützel, Ralf

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Experimental and Computational Micromechanical Fatigue Damage Initiation Data von Durmaz, Ali Riza, Natkowski, Erik

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Addressing materials' microstructure diversity using transfer learning von Goetz, Aurèle, Durmaz, Ali Riza, Müller, Martin, Thomas, Akhil, Britz, Dominik, Kerfriden, Pierre, Eberl, Chris

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Micromechanical fatigue experiments for validation of microstructure-sensitive fatigue simulation models von Durmaz, Ali Riza, Natkowski, Erik, Arnaudov, Nikolai, Sonnweber-Ribic, Petra, Weihe, Stefan, Münstermann, Sebastian, Eberl, Chris, Gumbsch, Peter

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