Vortrag (1226)

641.
Vortrag
Freysoldt, C.; Saxena, A.; Wang, N.; Sreekala, L.; Saikia, U.: Perspectives for machine learning applied to data-rich experiments on complex materials. Kolloquium Transregio 270 at Universität Duisburg-Essen, Duisburg, Germany (2024)
642.
Vortrag
Bitzek, E.: An atomistic Perspective on Fracture Toughness of inorganic Materials. FRASCAL Colloquium, Erlangen, Germany (2024)
643.
Vortrag
Feng, S.; Gong, Y.; Neugebauer, J.; Raabe, D.; Liotti, E.; Grant, P. S.: Multi-technique investigation of Fe-rich intermetallic compounds for more impurity-tolerant Al alloys. Annual Meeting of DPG and DPG-Frühjahrstagung (DPG Spring Meeting) of the Condensed Matter Section (SKM) 2024, Berlin, Germany (2024)
644.
Vortrag
Neugebauer, J.; Tehranchi, A.; Mathews, P.; Yang, J.; Todorova, M.; Hickel, T.: Metastable Defect Phase Diagrams as a road map for defect design. TMS Annual Meeting, Orlando, FL, USA (2024)
645.
Vortrag
Todorova, M.; Surendralal, S.; Yang, J.; Deißenbeck, F.; Wippermann, S. M.; Neugebauer, J.: Ab initio insights into atomistic processes at electrified solid/liquid interface. DPG Spring Meeting, Berlin, Germany (2024)
646.
Vortrag
Todorova, M.; Surendralal, S.; Yang, J.; Neugebauer, J.: Using ab initio calculations to unravel atomistic processes at electrified solid/ liquid interfaces. 63rd Sanibel Symposium, St. Augustine, FL, USA (2024)
647.
Vortrag
Neugebauer, J.; Deißenbeck, F.; Wippermann, S. M.; Todorova, M.: Discovery of Fundamental Reaction Mechanisms at Electrochemical Interfaces by Quantum Simulations. 63rd Sanibel Symposium, St. Augustine, FL, USA (2024)
648.
Vortrag
Zhu, L.-F.: Method developments on melting property calculations and further applications. 4th German-Austrian Workshop, Kirchdorf, Austria (2024)
649.
Vortrag
Neugebauer, J.: Boosting ab initio-based materials discovery by machine learning. MPCDF Workshop “High-performance computing, artificial intelligence, and data-intensive applications in the Max-Planck Society”, Schloss Ringberg, Tegernsee, Germany (2023)
650.
Vortrag
Zhou, X.; Ahmadian, A.; Hickel, T.; Gault, B.; Ophus, C.; Liebscher, C.; Dehm, G.; Raabe, D.: Atomic Scale Analysis Reveals the Interplay between Grain Boundary Structure and Composition. MRS 2023, Boston, MA, USA (2023)
651.
Vortrag
Neugebauer, J.: Boosting ab initio-based materials discovery by machine learning. AI MSE 2023 - Artificial Inteligence in Materials Science and Engineering, Saarbrücken, Germany (2023)
652.
Vortrag
Todorova, M.; Surendralal, S.; Deißenbeck, F.; Wippermann, S. M.; Neugebauer, J.: Insights into electrochemical solid/liquid interfaces under potential control from first principles and atomistic calculations. TACO Colloquium, Universität Wien, Vienna, Austria (2023)
653.
Vortrag
Bitzek, E.: Towards High-Throughput Atomistic Microstructure – Mechanics Simulations. Ab initio Description of Iron and Steel (ADIS2023): Digitalization and Workflows, Schloss Ringberg, Germany (2023)
654.
Vortrag
Bitzek, E.: Atomistic Simulations, Mesoscale Modelling and Micromechanical Testing of Crack – Microstructure Interactions. XVII International Conference on Computational Plasticity, Fundamentals and Applications (COMPLAS 2023), Barcelona, Spain (2023)
655.
Vortrag
Freysoldt, C.; Katnagallu, S.; Bhatt, S.; Saxena, A.; Ashton, M. W.: Pushing the limits of APT and FIM by pushing theoretical approaches. APT & M 2023, Leuven, Belgium (2023)
656.
Vortrag
Neugebauer, J.; Freysoldt, C.; Todorova, M.; Van de Walle, C. G.: Charged defects in semiconductors and beyond. 32nd International Conference on Defects in Semiconductors, Rehoboth Beach, DE, USA (2023)
657.
Vortrag
Neugebauer, J.; Körmann, F.; Ferrari, A.: Navigating and exploiting the high-dimensional configuration spaces of high entropy alloys. The 11th International Conference on Multiscale Materials Modeling, Prague, Czech Republic (2023)
658.
Vortrag
Zhu, L.-F.: Towards high throughput melting property calculations with ab initio accuracy aided by machine learning potential. The third generation (3G) Calphad at KTH, Stockholm, Sweden (2023)
659.
Vortrag
Freysoldt, C.; Saxena, A.; Wang, N.; Sreekala, L.: Perspectives for machine learning applied to data-rich experiments on complex materials. Materials Chain International Conference, Bochum, Germany (2023)
660.
Vortrag
Neugebauer, J.: Capturing the chemical complexity of HEAs by ab initio based modelling. CHEAC Summer School 2023 - High Entropy Materials and their properties, Metalskolen-Jørlunde, Denmark (2023)
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