Freysoldt, C.; Katnagallu, S.; Neugebauer, J.; Mishra, A.; Ashton, M. W.: Perspectives for machine learning applied to data-rich experiments on complex materials. Workshop on local probes of chemical bonding and atom probe tomography at RWTH Aachen, Aachen, Germany (2024)

Neugebauer, J.; Deißenbeck, F.; Wippermann, S. M.; Todorova, M.: Getting the Electrochemical Interface into an Ab Initio Supercell. CECAM workshop "Electrochemical Interfaces in Energy Storage: Advances in Simulations, Methods and Models", Lausanne, Switzerland (2024)

Neugebauer, J.; Deißenbeck, F.; Wippermann, S. M.; Todorova, M.: Unveiling Fundamental Reaction Mechanisms at the Electrochemical Interface by Ab Initio Simulations. 245th ECS Meeting, San Francisco, CA, USA (2024)

Neugebauer, J.; Menon, S.: Maximizing High-Throughput Discovery and Machine Learning Efficiency Through Computational Workflows. Machine Learning Modalities for Materials science, Ljubljana, Slovenia (2024)

Todorova, M.; Yang, J.; Surendralal, S.; Yoo, S.-H.; Deißenbeck, F.; Wippermann, S. M.; Neugebauer, J.: Insights into Atomistic Processes at Electrified Solid/Liquid Interfaces from Ab Initio Calculations. 245th ECS Meeting, San Francisco, CA, USA (2024)

Neugebauer, J.; Tehranchi, A.; Mathews, P.; Yang, J.; Todorova, M.; Hickel, T.: Metastable Defect Phase Diagrams as a road map for defect design. FLAIR Colloquium talk, Technical University Darmstadt, Darmstadt, Germany (2024)

Todorova, M.; Yoo, S.-H.; Yang, J.; Surendralal, S.; Deißenbeck, F.; Wippermann, S. M.; Neugebauer, J.: First-principles modelling of electrified solid-liquid interfaces – from reaction mechanisms to synthesis. First-principles modeling and machine learning approaches in simulations of technologically relevant materials, Linköping, Sweden (2024)

Bitzek, E.; Eggle-Sievers, B.: Screw Dislocations and Crack-Tip Plasticity in Tungsten: an Atomistic Study. Colloque Plasticité, Marseille, France (2024)

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)

Bitzek, E.: An atomistic Perspective on Fracture Toughness of inorganic Materials. FRASCAL Colloquium, Erlangen, Germany (2024)

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)

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)

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)

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)

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)

Zhu, L.-F.: Method developments on melting property calculations and further applications. 4th German-Austrian Workshop, Kirchdorf, Austria (2024)

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)

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)

Neugebauer, J.: Boosting ab initio-based materials discovery by machine learning. AI MSE 2023 - Artificial Inteligence in Materials Science and Engineering, Saarbrücken, Germany (2023)

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)