Suchergebnisse

Bienvenu, B.; Todorova, M.; Neugebauer, J.; Raabe, D.; Mrovec, M.; Lysogorskiy, Y.; Drautz, R.: Development of an atomic cluster expansion potential for iron and its oxides. npj Computational Materials 11 (1), 81 (2025)

Zhou, X.; Mathews, P.; Berkels, B.; Delis, W.; Saood, S.; Shamseldeen Ali Alhassan, A.; Keuter, P.; Schneider, J.; Korte-Kerzel, S.; Sandlöbes-Haut, S. et al.; Raabe, D.; Neugebauer, J.; Dehm, G.; Hickel, T.; Scheu, C.; Zhang, S.: Materials Design by Constructing Phase Diagrams for Defects. Advanced Materials 37 (3), 2402191 (2025)

Janßen, J.; George, J.; Geiger, J.; Bercx, M.; Wang, X.; Ertural, C.; Schaarschmidt, J.; Ganose, A. M.; Pizzi, G.; Hickel, T. et al.; Neugebauer, J.: A python workflow definition for computational materials design. Digital Discovery 4, S. 3149 - 3161 (2025)

Katnagallu, S.; Mattoso, S. H.; Zhao, H.; Kim, S.-H.; Yang, J.; Gault, B.; Freysoldt, C.; Neugebauer, J.: Electric field induced formation of a two-dimensional adatom gas on cryogenic Li surfaces. Physical Review B 112 (11), 115426 (2025)

Srinivas Varanasi, R.; Waseda, O.; Syed, F. W.; Prithiv, T. S.; Gault, B.; Neugebauer, J.; Ponge, D.: Temperature and misorientation-dependent austenite nucleation at ferrite grain boundaries in a medium manganese steel: role of misorientation-dependent grain boundary segregation. Acta Materialia 296, 121242 (2025)

Sung, M. Y.; Jang, T. J.; Song, S. Y.; Lee, G.; Ryou, K.; Oh, S.-H.; Lee, B.-J.; Choi, P.-P.; Neugebauer, J.; Grabowski, B. et al.; Körmann, F.; Ikeda, Y.; Zargaran, A.; Sohn, S. S.: Ultrastrong and ductile CoNiMoAl medium-entropy alloys enabled by L12 nanoprecipitate-induced multiple deformation mechanisms. Journal of Materials Science & Technology 225, S. 72 - 86 (2025)

Poul, M.; Huber, L.; Neugebauer, J.: Automated generation of structure datasets for machine learning potentials and alloys. npj Computational Materials 11 (1), 174 (2025)

Wu, C.; Gong, Y.; Liu, C.; Li, X.; Gizer, G.; Pistidda, C.; Körmann, F.; Ma, Y.; Neugebauer, J.; Raabe, D.: Hydrogen accommodation and its role in lattice symmetry in a TiNbZr medium-entropy alloy. Acta Materialia 288, 120852 (2025)

Janßen, J.; Taylor, M.; Yang, P.; Neugebauer, J.; Perez, D.: Executorlib – Up-scaling Python workflows for hierarchical heterogenous high-performance computing. The Journal of Open Source Software (JOSS) 10 (108), 7782 (2025)

Ghosh, S.; Ueltzen, K.; George, J.; Neugebauer, J.; Körmann, F.: Chemical ordering and magnetism in face-centered cubic CrCoNi alloy. npj Computational Materials 10 (1), 284 (2024)

Zhu, L.-F.; Körmann, F.; Chen, Q.; Selleby, M.; Neugebauer, J.; Grabowski, B.: Accelerating ab initio melting property calculations with machine learning: application to the high entropy alloy TaVCrW. npj Computational Materials 10 (1), 274 (2024)

Janßen, J.; Makarov, E.; Hickel, T.; Shapeev, A. V.; Neugebauer, J.: Automated optimization and uncertainty quantification of convergence parameters in plane wave density functional theory calculations. npj Computational Materials 10 (1), 263 (2024)

Menon, S.; Lysogorskiy, Y.; Knoll, A. L. M.; Leimeroth, N.; Poul, M.; Qamar, M.; Janssen, J.; Mrovec, M.; Rohrer, J.; Albe, K. et al.; Behler, J.; Drautz, R.; Neugebauer, J.: From electrons to phase diagrams with machine learning potentials using pyiron based automated workflows. npj Computational Materials 10 (1), 261 (2024)

Deißenbeck, F.; Surendralal, S.; Todorova, M.; Wippermann, S. M.; Neugebauer, J.: Revealing the Reaction Pathway of Anodic Hydrogen Evolution at Magnesium Surfaces in Aqueous Electrolytes. Journal of the American Chemical Society 146 (44), S. 30314 - 30319 (2024)

Tehranchi, A.; Zhang, S.; Zendegani, A.; Scheu, C.; Hickel, T.; Neugebauer, J.: Metastable defect phase diagrams as roadmap to tailor chemically driven defect formation. Acta Materialia 277, 120145 (2024)

Pei, Z.; Yin, J.; Neugebauer, J.; Jain, A.: Towards the holistic design of alloys with large language models. Nature Reviews Materials 9 (12), S. 840 - 841 (2024)

Waseda, O.; Hickel, T.; Neugebauer, J.: mamonca: magnetic Monte Carlo code. The Journal of Open Source Software (JOSS) 9 (100), 6194 (2024)

Li, Y.; Colnaghi, T.; Gong, Y.; Zhang, H.; Yu, Y.; Wei, Y.; Gan, B.; Song, M.; Marek, A.; Rampp, M. et al.; Zhang, S.; Pei, Z.; Wuttig, M.; Ghosh, S.; Körmann, F.; Neugebauer, J.; Wang, Z.; Gault, B.: Machine Learning-Enabled Tomographic Imaging of Chemical Short-Range Atomic Ordering. Advanced Materials 36 (44), 2407564 (2024)

Sasidhar, K. N.; Hamidi Siboni, N.; Mianroodi, J. R.; Rohwerder, M.; Neugebauer, J.; Raabe, D.: Enhancing corrosion-resistant alloy design through natural language processing and deep learning. Science Advances 9 (32), eadg7992 (2024)

Schwarz, T.; Yang, J.; Aota, L. S.; Woods, E.; Zhou, X.; Neugebauer, J.; Todorova, M.; McCarroll, I.; Gault, B.: Quasi-“In Situ” Analysis of the Reactive Liquid-Solid Interface during Magnesium Corrosion Using Cryo-Atom Probe Tomography. Advanced Materials 36 (32), 2401735 (2024)