Publications

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)

Hachet, G.; Tehranchi, A.; Shi, H.; Prabhakar, J. M.; Wei, S.; Angenendt, K.; Zaefferer, S.; Gault, B.; Sun, B.; Ponge, D. et al.; Raabe, D.: Segregation at prior austenite grain boundaries: The competition between boron and hydrogen. International Journal of Hydrogen Energy 95, pp. 734 - 746 (2024)

Xu, X.; Zhang, X.; Bitzek, E.; Schmauder, S.; Grabowski, B.: Origin of the yield stress anomaly in L12 intermetallics unveiled with physically informed machine-learning potentials. Acta Materialia 281, 120423 (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)

Liu, C.; Rao, J.; Sun, Z.; Lu, W.; Best, J. P.; Li, X.; Xia, W.; Gong, Y.; Wei, Y.; Zhang, B. et al.; Ding, J.; Wu, G.; Ma, E.: Near-theoretical strength and deformation stabilization achieved via grain boundary segregation and nano-clustering of solutes. Nature Communications 15, 9283 (2024)

Geng, X.; Vega-Paredes, M.; Wang, Z.; Ophus, C.; Lu, P.; Ma, Y.; Zhang, S.; Scheu, C.; Liebscher, C.; Gault, B.: Grain boundary engineering for efficient and durable electrocatalysis. Nature Communications 15, 8534 (2024)

Pei, Z.; Gong, Y.; Liu, X.; Yin, J.: Designing complex concentrated alloys with quantum machine learning and language modeling. Matter 7, pp. 3433 - 3446 (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), pp. 30314 - 30319 (2024)

Sevlikar, S. V.; Muralikrishna, G. M.; Gaertner, D.; Starikov, S.; Brink, T.; Scheiber, D.; Smirnova, D.; Irmer, D.; Tas, B.; Esin, V. A. et al.; Razumovskiy, V. I.; Liebscher, C.; Wilde, G.; Divinski, S. V.: Grain boundary diffusion and segregation of Cr in Ni Σ11(1̄13)[110] bicrystals: Decoding the role of grain boundary defects. Acta Materialia 278, 120229 (2024)

Xie, Z.; Chauraud, D.; Bitzek, E.; Korte-Kerzel, S.; Guénolé, J.: On the Temperature and Composition Dependence of Non-basal Stacking Faults in C14 Laves Phases. Advanced Engineering Materials 26 (20), 2400885 (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), pp. 840 - 841 (2024)

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)

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)

France-Lanord, A.; Menon, S.; Lam, J.: Harvesting nucleating structures in nanoparticle crystallization: The example of gold, silver, and iron. The Journal of Chemical Physics 161 (4), 044108 (2024)