Publications of Jörg Neugebauer

Li, Y.; Wei, Y.; Wang, Z.; Liu, X.; Colnaghi, T.; Han, L.; Rao, Z.; Zhou, X.; Huber, L.; Dsouza, R. et al.; Gong, Y.; Neugebauer, J.; Marek, A.; Rampp, M.; Bauer, S.; Li, H.; Baker, I.; Stephenson, L.; Gault, B.: Quantitative three-dimensional imaging of chemical short-range order via machine learning enhanced atom probe tomography. Nature Communications 14 (1), 7410 (2023)

Saxena, A.; Polin, N.; Kusampudi, N.; Katnagallu, S.; Molina-Luna, L.; Gutfleisch, O.; Berkels, B.; Gault, B.; Neugebauer, J.; Freysoldt, C.: A Machine Learning Framework for Quantifying Chemical Segregation and Microstructural Features in Atom Probe Tomography Data. Microscopy and Microanalysis 29 (5), pp. 1658 - 1670 (2023)

Bhatt, S.; Katnagallu, S.; Neugebauer, J.; Freysoldt, C.: Accurate computation of chemical contrast in field ion microscopy. Physical Review B 107 (23), 235413 (2023)

Ferrari, A.; Körmann, F.; Asta, M. D.; Neugebauer, J.: Simulating short-range order in compositionally complex materials. Nature Computational Science 3 (3), pp. 221 - 229 (2023)

Raabe, D.; Mianroodi, J. R.; Neugebauer, J.: Accelerating the design of compositionally complex materials via physics-informed artificial intelligence. Nature Computational Science 3 (3), pp. 198 - 209 (2023)

Sözen, H. I.; Ener, S.; Maccari, F.; Fayyazi, B.; Gutfleisch, O.; Neugebauer, J.; Hickel, T.: Combined ab initio and experimental screening of phase stabilities in the Ce–Fe–Ti–X system (X=3d and 4d metals). Physical Review Materials 7 (1), 014410 (2023)

Katnagallu, S.; Freysoldt, C.; Gault, B.; Neugebauer, J.: Ab initio vacancy formation energies and kinetics at metal surfaces under high electric field. Physical Review B 107 (4), L041406 (2023)

Srinivasan, P.; Shapeev, A.; Neugebauer, J.; Körmann, F.; Grabowski, B.: Anharmonicity in bcc refractory elements: A detailed ab initio analysis. Physical Review B 107 (1), 014301 (2023)

Tehranchi, A.; Zhang, S.; Zendegani, A.; Scheu, C.; Hickel, T.; Neugebauer, J.: Metastable defect phase diagrams as a tool to describe chemically driven defect formation: Application to planar defects. arXiv preprint arXiv:2303.07504 (2023)

Ghosh, S.; Sotskov, V.; Shapeev, A.; Neugebauer, J.; Körmann, F.: Short-range order and phase stability of CrCoNi explored with machine learning potentials. Physical Review Materials 6 (11), 113804 (2022)

Rao, Z.; Tung, P.-Y.; Xie, R.; Wei, Y.; Zhang, H.; Ferrari, A.; Klaver, T. P. C.; Körmann, F.; Prithiv, T. S.; Kwiatkowski da Silva, A. et al.; Chen, Y.; Li, Z.; Ponge, D.; Neugebauer, J.; Gutfleisch, O.; Bauer , S.; Raabe, D.: Machine learning–enabled high-entropy alloy discovery. Science 378 (6615), pp. 78 - 85 (2022)

Tehranchi, A.; Chakraborty, P.; López Freixes, M.; McEniry, E.; Gault, B.; Hickel, T.; Neugebauer, J.: Tailoring negative pressure by crystal defects: Crack induced hydride formation in Al alloys. Condensed Matter: Materials Science (2022)

Chakraborty, P.; Mouton, I.; Gault, B.; Tehranchi, A.; Neugebauer, J.; Hickel, T.: Effect of Sn on Generalized Stacking Fault Energy Surfaces in Zirconium and its Hydrides. Condensed Matter: Materials Science (2022)

Sasidhar, K. N.; Hamidi Siboni, N.; Mianroodi, J. R.; Rohwerder, M.; Neugebauer, J.; Raabe, D.: Deep learning framework for uncovering compositional and environmental contributions to pitting resistance in passivating alloys. npj Materials Degradation 6 (1), 71 (2022)

Kumar, K. B. S.; Todorova, M.; Neugebauer, J.: Construction and analysis of surface phase diagrams to describe segregation and dissolution behavior of Al and Ca in Mg alloys. Condensed Matter: Materials Science (2022)

Poul, M.; Huber, L.; Bitzek, E.; Neugebauer, J.: Systematic Structure Datasets for Machine Learning Potentials: Application to Moment Tensor Potentials of Magnesium and its Defects. Condensed Matter: Materials Science (2022)

Dsouza, R.; Huber, L.; Grabowski, B.; Neugebauer, J.: Approximating the impact of nuclear quantum effects on thermodynamic properties of crystalline solids by temperature remapping. Physical Review B 105 (18), 184111 (2022)

Mendive-Tapia, E.; Neugebauer, J.; Hickel, T.: Ab initio calculation of the magnetic Gibbs free energy of materials using magnetically constrained supercells. Physical Review B 105 (16), 064425 (2022)

Yoo, S.-H.; Kim, S.-H.; Woods, E.; Gault, B.; Todorova, M.; Neugebauer, J.: Origins of the hydrogen signal in atom probe tomography: case studies of alkali and noble metals. New Journal of Physics 24, 013008 (2022)

Sreekala, L.; Dey, P.; Hickel, T.; Neugebauer, J.: Unveiling nonmonotonic chemical trends in the solubility of H in complex Fe–Cr–Mn carbides by means of ab initio based approaches. Physical Review Materials 6 (1), 014403 (2022)