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Publications of Jörg Neugebauer

Journal Article (314)

1.
Journal Article
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)
2.
Journal Article
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)
3.
Journal Article
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. Physical Review Materials 7, 095802 (2023)
4.
Journal Article
Bhatt, S.; Katnagallu, S.; Neugebauer, J.; Freysoldt, C.: Accurate computation of chemical contrast in field ion microscopy. Physical Review B 107 (23), 235413 (2023)
5.
Journal Article
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)
6.
Journal Article
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)
7.
Journal Article
Poul, M.; Huber, L.; Bitzek, E.; Neugebauer, J.: Systematic atomic structure datasets for machine learning potentials: Application to defects in magnesium. Physical Review B 107, 104103 (2023)
8.
Journal Article
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)
9.
Journal Article
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)
10.
Journal Article
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)
11.
Journal Article
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)
12.
Journal Article
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)
13.
Journal Article
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)
14.
Journal Article
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)
15.
Journal Article
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)
16.
Journal Article
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)
17.
Journal Article
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)
18.
Journal Article
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)
19.
Journal Article
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)
20.
Journal Article
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)
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