Journal Article (27)

1. 2020
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   Litman, Y.; Behler, J.; Rossi, M.: Temperature dependence of the vibrational spectrum of porphycene: a qualitative failure of classical-nuclei molecular dynamics. Faraday Discussions 221, pp. 526 - 546 (2020)
2. 2019
   MPG.PuRe

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   Bartel, C. J.; Sutton, C. A.; Goldsmith, B. R.; Ouyang, R.; Musgrave, C. B.; Ghiringhelli, L. M.; Scheffler, M.: New tolerance factor to predict the stability of perovskite oxides and halides. Science Advances 5 (2) (2019)
3. MPG.PuRe

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   Diehl, M.; Kühbach, M.: Coupled experimental-computational analysis of primary static recrystallization in low carbon steel. Modelling and Simulation in Materials Science and Engineering 28 (1), 014001 (2019)
4. MPG.PuRe

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   Draxl, C.; Scheffler, M.: The NOMAD Laboratory: From Data Sharing to Artificial Intelligence. JPhys Materials 2 (3) (2019)
5. MPG.PuRe

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   Gebhard, T. D.; Kilbertus, N.; Harry, I.; Schölkopf, B.: Convolutional neural networks: A magic bullet for gravitational-wave detection? Physical Review D 100 (6), 063015 (2019)
6. MPG.PuRe

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   Goldsmith, B.; Florian, J.; Liu, J.-X.; Grüne, P.; Lyon, J. T.; Rayner, D. M.; Fielicke, A.; Scheffler, M.; Ghiringhelli, L. M.: Two-to-three dimensional transition in neutral gold clusters: The crucial role of van der Waals interactions and temperature. Physical Review Materials 3 (1) (2019)
7. MPG.PuRe

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   Janßen, J.; Surendralal, S.; Lysogorskiy, Y.; Todorova, M.; Hickel, T.; Drautz, R.; Neugebauer, J.: pyiron: An integrated development environment for computational materials sciences. Computational Materials Science 163, pp. 24 - 36 (2019)
8. MPG.PuRe

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   pre-print
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   Kapil, V.; Engel, E.; Rossi, M.; Ceriotti, M.: Assessment of Approximate Methods for Anharmonic Free Energies. Journal of Chemical Theory and Computation 15 (11), pp. 5845 - 5857 (2019)
9. MPG.PuRe

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   Kontis, P.; Chauvet, E.; Peng, Z.; He, J.; Kwiatkowski da Silva, A.; Raabe, D.; Tassin, C.; Blandin, J.-J.; Abed, S.; Dendievel, R. et al.; Gault, B.; Martin, G.: Atomic-scale grain boundary engineering to overcome hot-cracking in additively-manufactured superalloys. Acta Materialia 177, pp. 209 - 221 (2019)
10. MPG.PuRe

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    Kühbach, M.; Breen, A. J.; Herbig, M.; Gault, B.: Building a Library of Simulated Atom Probe Data for Different Crystal Structures and Tip Orientations Using TAPSim. Microscopy and Microanalysis 25 (2), pp. 320 - 330 (2019)
11. MPG.PuRe

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    Kühbach, M.; Bajaj, P.; Breen, A. J.; Jägle, E. A.; Gault, B.: On Strong Scaling Open Source Tools for Mining Atom Probe Tomography Data. Microscopy and Microanalysis 25 (S2 ), pp. 298 - 299 (2019)
12. MPG.PuRe

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    Lenz, M.-O.; Purcell, T.; Hicks, D.; Curtarolo, S.; Scheffler, M.; Carbogno, C.: Parametrically constrained geometry relaxations for high-throughput materials science. npj Computational Materials 5 (2019)
13. MPG.PuRe

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    Lysogorskiy, Y.; Hammerschmidt, T.; Janßen, J.; Neugebauer, J.; Drautz, R.: Transferability of interatomic potentials for molybdenum and silicon. Modelling and Simulation in Materials Science and Engineering 27 (2), 025007 (2019)
14. MPG.PuRe

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    Ouyang, R.; Ahmetcik, E.; Carbogno, C.; Scheffler, M.; Ghiringhelli, L. M.: Simultaneous learning of several materials properties from incomplete databases with multi-task SISSO. JPhys Materials 2 (2) (2019)
15. MPG.PuRe

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    Peng, Z.; Zanuttini, D.; Gervais, B.; Jacquet, E.; Blum, I.; Choi, P.-P.; Raabe, D.; Vurpillot, F.; Gault, B.: Unraveling the Metastability of C_n²⁺ (n = 2-4) Clusters. The Journal of Physical Chemistry Letters 10 (3), pp. 581 - 588 (2019)
16. MPG.PuRe

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    Peng, Z.; Lu, Y.; Hatzoglou, C.; Kwiatkowski da Silva, A.; Vurpillot, F.; Ponge, D.; Raabe, D.; Gault, B.: An Automated Computational Approach for Complete In-Plane Compositional Interface Analysis by Atom Probe Tomography. Microscopy and Microanalysis 25 (2), pp. 389 - 400 (2019)
17. MPG.PuRe

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    Schilling, C.; Mack, T.; Lickfett, S.; Sieste, S.; Ruggeri, F. S.; Šneideris, T.; Dutta, A.; Bereau, T.; Naraghi, R.; Sinske, D. et al.; Knowles, T. P. J.; Synatschke, C. V.; Weil, T.; Knöll, B.: Sequence-Optimized Peptide Nanofibers as Growth Stimulators for Regeneration of Peripheral Neurons. Advanced Functional Materials 29 (24), 1809112 (2019)
18. MPG.PuRe

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    Stimper, V.; Bauer, S.; Ernstorfer, R.; Schölkopf, B.; Xian, R. P.: Multidimensional Contrast Limited Adaptive Histogram Equalization. IEEE Access 7 (2019)
19. MPG.PuRe

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    Wei, Y.; Peng, Z.; Kühbach, M.; Breen, A. J.; Legros, M.; Larranaga, M.; Mompiou, F.; Gault, B.: 3D nanostructural characterisation of grain boundaries in atom probe data utilising machine learning methods. PLoS One 19, pp. 1 - 19 (2019)
20. 2018
    MPG.PuRe

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    Budhathoki, K.; Vreeken, J.: Origo: Causal Inference by Compression. Knowledge and Information Systems 56 (2), pp. 285 - 307 (2018)
21. MPG.PuRe

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    Draxl, C.; Scheffler, M.: NOMAD: The FAIR concept for big data-driven materials science. MRS Bulletin 43 (9), pp. 676 - 682 (2018)
22. MPG.PuRe

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    supplementary-material

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    Ouyang, R.; Curtarolo, S.; Ahmetcik, E.; Scheffler, M.; Ghiringhelli, L. M.: SISSO: a compressed-sensing method for identifying the best low-dimensional descriptor in an immensity of offered candidates. Physical Review Materials 2 (08) (2018)
23. MPG.PuRe

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    Peng, Z.; Vurpillot, F.; Choi, P.-P.; Li, Y.; Raabe, D.; Gault, B.: On the detection of multiple events in atom probe tomography. Ultramicroscopy 189, pp. 54 - 60 (2018)
24. MPG.PuRe

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    Shang, H.; Raimbault, N.; Rinke, P.; Scheffler, M.; Rossi, M.; Carbogno, C.: All-electron, real-space perturbation theory for homogeneous electric fields: theory, implementation, and application within DFT. New Journal of Physics 20 (7) (2018)
25. MPG.PuRe

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    Ziletti, A.; Kumar, D.; Scheffler, M.; Ghiringhelli, L. M.: Insightful classification of crystal structures using deep learning. Nature Communications 9 (2018)