D&D2 - Metal Alloys
Group Leaders
Related publications (until January 2020)
- Y. Hu, B. Szajewski, D. Rodney, W. Curtin, Atomistic dislocation core energies and calibration of non-singular discrete dislocation dynamics, Modelling and Simulation in Materials Science and Engineering 28, 015005 (2020).
Group(s): Curtin / Project(s): DD2 - P. Andric, B. Yin, W. A. Curtin, Stress-dependence of generalized stacking fault energies, Journal of the Mechanics and Physics of Solids 122, 262–279 (2019). [Open Access URL]
Dataset on Materials Cloud.
Group(s): Curtin / Project(s): DD2 - F. Musil, M. J. Willatt, M. A. Langovoy, M. Ceriotti, Fast and Accurate Uncertainty Estimation in Chemical Machine Learning, Journal of Chemical Theory and Computation 15, 906–915 (2019). [Open Access URL]
Group(s): Ceriotti, Jaggi / Project(s): DD2 - T. Würger, C. Feiler, F. Musil, G. B. V. Feldbauer, D. Höche, S. V. Lamaka, M. L. Zheludkevich, R. H. Meißner, Data Science Based Mg Corrosion Engineering, Frontiers in Materials 6, 53 (2019). [Open Access URL]
Group(s): Ceriotti / Project(s): DD2 - B. Yin, W. A. Curtin, First-principles-based prediction of yield strength in the RhIrPdPtNiCu high entropy alloy, npj Computational Materials 5, 14 (2019). [Open Access URL]
Dataset on Materials Cloud.
Group(s): Curtin / Project(s): DD2 - F. Maresca, D. Dragoni, G. Csányi, N. Marzari, W. A. Curtin, Screw dislocation structure and mobility in body centered cubic Fe predicted by a Gaussian Approximation Potential, npj Computational Materials 4, 69 (2018). [Open Access URL]
Group(s): Curtin, Marzari / Project(s): DD2 - M. J. Willatt, F. Musil, M. Ceriotti, Feature Optimization for Atomistic Machine Learning Yields a Data-Driven Construction of the Periodic Table of the Elements, Physical Chemistry Chemical Physics 20, 29661–29668 (2018). [Open Access URL]
Group(s): Ceriotti / Project(s): DD1, DD2