Berlin 2018 – scientific programme
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MM: Fachverband Metall- und Materialphysik
MM 52: Methods in Computational Materials Modelling (methodological aspects, numerics)
MM 52.3: Talk
Thursday, March 15, 2018, 10:45–11:00, TC 006
One shot calculation of multicomponent phase diagrams with combined umbrella and nested sampling — •Robert Baldock1, Christopher Sutton2, Luca Ghiringhelli2, and Nicola Marzari1 — 1Theory and Simulation of Materials (THEOS), and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), EPFL, Switzerland — 2Fritz-Haber-Institut der Max-Planck-Gesellschaft, Berlin, Germany
The automated calculation of complete phase diagrams, directly from a first-principles or empirical potential energy function, is one of the outstanding challenges in computational materials science. Here we show how nested sampling, a Bayesian Markov chain Monte Carlo algorithm, can be transformed into a powerful tool for exactly this task. In particular, the introduction of umbrella sampling within nested sampling enables the efficient, one-shot calculation of composition-temperature phase diagrams, including for materials that exhibit a miscibility gap whereby the material separates into domains of different composition. Since our nested sampling algorithm does not require previous information about the location of phase transitions, or the atomic structures of phases formed by the material, it can be used as a black-box tool for phase diagram calculation. I will showcase the efficacy of the approach by presenting the binary phase diagrams of a Lennard-Jones alloy (continuous atomistic state space) and gallium indium phosphide as described using a lattice model (discrete atomistic state space).