Dresden 2020 – scientific programme
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MM: Fachverband Metall- und Materialphysik
MM 17: Computational Materials Modelling - Methods II
MM 17.1: Talk
Monday, March 16, 2020, 17:00–17:15, IFW D
Phase Transitions Investigated by Variationally Enhanced Sampling with Permutationally Invariant Collective Variables — •Bin Song1, Gareth Tribello2, Kurt Kremer1, and Omar Valsson1 — 1Max Planck Institute for Polymer Research, Mainz, Germany — 2Queen’s University of Belfast, Belfast, United Kingdom
Phase transitions are a common theme in our physical world, which are performed over various acts in crystallization of atomic or molecular crystals and transformations between various phases of nanoalloys or soft matters. These phenomena could affect catalytic activity of a catalyst, the bioavailability of a drug molecule, and the stability of metal structures. For understanding phase transitions, molecular dynamic (MD) simulations have become an indispensable tool that is versatile and capable to provide mechanistic insights. Despite the advancement of computing hardware and development of algorithms, the timescale of MD simulations is still limited. Our group has been developing Variationally Enhanced Sampling (VES) method to transcend this limit placed upon MD practitioners. VES builds a bespoke bias potential in the collective variable (CV) space to drive the systems to visit different states and achieve ergodicity, with the collective variables being functions of the configuration space. In this work, we have extended the functionality of VES to use local Permutationally Invariant Collective Variables in situations when global CVs are not viable. We demonstrate the merits of method through studies of phase transition of LJ clusters, and crystallization and melting of bulk sodium.