Density Functional Tight-Binding Theory: Its Use in Metadynamics Molecular Dynamics Simulation and in Studying Magnetic Property of Carbon Clusters

Project Details

Description

In this project, we aim at two specific themes. The first theme concerns with developing a simulation scheme so thatkinetic problems such as the high barriers between metastable states which lead to significantly longer timescales can becircumvented. The metadynamics simulation is one of the numerous enhanced sampling methods and will betheoretically studied and implemented in the present project. Instead of working along the line of ab initio Born-Oppenheimer molecular dynamics (MD) approach which is computationally tedious and expensive, we propose tocombine the density functional tight-binding (DFTB) theory and the Brownian MD method developed previously by us.The former is employed to calculate the energy EDFTB of a cluster which together with the latter constitute theconventional canonical MD simulation (Nosé–Hoover thermostat), but the configuration space will be replaced by acollective variable space. We shall amend EDFTB of the canonical MD simulation algorithm with a history dependentpotential VG thereby constructing the biased potential (EDFTB+ VG) to be in the metadynamics simulation. In this project,we perform the metadynamics MD simulation for the cluster An consisting of a number n of Au atoms. Both the freeenergy surface and potential energy surface of Aun in the collective variable space will constructed and analyzed inparticular the issue of the bidimensional to tridimensional transition. The second theme is about the magnetism of Cnclusters. We shall investigate in this context using a generalized DFTB theory to calculate EDFTB, combine it with anelegant optimization algorithm developed by our group and carry out a systematic study of the magnetism of Cn. A uniquefeature of using the generalized DFTB theory is that the three entities, spin states, valence electrons and ions, are alltreated on an equal footing during the course of energy optimization.
StatusFinished
Effective start/end date1/08/1731/01/19

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 11 - Sustainable Cities and Communities
  • SDG 16 - Peace, Justice and Strong Institutions
  • SDG 17 - Partnerships for the Goals

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