A global reaction route mapping-based kinetic Monte Carlo algorithm | Zendy

Izaac Mitchell | Zendy; Stephan Irle | Zendy; Alister J. Page | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

A global reaction route mapping-based kinetic Monte Carlo algorithm

Author(s) -

Izaac Mitchell,

Stephan Irle,

Alister J. Page

Publication year - 2016

Publication title -

the journal of chemical physics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.071

H-Index - 357

eISSN - 1089-7690

pISSN - 0021-9606

DOI - 10.1063/1.4954660

Subject(s) - kinetic monte carlo , transition state theory , potential energy surface , monte carlo method , reaction coordinate , diffusion monte carlo , statistical physics , transition state , diffusion , density functional theory , molecular dynamics , quantum monte carlo , dynamic monte carlo method , chemistry , kinetic energy , kinetics , reaction rate constant , computational chemistry , monte carlo molecular modeling , physics , thermodynamics , mathematics , molecule , catalysis , quantum mechanics , biochemistry , statistics , organic chemistry , markov chain monte carlo

We propose a new on-the-fly kinetic Monte Carlo (KMC) method that is based on exhaustive potential energy surface searching carried out with the global reaction route mapping (GRRM) algorithm. Starting from any given equilibrium state, this GRRM-KMC algorithm performs a one-step GRRM search to identify all surrounding transition states. Intrinsic reaction coordinate pathways are then calculated to identify potential subsequent equilibrium states. Harmonic transition state theory is used to calculate rate constants for all potential pathways, before a standard KMC accept/reject selection is performed. The selected pathway is then used to propagate the system forward in time, which is calculated on the basis of 1st order kinetics. The GRRM-KMC algorithm is validated here in two challenging contexts: intramolecular proton transfer in malonaldehyde and surface carbon diffusion on an iron nanoparticle. We demonstrate that in both cases the GRRM-KMC method is capable of reproducing the 1st order kinetics observed during independent quantum chemical molecular dynamics simulations using the density-functional tight-binding potential

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research