DL_MONTE

a multipurpose code for Monte Carlo simulation

A. V. Brukhno, J. Grant, T. L. Underwood, K. Stratford, S. C. Parker, J. A. Purton, N. B. Wilding

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

DL_MONTE is an open-source, general-purpose software package for performing Monte Carlo (MC) simulations. It includes a wide variety of force fields and MC techniques, and thus is applicable to a broad range of problems in molecular simulation. Here we provide an overview of DL_MONTE, focussing on key features recently added to the package. These include the ability to treat systems confined to a planar pore (i.e. ‘slit’ or ‘slab’ boundary conditions); the lattice-switch Monte Carlo (LSMC) method for evaluating precise free energy differences between competing polymorphs; various commonly used methods for evaluating free energy profiles along transition pathways (including umbrella sampling, Wang–Landau and transition matrix); and a supplementary Python toolkit for simulation management and application of the histogram reweighting analysis method. We provide two ‘real-world’ examples to elucidate the use of these methods in DL_MONTE. In particular, we apply umbrella sampling to calculate the free energy profile associated with the translocation of a lipid through a bilayer. Moreover, we employ LSMC to examine the thermodynamic stability of two plastic crystal phases of water at high pressure. Beyond this, we provide instructions on how to access DL_MONTE and point to additional information valuable to existing and prospective users.

Original languageEnglish
JournalMolecular Simulation
Early online date1 Feb 2019
DOIs
Publication statusE-pub ahead of print - 1 Feb 2019

Keywords

  • free energy
  • molecular modelling
  • Monte Carlo
  • MPI
  • open-source software

ASJC Scopus subject areas

  • Chemistry(all)
  • Information Systems
  • Modelling and Simulation
  • Chemical Engineering(all)
  • Materials Science(all)
  • Condensed Matter Physics

Cite this

DL_MONTE : a multipurpose code for Monte Carlo simulation. / Brukhno, A. V.; Grant, J.; Underwood, T. L.; Stratford, K.; Parker, S. C.; Purton, J. A.; Wilding, N. B.

In: Molecular Simulation, 01.02.2019.

Research output: Contribution to journalArticle

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