PyFrag 2019—Automating the exploration and analysis of reaction mechanisms

Xiaobo Sun, Thomas M. Soini, Jordi Poater, Trevor A. Hamlin, F. Matthias Bickelhaupt

Research output: Contribution to journalArticlepeer-review

70 Citations (Scopus)

Abstract

We present a substantial update to the PyFrag 2008 program, which was originally designed to perform a fragment-based activation strain analysis along a provided potential energy surface. The original PyFrag 2008 workflow facilitated the characterization of reaction mechanisms in terms of the intrinsic properties, such as strain and interaction, of the reactants. The new PyFrag 2019 program has automated and reduced the time-consuming and laborious task of setting up, running, analyzing, and visualizing computational data from reaction mechanism studies to a single job. PyFrag 2019 resolves three main challenges associated with the automated computational exploration of reaction mechanisms: it (1) computes the reaction path by carrying out multiple parallel calculations using initial coordinates provided by the user; (2) monitors the entire workflow process; and (3) tabulates and visualizes the final data in a clear way. The activation strain and canonical energy decomposition results that are generated relate the characteristics of the reaction profile in terms of intrinsic properties (strain, interaction, orbital overlaps, orbital energies, populations) of the reactant species.

Original languageEnglish
Pages (from-to)2227-2233
Number of pages7
JournalJournal of Computational Chemistry
Volume40
Issue number25
DOIs
Publication statusPublished - 2019
Externally publishedYes

Keywords

  • activation strain model
  • automation
  • density functional calculations
  • energy decomposition analysis
  • program
  • reaction mechanisms

ASJC Scopus subject areas

  • General Chemistry
  • Computational Mathematics

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