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Automatic proposal of multistep reaction mechanisms using a graph-driven search
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Ismail, Idil, Stuttaford-Fowler, Holly B. V. A., Ochan-Ashok, Curtis, Robertson, Christopher and Habershon, Scott (2019) Automatic proposal of multistep reaction mechanisms using a graph-driven search. The Journal of Physical Chemistry A, 123 (15). pp. 3407-3417. doi:10.1021/acs.jpca.9b01014 ISSN 1089-5639.
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WRAP-automatic-proposal-multistep-reaction-mechanisms-using-graph-driven-search-Habershon-2019.pdf - Accepted Version - Requires a PDF viewer. Download (2887Kb) | Preview |
Official URL: http://dx.doi.org/10.1021/acs.jpca.9b01014
Abstract
Proposing and testing mechanistic hypotheses stands as one of the key applications of contemporary computational chemistry. In the majority of computational mechanistic analyses, the individual elementary steps leading from reactants to products are proposed by the user, based on learnt chemical knowledge, intuition, or comparison to an existing well-characterized mechanism for a closely-related chemical reaction. However, the pre-requisite of prior chemical knowledge is a barrier to automated (or ‘black box’) mechanistic generation and assessment, and may simultaneously preclude mechanistic proposals which lie outside the ‘standard’ chemical reaction set. In this Article, we propose a simple random-walk algorithm that searches for the set of elementary chemical reactions which transform defined reactant structures into target products. Our approach operates exclusively in the space of molecular connectivity matrices, seeking out the set of chemically-sensible bonding changes which link connectivity matrices for input reactant and product structures. We subsequently illustrate how atomic coordinates for each elementary reaction can be generated under the action of a graph- restraining potential, prior to further analysis by quantum chemical calculations. Our approach is successfully demonstrated for carbon monoxide oxidation, the water-gas shift reaction, and n-hexane aromatization, all catalyzed by Pt nanoparticles.
| Item Type: | Journal Article | ||||||||
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| Subjects: | Q Science > QD Chemistry | ||||||||
| Divisions: | Faculty of Science, Engineering and Medicine > Science > Chemistry Faculty of Science, Engineering and Medicine > Science > Centre for Scientific Computing |
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| Library of Congress Subject Headings (LCSH): | Chemical reactions, Random walks (Mathematics) | ||||||||
| Journal or Publication Title: | The Journal of Physical Chemistry A | ||||||||
| Publisher: | American Chemical Society | ||||||||
| ISSN: | 1089-5639 | ||||||||
| Official Date: | 18 April 2019 | ||||||||
| Dates: |
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| Volume: | 123 | ||||||||
| Number: | 15 | ||||||||
| Page Range: | pp. 3407-3417 | ||||||||
| DOI: | 10.1021/acs.jpca.9b01014 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Reuse Statement (publisher, data, author rights): | This document is the Accepted Manuscript version of a Published Work that appeared in final form in The Journal of Physical Chemistry A, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see http://dx.doi.org/10.1021/acs.jpca.9b01014 | ||||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||||
| Date of first compliant deposit: | 28 May 2019 | ||||||||
| Date of first compliant Open Access: | 22 March 2020 | ||||||||
| RIOXX Funder/Project Grant: |
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