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Table · dataset · 2019

Data for Automatic proposal of multi-step reaction mechanisms using a graph-driven search

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Proposing and testing mechanistic hypotheses stands as one of the key applications of contemporary computational chemistry.

Description

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 bond-enforcing potential, prior to further analysis by ab initio quantum chemistry.

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Our approach is successfully demonstrated for CO oxidation, the water-gas shift reaction, and n-hexane aromatization, all catalyzed by Pt nanoparticles.<br><br>This zip file contains the energy data information for Figures 3, 4 and 5 for the manuscript: Automatic Proposal of Multi-Step Reaction Mechanisms Using a Graph-Driven Search, by Idil Ismail, Holly Stuttaford-Fowler, Curtis Ochan-Ashok, Christopher Robertson, and Scott Habershon.

Submitted to Journal of Physical Chemistry, January 2019.

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Computational chemistry 80%
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