Predicting Competitive and Non-Competitive Torquoselectivity in Ring-Opening Reactions using QTAIM and the Stress Tensor
Alireza Azizi, Roya Momen, Alejandro Morales-Bayuelo, Tianlv Xu,, Steven R. Kirk, Samantha Jenkins

TL;DR
This study introduces a vector-based bond representation within QTAIM to predict ring-opening reaction preferences, offering a new criterion that better aligns with experimental outcomes than traditional activation energy analysis.
Contribution
The paper presents a novel vector-based bond-path framework set in QTAIM for predicting reaction selectivity, challenging the reliance on activation energies.
Findings
Longer path lengths predict inward or outward ring opening.
The new criterion accurately classifies reactions as competitive or non-competitive.
Activation energies are less reliable for determining reaction competitiveness.
Abstract
We present a new vector-based representation of the chemical bond referred to as the bond-path frame-work set , where , and represent three paths with corresponding eigenvector-following path lengths and the bond-path length from the quantum theory of atoms in molecules (QTAIM). We find that longer path lengths of the ring-opening bonds predict the preference for the transition state inward (\textbf{TSIC}) or transition state outward (\textbf{TSOC}) ring opening reactions in agreement with experiment for all five reactions \textbf{R1-R5}. Competitiveness and non-competitiveness have traditionally been considered using activation energies. The activation energy however, for \textbf{R3} does not satisfactorily determine competitiveness or provide consistent agreement with experimental yields. We choose a selection…
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Taxonomy
TopicsMachine Learning in Materials Science · Various Chemistry Research Topics · Computational Drug Discovery Methods
