Electronic Collective Variables for Chemical Reactions
YaoKun Lei, Yi Isaac Yang

TL;DR
This paper introduces a charge-space electronic collective variable (CV) based on atomic charges, enabling more physically meaningful and transferable reaction progress descriptions in chemical simulations, trained via neural networks.
Contribution
It presents a novel electronic CV framework based on atomic charges, trained with neural networks, for improved reaction sampling across diverse chemical environments.
Findings
Electronic CVs can be constructed in a common charge-space form.
Reaction progress involves coupled electronic and conformational components.
The framework can be extended to restrain side reactions.
Abstract
Chemical reaction sampling critically depends on collective variables (CVs) that capture the slow degrees of freedom governing reactive transformations. However, existing reaction CVs are often defined in geometric space or learned in a system-specific manner, which limits their transferability and leaves open the more fundamental question of how reaction progress should be represented. From a physical perspective, chemical reactions are defined by electron redistribution. Here, we introduce a charge-space electronic collective variable that describes the electronic component of reaction progress in a common linear form based on atomic charges. To enable its use in enhanced sampling, atomic charges and the corresponding CV gradients are provided by a neural-network model trained on QM/MM data within an iterative sampling-training workflow. Across multiple reactions in aqueous and…
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