(39d) Using Metadynamics to Resolve and Characterize Complex Reactions at the Molecular Scale
- Conference: AIChE Annual Meeting
- Year: 2017
- Proceeding: 2017 Annual Meeting
- Group: Computational Molecular Science and Engineering Forum
- Time: Sunday, October 29, 2017 - 4:15pm-4:30pm
In this study we discuss the use of generic CVs, i.e., those CVs that do not rely on a priori knowledge of a chemical transformation, to help ease the challenge of discovering both complex chemical reaction networks and the associated kinetics of pathways in the networks. We present how two different generic CVs, namely Social Permutation Invariant (SPRINT) coordinates2 and collective variable-driven hyperdynamics (CVHD),3 require a relatively low level of system knowledge to construct, but act as suitable CVs for estimating transition rates from biased simulations.4 We biased these generic CVs, as well as typical ones derived from chemical intuition, following the infrequent MetaD method5 to calculate the transition rates of two reaction systems: an SN2 reaction and a Diels Alder reaction. For both systems, we show that regardless of the biased CVs, consistent transition rates and energy barriers are recovered an ensemble of biased simulations, while reducing the simulation time. In addition, we demonstrate an approach for exploring large, complex reaction networks with high dimensionality by biasing the SPRINT coordinates of the atoms in a given system following the Parallel Bias MetaD method.6 Using only knowledge of the initial state, we explore the reaction pathways of the decomposition of g-ketohydroperoxide described by the PM6 Hamiltonian. From analyzing an ensemble of biased simulations at various temperatures, we are able to construct a network of species that encompasses pathways consistent with the Korcek reaction mechanism,7 as well as typical hydrocarbon chemistries. This presentation will close with notes on how these methods can be broadly applied to resolve and characterize the relevant pathways involved in poorly understood, complex reacting systems.
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