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Using Constrained Density Functional Theory to Track Proton Transfers and to Sample Their Associated Free Energy Surface
Author(s) -
Chenghan Li,
Gregory A. Voth
Publication year - 2021
Publication title -
journal of chemical theory and computation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.001
H-Index - 185
eISSN - 1549-9626
pISSN - 1549-9618
DOI - 10.1021/acs.jctc.1c00609
Subject(s) - proton , molecular dynamics , umbrella sampling , density functional theory , proton transport , tracking (education) , trajectory , work (physics) , sampling (signal processing) , solvation , position (finance) , ab initio , transfer (computing) , energy (signal processing) , physics , statistical physics , chemical physics , molecular physics , chemistry , computer science , computational chemistry , molecule , quantum mechanics , detector , psychology , pedagogy , finance , optics , economics , parallel computing
Ab initio molecular dynamics (AIMD) and quantum mechanics/molecular mechanics (QM/MM) methods are powerful tools for studying proton solvation, transfer, and transport processes in various environments. However, due to the high computational cost of such methods, achieving sufficient sampling of rare events involving excess proton motion-especially when Grotthuss proton shuttling is involved-usually requires enhanced free energy sampling methods to obtain informative results. Moreover, an appropriate collective variable (CV) that describes the effective position of the net positive charge defect associated with an excess proton is essential both for tracking the trajectory of the defect and for the free energy sampling of the processes associated with the resulting proton transfer and transport. In this work, such a CV is derived from first principles using constrained density functional theory (CDFT). This CV is applicable to a broad array of proton transport and transfer processes as studied via AIMD and QM/MM simulations.

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