Rotational and translational diffusion of liquid n-hexane: EFP-based Molecular Dynamics analysis

Thumbnail Image
Date
2022-03-21
Authors
Kim, Yu Lim
Gordon, Mark S.
Garcia, Andres
Evans, James W.
Major Professor
Advisor
Committee Member
Journal Title
Journal ISSN
Volume Title
Publisher
Iowa State University Digital Repository, Ames IA (United States)
Authors
Person
Person
Research Projects
Organizational Units
Organizational Unit
Organizational Unit
Organizational Unit
Organizational Unit
Journal Issue
Is Version Of
Versions
Series
Department
ChemistryAmes LaboratoryPhysics and AstronomyMathematics
Abstract
Molecular Dynamics (MD) simulations based upon the Effective Fragment Potential (EFP) method are utilized to provide a comprehensive assessment of diffusion in liquid n-hexane. We decompose translational diffusion into components along and orthogonal to the long axis of the molecule. Rotational diffusion is decomposed into tumbling and spinning motions about this axis. Our analysis yields four corresponding diffusion coefficients which are related to diagonal entries in the complete 6 ´ 6 diffusion tensor accounting for the three rotational and three translational degrees of freedom, and for the potential coupling between them. However, coupling between different degrees of freedom is expected to be minimal for a natural choice of molecular body-fixed axis, so then off-diagonal entries in the tensor are negligible. This expectation is supported by a hydrodynamic analysis of the diffusion tensor which treats the liquid surrounding the molecule being tracked as a viscous continuum. Thus, the EFP MD analysis provides a comprehensive characterization of diffusion, and also reveals expected shortcomings of the hydrodynamic treatment particularly for rotational diffusion.
Comments
This is a manuscript of an article published as Kim, Yu Lim, Mark S. Gordon, Andres Garcia, and James W. Evans. "Rotational and translational diffusion of liquid n-hexane: EFP-based molecular dynamics analysis." The Journal of Chemical Physics 156, no. 11 (2022): 114503. DOI: 10.1063/5.0079212. Copyright 2022 The Author(s). Posted with permission. DOE Contract Number(s): AC02-07CH11358.
Description
Keywords
Citation
DOI
Copyright
Collections