NMR spin-rotation relaxation and diffusion of methane

P. M. Singer, D. Asthagiri, W. G. Chapman, G. J. Hirasaki

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30 Scopus citations

Abstract

The translational diffusion-coefficient and the spin-rotation contribution to the 1H NMR relaxation rate for methane (CH4) are investigated using MD (molecular dynamics) simulations, over a wide range of densities and temperatures, spanning the liquid, supercritical, and gas phases. The simulated diffusion-coefficients agree well with measurements, without any adjustable parameters in the interpretation of the simulations. A minimization technique is developed to compute the angular velocity for non-rigid spherical molecules, which is used to simulate the autocorrelation function for spin-rotation interactions. With increasing diffusivity, the autocorrelation function shows increasing deviations from the single-exponential decay predicted by the Langevin theory for rigid spheres, and the deviations are quantified using inverse Laplace transforms. The 1H spin-rotation relaxation rate derived from the autocorrelation function using the "kinetic model" agrees well with measurements in the supercritical/gas phase, while the relaxation rate derived using the "diffusion model" agrees well with measurements in the liquid phase. 1H spin-rotation relaxation is shown to dominate over the MD-simulated 1H-1H dipole-dipole relaxation at high diffusivity, while the opposite is found at low diffusivity. At high diffusivity, the simulated spin-rotation correlation time agrees with the kinetic collision time for gases, which is used to derive a new expression for 1H spin-rotation relaxation, without any adjustable parameters.

Original languageEnglish
Article number204504
JournalJournal of Chemical Physics
Volume148
Issue number20
DOIs
StatePublished - May 28 2018
Externally publishedYes

Funding

This work was funded by the Rice University Consortium on Processes in Porous Media and the American Chemical Society Petroleum Research Fund [Grant No. ACS-PRF-58859-ND6]. We gratefully acknowledge the National Energy Research Scientific Computing Center that is supported by the Office of Science of the U.S. Department of Energy [Grant No. DE-AC02-05CH11231] for HPC time and support. We also gratefully acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin (URL: http://www.tacc.utexas.edu) for providing HPC resources and Zeliang Chen for his assistance.

FundersFunder number
National Energy Research Scientific Computing Center
U.S. Department of Energy
Office of Science
American Chemical Society Petroleum Research Fund

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