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Diffusivity of Mixtures in Warm Dense Matter Regime

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Frontiers and Challenges in Warm Dense Matter

Part of the book series: Lecture Notes in Computational Science and Engineering ((LNCSE,volume 96))

Abstract

Modeling of ionic diffusion in warm dense plasma mixtures has been of longstanding interest in astrophysics and in Inertial Confinement Fusion. Here we review traditional approaches to calculating plasma diffusion using kinetic theory. We also review earlier classical molecular dynamics (MD) results. We discuss some new results from MD for self and mutual diffusion in a mixture of deuterium and argon at warm dense matter regime. We make use of Yukawa interionic potentials as an effective potential that accounts for the screening effects of the electrons to the ions. We further provide a general description of the Green-Kubo technique to extract the diffusivity of a multicomponent mixture. The description is very general and it can be extended to plasmas.

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Acknowledgements

The authors would like to thank Bill Cabot, Kyle Caspersen, John Castor, Jim Glosli, Frank Graziani, Jeff Greenough, Julie Jackson, A. Bruce Langdon, Paul Miller, Michael Murillo, Dave Richards, Mike Surh, Heather Whitley and all the Cimarron team for their contributions and fruitful discussions. One of us T.H. acknowledges interesting discussion with Jerome Daligault during the IPAM workshop. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. This work was funded by the Laboratory Directed Research and Development Program at LLNL under project tracking code 12-SI-005 and 10-ERD-004. We gratefully acknowledge supercomputer time provided through the Institutional Computing Grand Challenge program at LLNL.

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Correspondence to Robert E. Rudd .

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Haxhimali, T., Rudd, R.E. (2014). Diffusivity of Mixtures in Warm Dense Matter Regime. In: Graziani, F., Desjarlais, M., Redmer, R., Trickey, S. (eds) Frontiers and Challenges in Warm Dense Matter. Lecture Notes in Computational Science and Engineering, vol 96. Springer, Cham. https://doi.org/10.1007/978-3-319-04912-0_9

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