Self-consistent microphysics models for materials at high-energy-density

Abstract

In this thesis we develop a new model for the fast generation of equation of state (EoS) data that is self-consistent with the underlying microphysics models. Following the successful implementation and testing of the EoS derived from the screened hydrogenic model with ℓ-splitting (SHM-ℓ), developed by Faussurier et al. [1], this work presents the further development of the atomic physics code, SpK. The core model of SpK solves the Saha equation, modified to capture non-ideal physics, to obtain distributions of ion charges and their bound electron configuration populations. Configuration energies are obtained from the NIST database, or calculated using the SHM-ℓ. Originally designed to calculate opacities from this information, the present work extends the capabilities of the code to calculate EoS data self-consistently with the opacity and underlying atomic physics model. The Q-MHD model [2], an electron EoS that utilises a fit to the Hooper microfield distribution function [3, 4] to truncate the internal partition functions in Saha-type methods, is implemented for weakly coupled conditions. We interpolate into the Thomas-Fermi (TF) model [5] when strongly coupled, because the TF model is more valid than Saha-type methods in this region of parameter space. We also implement a model approximating the physics of diatomic molecular dissociation in the Cowan model [6] for the ion EoS. The semi-empirical bonding corrections used in the FEOS code [7] are implemented to approximate the attractive forces of chemical bonding, with a Maxwell construction routine developed to model the liquid-vapour coexistence region. The result is a code that can generate tabulated EoS and opacity data in minutes. EoS data generated by SpK is utilised in shock Hugoniot calculations and sensitivity studies on integrated simulations of indirect-drive implosions and the experiments of Setchell et al. [8]. Both studies demonstrate a sensitivity to the choice of EoS models utilised.