First-principles prediction of shock Hugoniot curves of boron, aluminum, and silicon from stochastic density functional theory

By adopting stochastic density functional theory (SDFT) and mixed stochastic–deterministic density functional theory (MDFT) methods, we perform first-principles calculations to predict the shock Hugoniot curves of boron (pressure P = 7.9 × 103–1.6 × 106 GPa and temperature T = 25–2800 eV), silicon (P = 2.6 × 103–7.9 × 105 GPa and T = 21.5–1393 eV), and aluminum (P = 5.2 × 103–9.0 × 105 GPa and T = 25–1393 eV) over wide ranges of pressure and temperature. In particular, we systematically investigate the impact of different cutoff radii in norm-conserving pseudopotentials on the calculated properties at elevated temperatures, such as pressure, ionization energy, and equation of state. By comparing the SDFT and MDFT results with those of other first-principles methods, such as extended first-principles molecular dynamics and path integral Monte Carlo methods, we find that the SDFT and MDFT methods show satisfactory precision, which advances our understanding of first-principles methods when applied to studies of matter at extremely high pressures and temperatures.