Wei Kang

Over the past decade, high-power laser experiments have enabled access to warm dense matter, an intermediate regime between solids and ideal plasmas, characterized by weak ionization, strong coupling, and partial degeneracy. In this regime, the equation of state (EoS) is a key quantity for describing the thermodynamic properties of matter. Although ab initio calculations provide increasingly accurate predictions for the EoS, experimental data that are both accurate and statistically significant remain essential to constrain theoretical models. However, most kilojoule-class laser systems operate at low repetition rates, limiting the amount of available data. The recently commissioned L4n beamline at ELI-Beamlines (Czech Republic) overcomes this limitation by combining kilojoule-scale energy with high-repetition-rate (HRR) operation. Leveraging this capability, we performed the first laser-driven shock compression experiment on hexagonal boron nitride (h-BN) at the L4n beamline, using Velocity Interferometer System for Any Reflector and streak optical pyrometry diagnostics to measure shock velocities. By complementing the existing experimental Hugoniot database for h-BN, this work demonstrates the capability of the HRR L4n beamline for EoS measurements, paving the way for larger experimental datasets in future experiments.

We report thermodynamic properties, including equation of state, principal Hugoniot, heat capacity, and Grüneisen parameter, for beryllium under density–temperature conditions of ρ = 3.0–9.0 g/cm3 and T = 5–10 000 eV, using an extended first-principles molecular dynamics method together with finite-temperature exchange–correlation functionals. Compared with zero-temperature exchange–correlation models, our results exhibit appreciable differences of about 3% in modeling the equation of state. Thermal excitations of K-shell electrons, delocalization of wave functions, and the merging of energy bands for beryllium along the Hugoniot curve are also presented. In addition to the application of these thermodynamic data to inertial confinement fusion and high-energy-density physics, our results may also serve as useful benchmarks for investigating thermal exchange–correlation effects on thermodynamic properties of warm dense matter, and further help to elucidate the mechanisms of inner-shell electron excitation.

Species separation induced by ultra-strong shocks is a fundamental topic for both inertial confinement fusion and high-energy-density experiments. However, how this phenomenon unfolds during the propagation and release phases of shocks has not been fully understood. In this study, we conduct a systematic investigation of species separation dynamics induced by strong shocks covering both steady propagation stage and shock release stage. Our study employs the non-equilibrium molecular dynamics method to explore these processes in a medium composed of two representative isotopes. Simulation results unveil distinct physical scenarios and dynamic behaviors of species separation during the two stages: During the steady propagation stage, species separation is confined to a localized region near the shock front, where the dynamics of the binary isotopic mixture are well-captured by the single-fluid approximation. In contrast, at the shock release stage, the species expand independently into the vacuum with different speeds, leading to a separation region of several orders of the mean free path. Interactions between particles play a minimal role in this process, allowing the dynamics of the mixture to be effectively described by decoupled two-phase hydrodynamic equations. Specifically, a self-similar behavior in the degree of separation and the isentropic expansion laws governing the two highly rarefied species at the shock release stage are identified, offering quantitative insights for applications.

We show that it is possible to perform a first-principles precision molecular dynamics (MD) investigation of hypervelocity gas–surface interaction (HGSI) with the help of deep potential (DP) type interaction model as a bridge. A DP type interaction model specifically designed for HGSI is trained based on dataset generated from high-precision first-principles MD (FPMD) simulations of HGSI processes at a relatively small spatial scale, and then is directly integrated into MD simulations of large spatial and temporal scales to simulate complete HGSI processes. Special care is taken in the FPMD simulations to correctly describe the van der Waals interaction, which is of particular importance to HGSI. As an illustrating example, the HGSI process of helium atoms and aluminum surface is investigated with incident velocity ranging from 5.0 to 15.0 km/s. Accommodation coefficients and reflected velocity distributions of He atoms are calculated and show significant differences with MD simulations using empirical interaction potentials, which highlights the necessity for high-accuracy interaction model in HGSI investigations. In addition, we find that it is necessary to include high-incident velocity collision data in the generation of DP type interaction potential to guarantee the accuracy of interaction model in the context of HGSI. Results of this work may help to provide more accurate theoretical benchmarks for the prediction of aerodynamic properties and thermal loads, which is essential for the design and optimization of hypervelocity vehicles.

We show with molecular dynamics simulations that spinodal decomposition is a probable initiation mechanism of spallation in impact-melted samples at extremely high strain rates. The formation of voids or bubbles is a secondary process following the spinodal amplification of density fluctuations. As a result, the spallation strength can be related to the inherent thermodynamic property of the liquid, i.e., the liquid-gas spinodal curve, which can be determined by independent equation-of-state studies in prior. This connection between high strain-rate spallation and spinodal decomposition may be further examined in future experiments.

The widely used quasi-isentropic ramp loading technique relies heavily on back-calculation methods that convert the measured free-surface velocity profiles to the stress–density states inside the compressed sample. Existing back-calculation methods are based on one-dimensional isentropic hydrodynamic equations, which assume a well-defined functional relationship P(ρ) between the longitudinal stress and density throughout the entire flow field. However, this kind of idealized stress–density relation does not hold in general, because of the complexities introduced by structural phase transitions and/or elastic–plastic response. How and to what extent these standard back-calculation methods may be affected by such inherent complexities is still an unsettled question. Here, we present a close examination using large-scale molecular dynamics (MD) simulations that include the detailed physics of the irreversibly compressed solid samples. We back-calculate the stress–density relation from the MD-simulated rear surface velocity profiles and compare it directly against the stress–density trajectories measured from the MD simulation itself. Deviations exist in the cases studied here, and these turn out to be related to the irreversibility between compression and release. Rarefaction and compression waves are observed to propagate with different sound velocities in some parts of the flow field, violating the basic assumption of isentropic hydrodynamic models and thus leading to systematic back-calculation errors. In particular, the step-like feature of the P(ρ) curve corresponding to phase transition may be completely missed owing to these errors. This kind of mismatch between inherent properties of matter and the basic assumptions of isentropic hydrodynamics has a fundamental influence on how the ramp loading method can be applied.

The thermodynamic properties of boron nitride under extreme pressures and temperatures are of great interest and importance for materials science and inertial confinement fusion physics, but they are poorly understood owing to the challenges of performing experiments and realizing ab initio calculations. Here, we report the first shock Hugoniot data on hexagonal boron nitride at pressures of 5–16 Mbar, using hohlraum-driven shock waves at the SGIII-p laser facility in China. Our density functional theory molecular dynamics calculations closely match experimental data, validating the equations of state for modeling the shock response of boron nitride and filling a crucial gap in the knowledge of boron nitride properties in the region of multi-Mbar pressures and eV temperatures. The results presented here provide fundamental insights into boron nitride under the extreme conditions relevant to inertial confinement fusion, hydrogen–boron fusion, and high-energy-density physics.

The theoretical design for the time profile of radiation temperature plays an important role in indirect laser-driven equation-of-state measurement, which severely relies on a large number of radiation hydrodynamic simulations. In this work, we provide a concise data-driven method for optimizing the radiation temperature profile, which combines a time-varying Volterra model with an improvement achieved by data generation via radiation hydrodynamic simulations utilizing random perturbations in a skew normal distribution as inputs. We find that the time-varying Volterra model can be used to investigate the time-dependent relationship between the radiation temperature and the key physical quantities of interest, such as shock-wave velocity and ablation drive pressure. With this method, we realize the inverse designs of the radiation temperature profiles for planar dynamic shock and ramp compressions according to the desired shock-wave velocity and drive pressure, respectively, which shows the advantage of practical application in experiments.

We propose an ansatz without adjustable parameters for the calculation of dynamical structure factor. The ansatz combines quasi-particle Green's function, especially the contribution from the renormalization factor, and the exchange-correlation kernel from time-dependent density functional theory together, verified for typical metals and semiconductors from plasmon excitation regime to Compton scattering regime. It has the capability to reconcile both small-angle and large-angle x-ray scattering (IXS) signals with much improved accuracy, which can be used, as the theoretical base model, in inversely inferring electronic structures of condensed matter from IXS experimental signals directly. It may also used to diagnose thermal parameters, such as temperature and density, of dense plasmas in x-ray Thomson scattering experiments.