Numerical convergence of the self-diffusion coefficient and viscosity obtained with Thomas-Fermi-Dirac molecular dynamics

Efficient single-run implementation of generalized Einstein relation to compute transport coefficients: A binary-based time sampling

A robust and simple implementation of the generalized Einstein formulation using single equilibrium molecular dynamics simulation is introduced to compute diffusion and shear viscosity. The unique features underlying this framework are as follows: (1) The use of a simple binary-based method to sample time-dependent transport coefficients results in a uniform distribution of data on a logarithmic time scale. Although we sample "on-the-fly," the algorithm is readily applicable for post-processing analysis. Overlapping same-length segments are not sampled as they indicate strong correlations. (2) Transport coefficients are estimated using a power law fitting function, a generalization of the standard linear relation, that accurately describes the long-time plateau. (3) The use of a generalized least squares (GLS) fitting estimator to explicitly consider correlations between fitted data points results in a reliable estimate of the statistical uncertainties in a single run. (4) The covariance matrix for the GLS method is estimated analytically using the Wiener process statistics and computed variances. (5) We provide a Python script to perform the fits and automate the procedure to determine the optimal fitting domain. The framework is applied to two fluids, binary hard sphere and a Lennard-Jones near the triple point, and the validity of the single-run estimates is verified against multiple independent runs. The approach should be applicable to other transport coefficients since the diffusive limit is universal to all of them. Given its rigor and simplicity, this methodology can be readily incorporated into standard molecular dynamics packages using on-the-fly or post-processing analysis.

Probing the Origin of Viscosity of Liquid Electrolytes for Lithium Batteries

Viscosity is an extremely important property for ion transport and wettability of electrolytes. Easy access to viscosity values and a deep understanding of this property remain challenging yet critical to evaluating the electrolyte performance and tailoring electrolyte recipes with targeted properties. We proposed a screened overlapping method to efficiently compute the viscosity of lithium battery electrolytes by molecular dynamics simulations. The origin of electrolyte viscosity was further comprehensively probed. The viscosity of solvents exhibits a positive correlation with the binding energy between molecules, indicating viscosity is directly correlated to intermolecular interactions. Salts in electrolytes enlarge the viscosity significantly with increasing concentrations while diluents serve as the viscosity reducer, which is attributed to the varied binding strength from cation-anion and cation-solvent associations. This work develops an accurate and efficient method for computing the electrolyte viscosity and affords deep insight into viscosity at the molecular level, which exhibits the huge potential to accelerate advanced electrolyte design for next-generation rechargeable batteries.

Development of Deep Potentials of Molten MgCl2-NaCl and MgCl2-KCl Salts Driven by Machine Learning

Molten MgCl2-based chlorides have emerged as potential thermal storage and heat transfer materials due to high thermal stabilities and lower costs. In this work, deep potential molecular dynamics (DPMD) simulations by a method combination of the first principle, classical molecular dynamics, and machine learning are performed to systemically study the relationships of structures and thermophysical properties of molten MgCl2-NaCl (MN) and MgCl2-KCl (MK) eutectic salts at the temperature range of 800-1000 K. The densities, radial distribution functions, coordination numbers, potential mean forces, specific heat capacities, viscosities, and thermal conductivities of these two chlorides are successfully reproduced under extended temperatures by DPMD with a larger size (5.2 nm) and longer timescale (5 ns). It is concluded that the higher specific heat capacity of molten MK is originated from the strong potential mean force of Mg-Cl bonds, whereas the molten MN performs better in heat transfer due to the larger thermal conductivity and lower viscosity, attributed to the weak interaction between Mg and Cl ions. Innovatively, the plausibility and reliability of microscopic structures and macroscopic properties for molten MN and MK verify the extensibilities of these two deep potentials in temperatures, and these DPMD results also provide detailed technical parameters to the simulations of other formulated MN and MK salts.

Aqueous films on pore surfaces mediate adsorption and transport of gases through crowded nanopores

Interactions of trapped reservoir gases within organic-rich and brine-bearing sedimentary rocks have direct relevance to many geoenergy applications. Extracting generalizable information from experimental campaigns is hindered by the fact that geological systems are extremely complex. However, modern computational tools offer the opportunity of studying systems with controlled complexity, in an effort to better understand the mechanisms at play. Employing molecular dynamics, we examine here adsorption and transport of gases containing CH₄ and either CO₂ or H₂S within amorphous silica nanopores filled with benzene. We explicitly quantify the effect of small amounts of water/brines at geological temperature and pressure conditions. Because of wetting, the presence of brines lessens the adsorption capacity of the aromatic-filled pore. The simulation results show salt-specific effects on the transport properties of the gases when either KCl or CaCl₂ brines are considered, although adsorption was not affected. The acid gases considered either facilitate or hinder CH₄ transport depending on whether they are more or less preferentially adsorbed within the pore as compared to benzene, and this effect is mediated by the presence of water/brines. Our simulation results could be used to extract thermodynamic quantities that in the future will help to optimize transport of various gases through organic-rich and brine-bearing sedimentary rocks, which is likely to have a positive impact on both hydrocarbon production and carbon sequestration applications. As a first step, a phenomenological model is presented here, which allows one to predict permeability based on interatomic energies.

Quantum molecular dynamics study on the proton exchange, ionic structures, and transport properties of warm dense hydrogen-deuterium mixtures

Comprehensive knowledge of physical properties such as equation of state (EOS), proton exchange, dynamic structures, diffusion coefficients, and viscosities of hydrogen-deuterium mixtures with densities from 0.1 to 5 g/cm^{3} and temperatures from 1 to 50 kK has been presented via quantum molecular dynamics (QMD) simulations. The existing multi-shock experimental EOS provides an important benchmark to evaluate exchange-correlation functionals. The comparison of simulations with experiments indicates that a nonlocal van der Waals density functional (vdW-DF1) produces excellent results. Fraction analysis of molecules using a weighted integral over pair distribution functions was performed. A dissociation diagram together with a boundary where the proton exchange (H_{2}+D_{2}⇌2HD) occurs was generated, which shows evidence that the HD molecules form as the H_{2} and D_{2} molecules are almost 50% dissociated. The mechanism of proton exchange can be interpreted as a process of dissociation followed by recombination. The ionic structures at extreme conditions were analyzed by the effective coordination number model. High-order cluster, circle, and chain structures can be founded in the strongly coupled warm dense regime. The present QMD diffusion coefficient and viscosity can be used to benchmark two analytical one-component plasma (OCP) models: the Coulomb and Yukawa OCP models.

Structural and transport properties of ammonia along the principal Hugoniot

We investigate, via quantum molecular dynamics simulations, the structural and transport properties of ammonia along the principal Hugoniot for temperatures up to 10 eV and densities up to 2.6 g/cm³. With the analysis of the molecular dynamics trajectories by use of the bond auto-correlation function, we identify three distinct pressure-temperature regions for local chemical structures of ammonia. We derive the diffusivity and viscosity of strong correlated ammonia with high accuracy through fitting the velocity and stress-tensor autocorrelation functions with complex functional form which includes structures and multiple time scales. The statistical error of the transport properties is estimated. It is shown that the diffusivity and viscosity behave in a distinctly different manner at these three regimes and thus present complex features. In the molecular fluid regime, the hydrogen atoms have almost the similar diffusivity as nitrogen and the viscosity is dominated by the kinetic contribution. When entering into the mixture regime, the transport behavior of the system remarkably changes due to the stronger ionic coupling, and the viscosity is determined to decrease gradually and achieve minimum at about 2.0 g/cm³ on the Hugoniot. In the plasma regime, the hydrogen atoms diffuse at least twice as fast as the nitrogen atoms.

Method to manage integration error in the Green-Kubo method

The Green-Kubo method is a commonly used approach for predicting transport properties in a system from equilibrium molecular dynamics simulations. The approach is founded on the fluctuation dissipation theorem and relates the property of interest to the lifetime of fluctuations in its thermodynamic driving potential. For heat transport, the lattice thermal conductivity is related to the integral of the autocorrelation of the instantaneous heat flux. A principal source of error in these calculations is that the autocorrelation function requires a long averaging time to reduce remnant noise. Integrating the noise in the tail of the autocorrelation function becomes conflated with physically important slow relaxation processes. In this paper we present a method to quantify the uncertainty on transport properties computed using the Green-Kubo formulation based on recognizing that the integrated noise is a random walk, with a growing envelope of uncertainty. By characterizing the noise we can choose integration conditions to best trade off systematic truncation error with unbiased integration noise, to minimize uncertainty for a given allocation of computational resources.

Pseudoatom molecular dynamics

An approach to simulating warm and hot dense matter that combines density-functional-theory-based calculations of the electronic structure to classical molecular dynamics simulations with pair interaction potentials is presented. The method, which we call pseudoatom molecular dynamics, can be applied to single-component or multicomponent plasmas. It gives equation of state and self-diffusion coefficients with an accuracy comparable to orbital-free molecular dynamics simulations but is computationally much more efficient.

Effect of correlation on viscosity and diffusion in molecular-dynamics simulations

In the warm dense matter (WDM) regime, material properties like diffusion and viscosity can be obtained from lengthy quantum molecular dynamics simulations, where the quantum behavior of the electrons is represented using either Kohn-Sham or orbital-free density functional theory. To reduce the simulation duration, we fit the time dependence of the autocorrelation functions (ACFs) and then use the fit to find values of the diffusion and viscosity. This fitting procedure avoids noise in the long time behavior of the ACFs. We present a detailed analysis of the functional form used to fit the ACFs, which is always a more efficient means to obtain mass transport properties. We use the fits to estimate the statistical error of the transport properties. We apply this methodology to a dense correlated plasma of copper and a mixture of carbon and hydrogen. Both systems show structure in their ACFs and exhibit multiple time scales. The mixture contains different structural forms of the ACFs for each component in the mixture.

Partial ionization in dense plasmas: comparisons among average-atom density functional models

Nuclei interacting with electrons in dense plasmas acquire electronic bound states, modify continuum states, generate resonances and hopping electron states, and generate short-range ionic order. The mean ionization state (MIS), i.e, the mean charge Z of an average ion in such plasmas, is a valuable concept: Pseudopotentials, pair-distribution functions, equations of state, transport properties, energy-relaxation rates, opacity, radiative processes, etc., can all be formulated using the MIS of the plasma more concisely than with an all-electron description. However, the MIS does not have a unique definition and is used and defined differently in different statistical models of plasmas. Here, using the MIS formulations of several average-atom models based on density functional theory, we compare numerical results for Be, Al, and Cu plasmas for conditions inclusive of incomplete atomic ionization and partial electron degeneracy. By contrasting modern orbital-based models with orbital-free Thomas-Fermi models, we quantify the effects of shell structure, continuum resonances, the role of exchange and correlation, and the effects of different choices of the fundamental cell and boundary conditions. Finally, the role of the MIS in plasma applications is illustrated in the context of x-ray Thomson scattering in warm dense matter.

Longitudinal viscosity of two-dimensional Yukawa liquids

The longitudinal viscosity η(l) is obtained for a two-dimensional (2D) liquid using a Green-Kubo method with a molecular dynamics simulation. The interparticle potential used has the Debye-Hückel or Yukawa form, which models a 2D dusty plasma. The longitudinal η(l) and shear η(s) viscosities are found to have values that match very closely, with only negligible differences for the entire range of temperatures that is considered. For a 2D Yukawa liquid, the bulk viscosity η(b) is determined to be either negligibly small or not a meaningful transport coefficient.

Plastic ablator and hydrodynamic instabilities: a first-principles set of microscopic coefficients

We have performed orbital-free and quantum molecular dynamics simulations on plastic ablator along two isochores, namely 7 and 9 g cm(-3), from 5 to 40 eV. These thermodynamic conditions correspond to those encountered during inertial confinement fusion capsule implosion when hydrodynamic instabilities can take place. The coupling between orbital-free and quantum approaches allowed us to compute an exhaustive set of microscopic coefficients, i.e., equation-of-state, ionic diffusion coefficients, thermal and electrical conductivities, spanning phenomena that can mitigate the growth of classical Rayleigh-Taylor instability. Comparisons to widely used models in hydrodynamics codes are developed.