Adaptive Green-Kubo estimates of transport coefficients from molecular dynamics based on robust error analysis

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.

Understanding the Anomalous Diffusion of Water in Aqueous Electrolytes Using Machine Learned Potentials

The diffusivity of water in aqueous cesium iodide solutions is larger than that in neat liquid water and vice versa for sodium chloride solutions. Such peculiar ion-specific behavior, called anomalous diffusion, is not reproduced in typical force field based molecular dynamics (MD) simulations due to inadequate treatment of ion-water interactions. Herein, this hurdle is tackled by using machine learned atomic potentials (MLPs) trained on data from density functional theory calculations. MLP based atomistic MD simulations of aqueous salt solutions reproduce experimentally determined thermodynamic, structural, dynamical, and transport properties, including their varied trends in water diffusivities across salt concentration. This enables an examination of their intermolecular structure to unravel the microscopic underpinnings of the differences in their transport properties. While both ions in CsI solutions contribute to the faster diffusion of water molecules, the competition between the heavy retardation by Na ions and the slight acceleration by Cl ions in NaCl solutions reduces their water diffusivity.

Transport properties in liquids from first-principles: The case of liquid water and liquid argon

Shear and bulk viscosities of liquid water and argon are evaluated from first-principles in the density functional theory (DFT) framework, by performing molecular dynamics simulations in the NVE ensemble and using the Kubo–Greenwood equilibrium approach. The standard DFT functional is corrected in such a way to allow for a reasonable description of van der Waals effects. For liquid argon, the thermal conductivity has been also calculated. Concerning liquid water, to our knowledge, this is the first estimate of the bulk viscosity and of the shear-viscosity/bulk-viscosity ratio from first-principles. By analyzing our results, we can conclude that our first-principles simulations, performed at a nominal average temperature of 366 to guarantee that the systems are liquid-like, actually describe the basic dynamical properties of liquid water at about 330 K. In comparison with liquid water, the normal, monatomic liquid Ar is characterized by a much smaller bulk-viscosity/shear-viscosity ratio (close to unity) and this feature is well reproduced by our first-principles approach, which predicts a value of the ratio in better agreement with experimental reference data than that obtained using the empirical Lennard-Jones potential. The computed thermal conductivity of liquid argon is also in good agreement with the experimental value.

Intrinsic viscuit probability distribution functions for transport coefficients of liquids and solids

A reformulation of the Green–Kubo expressions for the transport coefficients of liquids in terms of a probability distribution function (PDF) of short trajectory contributions, which were named “viscuits,” has been explored in a number of recent publications. The viscuit PDF, P, is asymmetric on the two sides of the distribution. It is shown here using equilibrium 3D and 2D molecular dynamics simulations that the viscuit PDF of a range of simple molecular single component and mixture liquid and solid systems can be expressed in terms of the same intrinsic PDF ( P0), which is derived from P with the viscuit normalized by the standard deviation separately on each side of the distribution. P0 is symmetric between the two sides and can be represented for not very small viscuit values by the same gamma distribution formulated in terms of a single disposable parameter. P0 tends to an exponential in the large viscuit wings. Scattergrams of the viscuits and their associated single trajectory correlation functions are shown to distinguish effectively between liquids, solids, and glassy systems. The so-called viscuit square root method for obtaining the transport coefficients is shown to be a useful probe of small and statistically zero self-diffusion coefficients of molecules in the liquid and solid states, respectively. The results of this work suggest that the transport coefficients have a common underlying physical origin, reflecting at a coarse-grained level the traversal statistics of the system through its high-dimensioned potential energy landscape.

Computational Study of the Structure and Transport in Pyrrolidinium-Li-TFSI-Silica Ionogels

Ionogels (IGs) are a unique class of composite materials with attributes that make them promising materials for applications in electrochemical energy storage. Due to the solid porous matrix that confines the ionic liquid (IL) in the IG, they can be used as self-supporting electrolytes. Furthermore, interactions of the IL with the porous matrix can have beneficial effects on transport, such as lowering the freezing/glass transition temperature of the conducting IL. In this work, we employ molecular dynamics simulations to investigate the influence of the porous morphology and solid volume fraction on ionic conductivity and Li⁺ diffusivity using a representative 0.5 M Li-bis(trifluoromethane)sulfonimide (TFSI)-pyrrolidinium (Pyr1.3) IL confined in a nanoporous silica matrix. The effect of the morphology of the confining matrix is compared using the pure IL as a baseline. We find that the tracer and collective Li⁺ diffusion and ionic conductivity of all the model IGs have significantly lower temperature dependence than the corresponding pure IL. In general, low-silica IGs with wide pores displayed the best transport properties at high temperatures, but the trends with the morphology for the nested set of transport coefficients we examined changed as the collective behavior of the Li⁺ ions and the molecular IL components were considered. Remarkably, some of the model IGs displayed better transport properties on a volume of fluid basis at low temperatures than the constituent IL. These trends were tied to structural changes revealed by the radial distribution functions of the IL components and the silica surface, including a decreasing Li⁺ adsorption peak of the surface silica indicating a change in the relative contributions of bulk-like and surface-like transport in the confined IL.

Invariance principles in the theory and computation of transport coefficients

ABSTRACT

In this work, we elaborate on two recently discovered invariance principles, according to which transport coefficients are, to a large extent, independent of the microscopic definition of the densities and currents of the conserved quantities being transported (energy, momentum, mass, charge). The first such principle, gauge invariance, allows one to define a quantum adiabatic energy current from density-functional theory, from which the heat conductivity can be uniquely defined and computed using equilibrium ab initio molecular dynamics. When combined with a novel topological definition of atomic oxidation states, gauge invariance also sheds new light onto the mechanisms of charge transport in ionic conductors. The second principle, convective invariance, allows one to extend the analysis to multi-component systems. These invariance principles can be combined with new spectral analysis methods for the current time series to be fed into the Green-Kubo formula to obtain accurate estimates of transport coefficients from relatively short molecular dynamics simulations.

Viscuit and the fluctuation theorem investigation of shear viscosity by molecular dynamics simulations: The information and the noise

The shear viscosity, η, of model liquids and solids is investigated within the framework of the viscuit and Fluctuation Theorem (FT) probability distribution function (PDF) theories, following Heyes et al. [J. Chem. Phys. 152, 194504 (2020)] using equilibrium molecular dynamics (MD) simulations on Lennard-Jones and Weeks-Chandler-Andersen model systems. The viscosity can be obtained in equilibrium MD simulation from the first moment of the viscuit PDF, which is shown for finite simulation lengths to give a less noisy plateau region than the Green-Kubo method. Two other formulas for the shear viscosity in terms of the viscuit and PDF analysis are also derived. A separation of the time-dependent average negative and positive viscuits extrapolated from the noise dominated region to zero time provides another route to η. The third method involves the relative number of positive and negative viscuits and their PDF standard deviations on the two sides for an equilibrium system. For the FT and finite shear rates, accurate analytic expressions for the relative number of positive to negative block average shear stresses is derived assuming a shifted Gaussian PDF, which is shown to agree well with non-equilibrium molecular dynamics simulations. A similar treatment of the positive and negative block average contributions to the viscosity is also shown to match the simulation data very well.

Accurate thermal conductivities from optimally short molecular dynamics simulations

The evaluation of transport coefficients in extended systems, such as thermal conductivity or shear viscosity, is known to require impractically long simulations, thus calling for a paradigm shift that would allow to deploy state-of-the-art quantum simulation methods. We introduce a new method to compute these coefficients from optimally short molecular dynamics simulations, based on the Green-Kubo theory of linear response and the cepstral analysis of time series. Information from the full sample power spectrum of the relevant current for a single and relatively short trajectory is leveraged to evaluate and optimally reduce the noise affecting its zero-frequency value, whose expectation is proportional to the corresponding conductivity. Our method is unbiased and consistent, in that both the resulting bias and statistical error can be made arbitrarily small in the long-time limit. A simple data-analysis protocol is proposed and validated with the calculation of thermal conductivities in the paradigmatic cases of elemental and molecular fluids (liquid Ar and H₂O) and of crystalline and glassy solids (MgO and a-SiO₂). We find that simulation times of one to a few hundred picoseconds are sufficient in these systems to achieve an accuracy of the order of 10% on the estimated thermal conductivities.

Structure formation in nanocomposite hydrogels

We use molecular dynamics simulations to study structure formation in physically associating nanocomposite hydrogels. Nanofillers were modeled as rigid bodies of disk-like shapes and physical crosslinks were simulated by introducing a short-range attraction between the nanofillers and polymer chain ends. The structure, dynamics and mechanics of these polymer gels were studied as a function of nanofiller volume fraction. We observe the formation of a percolated network in the hydrogels, with an ordered local structure but disordered globally, as we increase the filler fraction. This locally ordered structure was a result of the anisotropy of the disk-like fillers. The dynamics of polymers showed significant caging effects in the gel state. Stress autocorrelation and elongation results were analyzed as a function of nano-filler concentrations. Comparisons with nanofillers of different shapes showed that disk-like nanofillers are more effective in strengthening the hydrogels than spherical nanofillers.

Energy exchange network of inter-residue interactions within a thermally fluctuating protein molecule: A computational study

Protein function is regulated not only by the structure but also by physical dynamics and thermal fluctuations. We have developed the computer program, CURrent calculation for proteins (CURP), for the flow analysis of physical quantities within thermally fluctuating protein media. The CURP program was used to calculate the energy flow within the third PDZ domain of the neuronal protein PSD-95, and the results were used to illustrate the energy exchange network of inter-residue interactions based on atomistic molecular dynamics simulations. The removal of the α3 helix is known to decrease ligand affinity by 21-fold without changing the overall protein structure; nevertheless, we demonstrated that the helix constitutes an essential part of the network graph.

Spatial resolution of the electrical conductance of ionic fluids using a Green-Kubo method

We present a Green-Kubo method to spatially resolve transport coefficients in compositionally heterogeneous mixtures. We develop the underlying theory based on well-known results from mixture theory, Irving-Kirkwood field estimation, and linear response theory. Then, using standard molecular dynamics techniques, we apply the methodology to representative systems. With a homogeneous salt water system, where the expectation of the distribution of conductivity is clear, we demonstrate the sensitivities of the method to system size, and other physical and algorithmic parameters. Then we present a simple model of an electrochemical double layer where we explore the resolution limit of the method. In this system, we observe significant anisotropy in the wall-normal vs. transverse ionic conductances, as well as near wall effects. Finally, we discuss extensions and applications to more realistic systems such as batteries where detailed understanding of the transport properties in the vicinity of the electrodes is of technological importance.