Binary Lennard-Jones Mixture Research Articles

Propagation gap for shear waves in binary liquids: Analytical and simulation study.

Transverse collective excitations in 50-50 and 80-20 Lennard-Jones binary liquid mixtures are studied for different mass ratio of components R at fixed numerical densities. Increasing the mass ratio results in a growing difference between frequencies of shear waves and transverse optic modes. We report an increase in the propagation gap width for shear waves with mass ratio of components and compare it to the gap width expression, known from the transverse dynamics of simple liquids. A four-variable dynamic model of transverse dynamics in binary liquids with an account of cross correlations between total-mass and mass-concentration transverse current fluctuations is solved analytically in the long-wavelength region. An equation for the propagation gap of shear waves for binary liquids is reported and analyzed.

Equilibrium thermodynamic properties of Lennard–Jones fluid mixtures from a single-component effective fluid model

ABSTRACT The equilibrium thermodynamic properties of binary Lennard–Jones mixtures are determined by means of a Monte Carlo-based perturbation theory for an effective single-component fluid. The results for the equation of state and the excess energy are compared with simulation data obtained for two equimolar binary Lennard–Jones fluid mixtures at different temperatures along a wide range of densities. The satisfactory accuracy achieved seems to suggest that this approach might be a useful tool to deal with mixtures with a wide variety of intermolecular interactions including mixtures of real fluids.

Relationship between Diffusion Coefficients in Nonideal Binary Lennard-Jones Mixtures and Entropy

Relationship between Diffusion Coefficients in Nonideal Binary Lennard-Jones Mixtures and Entropy

Mass Transfer through Vapor–Liquid Interfaces Studied by Non-Stationary Molecular Dynamics Simulations

Molecular dynamics (MD) simulations are highly attractive for studying the influence of interfacial effects, such as the enrichment of components, on the mass transfer through the interface. In a recent work, we have presented a steady-state MD simulation method for investigating this phenomenon and tested it using model mixtures with and without interfacial enrichment. The present study extends this work by introducing a non-stationary MD simulation method. A rectangular simulation box that contains a mixture of two components 1 + 2 with a vapor phase in the middle and two liquid phases on both sides is used. Starting from a vapor-liquid equilibrium state, a non-stationary molar flux of component 2 is induced by inserting particles of component 2 into the center of the vapor phase in a pulse-like manner. During the isothermal relaxation process, particles of component 2 pass through the vapor phase, cross the vapor-liquid interface, and enter the liquid phase. The system thereby relaxes into a new vapor-liquid equilibrium state. During the relaxation process, spatially resolved responses for the component densities, fluxes, and pressure are sampled. To reduce the noise and provide measures for the uncertainty of the observables, a set of replicas of simulations is carried out. The new simulation method was applied to study mass transfer in two binary Lennard-Jones mixtures: one that exhibits a strong enrichment of the low-boiling component 2 at the vapor-liquid interface and one that shows no enrichment. Even though both mixtures have similar transport coefficients in the bulk phases, the results for mass transfer differ significantly, indicating that the interfacial enrichment influences the mass transfer.

Continuous fractional component Gibbs ensemble Monte Carlo

A continuous fractional component (CFC) approach increases the probability of particle swaps in the context of vapor-liquid equilibrium simulations using the Gibbs ensemble Monte Carlo algorithm. Two variants of the CFC approach are compared for simulations of pure Lennard-Jones (LJ) fluids and binary LJ mixtures as examples. The details of an exemplary CFC implementation are presented. Recommendations are provided to reduce the effort required for the suggested problems.

Phase equilibria of symmetric Lennard-Jones mixtures and a look at the transport properties near the upper critical solution temperature.

This study investigates phase equilibria and transport properties of five symmetric binary Lennard-Jones mixtures using molecular simulation and equation of state models. The mixtures are selected for their representation of different types of phase behavior and the research contributes to the development of simulation techniques, mixture theories and understanding of thermophysical mixture properties. A novel method is introduced for determining the critical end point (CEP) and critical azeotropic end point (CAEP) by molecular simulation. The van der Waals one-fluid theory is assessed for its performance in conjunction with Lennard-Jones equation of state models, while addressing different phase equilibrium types simultaneously. An empirical correlation is introduced to account for deviations between the equation of state and simulation that arise when using the same binary interaction parameter. This study also investigates the influence of the liquid-liquid critical point on thermophysical properties, which are found to exhibit no significant anomalies or singularities. System-size effects of diffusion coefficients are addressed by extrapolating simulation data to the thermodynamic limit and applying analytical finite-size corrections.

Predicting Scaling Properties from a Single Fluid Configuration.

Time-dependent dynamical properties of a fluid cannot be estimated directly from a single configuration without performing a simulation. Here, however, we present a method that predicts the scaling properties of both structure and dynamics from a single configuration. The method is demonstrated to work well for the Lennard-Jones fluid as well as the viscous Kob-Andersen Lennard-Jones mixture, both in and out of equilibrium. The method is conceptually simple and easy to implement and, thus, should become a standard tool in the study of scaling properties of fluids and liquids.

Gas-liquid interface of a Lennard-Jones binary mixture controlled by differential activity: phase transition and interfacial stability.

We perform molecular dynamics simulations of a two-dimensional binary mixture of Lennard-Jones particles, characterized by some degree of "activity" inside. Starting from a base state that features a gas-liquid interface and a completely segregated system at thermodynamic equilibrium, we introduce differential scalar activity between the two species by prescribing two different effective temperatures. The differential activity is measured as the ratio of the two temperatures. Previous studies showed segregation in a homogeneously mixed system induced by high activity. In this study, we investigate the effect of activity on a pre-existing gas-liquid interface between two separated species. Whereas a high activity ratio induces the formation of new interfaces, we show that a low activity ratio destabilizes existing ones. Moreover, the combination of a pre-existent interface with differential activity leads to partial crystallization and thus to triple phase coexistence (solid, liquid and gas), which is observed over a wide range of moderate differential activities. Findings from this idealized system can guide our understanding of interfacial behaviors in certain biological systems.

Transport properties of binary Lennard-Jones mixtures: Insights from entropy scaling and conformal solution theory

The relation of transport properties and the molecular interactions in binary mixtures was studied. The self-diffusion coefficient, Maxwell–Stefan as well as Fickian mutual diffusion coefficient, shear viscosity, and thermal conductivity of liquid binary simple mixtures were therefore sampled using molecular dynamics simulations. The mixtures were described by the Lennard-Jones potential. The molecular interaction parameters were chosen such that a large variety of mixture behavior was covered. The two components had the same size parameter in all cases, but different dispersion energies. Moreover, the cross-interaction parameter used in the modified Lorentz-Berthelot combination rule was varied such that the resulting mixtures showed different types of phase behavior: ideal, high- and low-boiling azeotrope. The results are discussed using conformal solution theory as a link between the molecular interactions in the mixtures and the macroscopic properties. Moreover, the applicability of Rosenfeld’s entropy scaling is tested. Despite the important differences of the studied mixtures regarding their molecular interactions and the large pressure, temperature, and composition range considered, a practically monovariate relation of these properties with respect to the configurational entropy is observed. Yet, the quality of the approximation differs for the studied properties.

Importance of feature construction in machine learning for phase transitions.

Machine learning is an important tool in the study of the phase behavior from molecular simulations. In this work, we use un-supervised machine learning methods to study the phase behavior of two off-lattice models, a binary Lennard-Jones (LJ) mixture and the Widom-Rowlinson (WR) non-additive hard-sphere mixture. The majority of previous work has focused on lattice models, such as the 2D Ising model, where the values of the spins are used as the feature vector that is input into the machine learning algorithm, with considerable success. For these two off-lattice models, we find that the choice of the feature vector is crucial to the ability of the algorithm to predict a phase transition, and this depends on the particular model system being studied. We consider two feature vectors, one where the elements are distances of the particles of a given species from a probe (distance-based feature) and one where the elements are +1 if there is an excess of particles of the same species within a cut-off distance and -1 otherwise (affinity-based feature). We use principal component analysis and t-distributed stochastic neighbor embedding to investigate the phase behavior at a critical composition. We find that the choice of the feature vector is the key to the success of the unsupervised machine learning algorithm in predicting the phase behavior, and the sophistication of the machine learning algorithm is of secondary importance. In the case of the LJ mixture, both feature vectors are adequate to accurately predict the critical point, but in the case of the WR mixture, the affinity-based feature vector provides accurate estimates of the critical point, but the distance-based feature vector does not provide a clear signature of the phase transition. The study suggests that physical insight into the choice of input features is an important aspect for implementing machine learning methods.

Molecular simulations and hydrodynamic theory of nonlocal shear-stress correlations in supercooled fluids.

A supercooled fluid close to the glass transition develops nonlocal shear-stress correlations that anticipate the emergence of elasticity. We performed molecular dynamics simulations of a binary Lennard-Jones mixture at different temperatures and investigated the spatiotemporal autocorrelation function of the shear stress for different wavevectors, q, from a locally measured and Fourier-transformed stress tensor. Anisotropic correlations are observed at non-zero wavevectors, exhibiting strongly damped oscillations with a characteristic frequency ω(q). A comparison with a recently developed hydrodynamic theory [Maier et al., Phys. Rev. Lett. 119, 265701 (2017)] shows a remarkably good quantitative agreement between particle-based simulations and theoretical predictions.

Glass-forming ability of binary Lennard-Jones systems

The glass-forming ability (GFA) of alloys, colloidal dispersions, and other particulate materials, as measured by the critical cooling rate $R_c$, can span more than ten orders of magnitude. Even after numerous previous studies, the physical features that control the GFA are still not well understood. For example, it is well-known that mixtures are better glass-formers than monodisperse systems and that particle size and cohesive energy differences among constituents improve the GFA, but it is not currently known how particle size differences couple to cohesive energy differences to determine the GFA. We perform molecular dynamics simulations to determine the GFA of equimolar, binary Lennard-Jones (LJ) mixtures versus the normalized cohesive energy difference $\epsilon_\_$ and mixing energy $\bar \epsilon_{AB}$ between particles A and B. We find several important results. First, the $\log_{10} R_c$ contours in the $\bar \epsilon_{AB}$-$\epsilon_\_$ plane are ellipsoidal for all diameter ratios, and thus $R_c$ is determined by the Mahalanobis distance $d_M$ from a given point in the $\bar \epsilon_{AB}$-$\epsilon_\_$ plane to the center of the ellipsoidal contours. Second, LJ systems for which the larger particles have larger cohesive energy are generally better glass formers than those for which the larger particles have smaller cohesive energy. Third, $d_M(\epsilon_\_,\bar \epsilon_{AB})$ is determined by the relative Voronoi volume difference between particles and local chemical order $S_{AB}$, which gives the average fraction of nearest-neighbor B particles surrounding an A particle and vice-versa. In particular, the shifted Mahalanobis distance $d_M - d^0_M$ versus the shifted chemical order $S_{AB}-S_{AB}^0$ collapses onto a hyperbolic master curve for all diameter ratios.

The structural difference between strong and fragile liquids

A structural order parameter for disordered configurations is defined, based, not on local topologies, but on the degree of local restraint imposed on each atom. This restraint parameter provides a clear distinction between a strong liquid (SiO 2 ) and a fragile liquid (a binary Lennard-Jones mixture) without reference to dynamics. Where the fragile liquid exhibits an abrupt transition from unrestrained to restrain below the melting point, molten silica is highly constrained even at equilibrium. We determine the temperature dependence of the average number of particles restrained per pinned particle and consider the feature of the potential energy landscape responsible for determining the fragility.

A classical density functional approach to depletion interaction of Lennard-Jones binary mixtures

In this article, we apply classical density functional theory to investigate the characteristics of depletion interaction in Lennard-Jones (LJ) binary fluid mixtures. First, to confirm the validity of our adopted density functional formalism, we calculate the radial distribution functions using a theoretical approach and compare them with results obtained by molecular dynamics simulation. Then, this approach is applied to two colloids immersed in LJ solvent systems. We investigate the variation of depletion interaction with respect to the distance of two colloids in LJ binary systems. We find that depletion interaction may be attractive or repulsive, mostly depending on the bulk density of the solvent and the temperature of the binary system. For high bulk densities, the repulsive barrier of depletion force is remarkable when the total excluded volume of colloids touches each other and reaches a maximum. The height of the repulsive barrier is related to the parameters of the LJ potential and bulk density. Moreover, the depletion force may exhibit attractive wells if the bulk density of the solvent is low. The attractive well tends to appear when the surface–surface distance of colloids is half of the size of the polymer and deepens with temperature lowering in a fixed bulk density. In contrast with the hard-sphere system, no oscillation of depletion potential around zero is observed.

Phase equilibria and stability boundaries in a two[sbnd]component Lennard-Jones mixture

The mechanical and diffusion stability conditions of binary Lennard-Jones mixtures with respect to infinitesimal changes in state parameters are considered. In stable and metastable states, by molecular dynamics method, the pressure is determined as a function of temperature, density and composition of a Lennard-Jones mixture simulating the methane–nitrogen system. The phase equilibrium parameters are calculated. Based on the data obtained, a unified mixture state equation for liquid and vapor was created. The diffusion and mechanical spinodals of the mixture were determined.

A symmetry-orientated divide-and-conquer method for crystal structure prediction.

Crystal structure prediction has been a subject of topical interest but remains a substantial challenge especially for complex structures as it deals with the global minimization of the extremely rugged high-dimensional potential energy surface. In this paper, a symmetry-orientated divide-and-conquer scheme was proposed to construct a symmetry tree graph, where the entire search space is decomposed into a finite number of symmetry dependent subspaces. An artificial intelligence-based symmetry selection strategy was subsequently devised to select the low-lying subspaces with high symmetries for global exploration and in-depth exploitation. Our approach can significantly simplify the problem of crystal structure prediction by avoiding exploration of the most complex P1 subspace on the entire search space and has the advantage of preserving the crystal symmetry during structure evolution, making it well suitable for predicting the complex crystal structures. The effectiveness of the method has been validated by successful prediction of the candidate structures of binary Lennard-Jones mixtures and the high-pressure phase of ice, containing more than 100 atoms in the simulation cell. The work therefore opens up an opportunity toward achieving the long-sought goal of crystal structure prediction of complex systems.

Generalized mode-coupling theory for mixtures of Brownian particles

Generalized mode-coupling theory (GMCT) has recently emerged as a promising first-principles theory to study the poorly understood dynamics of glass-forming materials. Formulated as a hierarchical extension of standard mode-coupling theory (MCT), it is able to systematically improve its predictions by including the exact dynamics of higher-order correlation functions into its hierarchy. However, in contrast to Newtonian dynamics, a fully generalized version of the theory based on Brownian dynamics is still lacking. To close this gap, we provide a detailed derivation of GMCT for colloidal mixtures obeying a many-body Smoluchowski equation. We demonstrate that a hierarchy of coupled equations can again be established and show that these, consistent with standard MCT, are identical to the ones obtained from Newtonian GMCT when taking the overdamped limit. Consequently, the nontrivial similarity between Brownian and Newtonian MCT is maintained for our multicomponent GMCT. As a proof of principle, we also solve the generalized mode-coupling equations for the binary Kob-Andersen Lennard-Jones mixture undergoing Brownian dynamics and confirm the improved predictive power of the theory upon using more levels of the GMCT hierarchy of equations.

Isomorph Invariance of Higher-Order Structural Measures in Four Lennard-Jones Systems.

In the condensed liquid phase, both single- and multicomponent Lennard–Jones (LJ) systems obey the “hidden-scale-invariance” symmetry to a good approximation. Defining an isomorph as a line of constant excess entropy in the thermodynamic phase diagram, the consequent approximate isomorph invariance of structure and dynamics in appropriate units is well documented. However, although all measures of the structure are predicted to be isomorph invariant, with few exceptions only the radial distribution function (RDF) has been investigated. This paper studies the variation along isomorphs of the nearest-neighbor geometry quantified by the occurrence of Voronoi structures, Frank–Kasper bonds, icosahedral local order, and bond-orientational order. Data are presented for the standard LJ system and for three binary LJ mixtures (Kob–Andersen, Wahnström, ). We find that, while the nearest-neighbor geometry generally varies significantly throughout the phase diagram, good invariance is observed along the isomorphs. We conclude that higher-order structural correlations are no less isomorph invariant than is the RDF.

Single-parameter aging in a binary Lennard-Jones system.

This paper studies physical aging by computer simulations of a 2:1 Kob-Andersen binary Lennard-Jones mixture, a system that is less prone to crystallization than the standard 4:1 composition. Starting from thermal-equilibrium states, the time evolution of the following four quantities is monitored by following up and down jumps in temperature: potential energy, virial, average squared force, and the Laplacian of the potential energy. Despite the fact that significantly larger temperature jumps are studied here than in typical similar experiments, to a good approximation, all four quantities conform to the single-parameter-aging scenario derived and validated for small jumps in experiments [T. Hecksher, N. B. Olsen, and J. C. Dyre, J. Chem. Phys. 142, 241103 (2015)]. As a further confirmation of single-parameter aging with a common material time for the four different quantities monitored, their relaxing parts are found to be almost identical for all temperature jumps.

Isomorphs in nanoconfined liquids.

We study in this paper the possible existence of Roskilde-simple liquids and their isomorphs in a rough-wall nanoconfinement. Isomorphs are curves in the thermodynamic phase diagram along which structure and dynamics are invariant in suitable nondimensionalized units. Two model liquids using molecular dynamics computer simulations are considered: the single-component Lennard-Jones (LJ) liquid and the Kob–Andersen binary LJ mixture, both of which in the bulk phases are known to have good isomorphs. Nanoconfinement is implemented by adopting a slit-pore geometry with fcc crystalline walls; this implies inhomogenous density profiles both parallel and perpendicular to the confining walls. Despite this fact and consistent with an earlier study [Ingebrigtsen et al., Phys. Rev. Lett., 2013, 111, 235901] we find that these two nanoconfined liquids have isomorphs to a good approximation. More specifically, we show good invariance along the isomorphs of inhomogenous density profiles, mean-square displacements, and higher-order structures probed using the topological cluster classification algorithm. Our study thus provides an alternative framework for understanding nanoconfined liquids.