Finite-Size Effects of Binary Mutual Diffusion Coefficients from Molecular Dynamics

Experimental and computational study of binary mixture ethanolamine and 2-amino-2-methyl-1-propanol

The present work involves experimental and computational investigations into the density of pure and mixed states of ethanolamine (ET) and 2-amino-2-methyl-1-propanol (AMP) under a pressure of 1 atm and temperatures ranging from 293.15 K to 333.15 K The density data were used to derive the excess molar volume, thermal expansion coefficient, and isothermal coefficient of pressure excess molar enthalpy. The Redlich-Kister equation was employed to calculate the excess molar and its accompanying coefficients. In the gas phase, density functional theory (DFT) was utilized to explore the most stable structures of ET … ET, AMP … AMP, and the ET … AMP mixture. Molecular dynamics simulation (MD) was used to calculate the structural properties of these mixtures in the liquid phase. Radial distribution function (RDFs) combined distribution function (CDF) and spatial distribution function (SDF) in different mole fractions calculated in the liquid phase. The intramolecular and intermolecular interactions of ethanolamine and AMP were obtained using the radial distribution function in different molar fractions. It was found that the ethanolamine molecule has a greater tendency to form intramolecular hydrogen bonds, while the AMP molecule has a greater tendency to form intermolecular hydrogen bonds.

Mutual Diffusivities of Mixtures of Carbon Dioxide and Hydrogen and Their Solubilities in Brine: Insight from Molecular Simulations

H2-CO2 mixtures find wide-ranging applications, including their growing significance as synthetic fuels in the transportation industry, relevance in capture technologies for carbon capture and storage, occurrence in subsurface storage of hydrogen, and hydrogenation of carbon dioxide to form hydrocarbons and alcohols. Here, we focus on the thermodynamic properties of H2-CO2 mixtures pertinent to underground hydrogen storage in depleted gas reservoirs. Molecular dynamics simulations are used to compute mutual (Fick) diffusivities for a wide range of pressures (5 to 50 MPa), temperatures (323.15 to 423.15 K), and mixture compositions (hydrogen mole fraction from 0 to 1). At 5 MPa, the computed mutual diffusivities agree within 5% with the kinetic theory of Chapman and Enskog at 423.15 K, albeit exhibiting deviations of up to 25% between 323.15 and 373.15 K. Even at 50 MPa, kinetic theory predictions match computed diffusivities within 15% for mixtures comprising over 80% H2 due to the ideal-gas-like behavior. In mixtures with higher concentrations of CO2, the Moggridge correlation emerges as a dependable substitute for the kinetic theory. Specifically, when the CO2 content reaches 50%, the Moggridge correlation achieves predictions within 10% of the computed Fick diffusivities. Phase equilibria of ternary mixtures involving CO2-H2-NaCl were explored using Gibbs Ensemble (GE) simulations with the Continuous Fractional Component Monte Carlo (CFCMC) technique. The computed solubilities of CO2 and H2 in NaCl brine increased with the fugacity of the respective component but decreased with NaCl concentration (salting out effect). While the solubility of CO2 in NaCl brine decreased in the ternary system compared to the binary CO2-NaCl brine system, the solubility of H2 in NaCl brine increased less in the ternary system compared to the binary H2-NaCl brine system. The cooperative effect of H2-CO2 enhances the H2 solubility while suppressing the CO2 solubility. The water content in the gas phase was found to be intermediate between H2-NaCl brine and CO2-NaCl brine systems. Our findings have implications for hydrogen storage and chemical technologies dealing with CO2-H2 mixtures, particularly where experimental data are lacking, emphasizing the need for reliable thermodynamic data on H2-CO2 mixtures.

Relative Resolution: An Analysis with the Kullback-Leibler Entropy

A novel type of a multiscale approach, called Relative Resolution (RelRes), can correctly retrieve the behavior of various nonpolar liquids while speeding up molecular simulations by almost an order of magnitude. In this approach in a single system, molecules switch their resolution in terms of their relative separation, with near neighbors interacting via fine-grained potentials, yet far neighbors interacting via coarse-grained potentials; notably, these two potentials are analytically parametrized by a multipole approximation. Our current work focuses on analyzing RelRes by relating it with the Kullback-Leibler (KL) entropy, which is a useful metric for multiscale errors. In particular, we thoroughly examine the exact and approximate versions of this informatic measure for several alkane systems. By analyzing its dependency on the system size, we devise a formula for predicting the exact KL entropy of an "infinite" system via the computation of the approximate KL entropy of an "infinitesimal" system. Demonstrating that the KL entropy can holistically capture many multiscale errors, we settle bounds for the KL entropy that ensure a sufficient representation of the structural and thermal behavior by the RelRes algorithm. This, in turn, allows the scientific community to readily determine the ideal switching distance for an arbitrary RelRes system.

Connection between partial pressure, volatility, and the Soret effect elucidated using simulations of nonideal supercritical fluid mixtures

Building on recent simulation work, it is demonstrated using molecular dynamics simulations of two-component fluid mixtures that the chemical contribution to the Soret effect in two-component nonideal fluid mixtures arises due to differences in how the partial pressures of the components respond to temperature and density gradients. Further insight is obtained by reviewing the connection between activity and deviations from Raoult's law in the measurement of the vapor pressure of a liquid mixture. A new parameter γsS, defined in a manner similar to the activity coefficient, is used to characterize differences deviations from "ideal" behavior. It is then shown that the difference γ2S-γ1S is predictive of the sign of the Soret coefficient and is correlated to its magnitude. We hence connect the Soret effect to the relative volatility of the components of a fluid mixture, with the more volatile component enriched in the low-density, high-temperature region, and the less volatile component enriched in the high-density, low-temperature region. Because γsS is closely connected to the activity coefficient, this suggests the possibility that measurement of partial vapor pressures might be used to indirectly determine the Soret coefficient. It is proposed that the insight obtained here is quite general and should be applicable to a wide range of materials systems. An attempt is made to understand how these results might apply to other materials systems including interstitials in solids and multicomponent solids with interdiffusion occurring via a vacancy mechanism.

Interfacial Tensions, Solubilities, and Transport Properties of the H2/H2O/NaCl System: A Molecular Simulation Study

Data for several key thermodynamic and transport properties needed for technologies using hydrogen (H2), such as underground H2 storage and H2O electrolysis are scarce or completely missing. Force field-based Molecular Dynamics (MD) and Continuous Fractional Component Monte Carlo (CFCMC) simulations are carried out in this work to cover this gap. Extensive new data sets are provided for (a) interfacial tensions of H2 gas in contact with aqueous NaCl solutions for temperatures of (298 to 523) K, pressures of (1 to 600) bar, and molalities of (0 to 6) mol NaCl/kg H2O, (b) self-diffusivities of infinitely diluted H2 in aqueous NaCl solutions for temperatures of (298 to 723) K, pressures of (1 to 1000) bar, and molalities of (0 to 6) mol NaCl/kg H2O, and (c) solubilities of H2 in aqueous NaCl solutions for temperatures of (298 to 363) K, pressures of (1 to 1000) bar, and molalities of (0 to 6) mol NaCl/kg H2O. The force fields used are the TIP4P/2005 for H2O, the Madrid-2019 and the Madrid-Transport for NaCl, and the Vrabec and Marx for H2. Excellent agreement between the simulation results and available experimental data is found with average deviations lower than 10%.

Ideal conductor/dielectric model (ICDM): A generalized technique to correct for finite-size effects in molecular simulations of hindered ion transport

Molecular simulations serve as indispensable tools for investigating the kinetics and elucidating the mechanism of hindered ion transport across nanoporous membranes. In particular, recent advancements in advanced sampling techniques have made it possible to access translocation timescales spanning several orders of magnitude. In our prior study [Shoemaker et al., J. Chem. Theory Comput. 18, 7142 (2022)], we identified significant finite size artifacts in simulations of pressure-driven hindered ion transport through nanoporous graphitic membranes. We introduced the ideal conductor model, which effectively corrects for such artifacts by assuming the feed to be an ideal conductor. In the present work, we introduce the ideal conductor dielectric model (Icdm), a generalization of our earlier model, which accounts for the dielectric properties of both the membrane and the filtrate. Using the Icdm model substantially enhances the agreement among corrected free energy profiles obtained from systems of varying sizes, with notable improvements observed in regions proximate to the pore exit. Moreover, the model has the capability to consider secondary ion passage events, including the transport of a co-ion subsequent to the traversal of a counter-ion, a feature that is absent in our original model. We also investigate the sensitivity of the new model to various implementation details. The Icdm model offers a universally applicable framework for addressing finite size artifacts in molecular simulations of ion transport. It stands as a significant advancement in our quest to use molecular simulations to comprehensively understand and manipulate ion transport processes through nanoporous membranes.

Predicting Gaseous Solute Diffusion in Viscous Multivalent Ionic Liquid Solvents

Calculating solute diffusion in dense, viscous solvents can be particularly challenging in molecular dynamics simulations due to the long time scales involved. Here, a new scaling approach is developed for predicting solute diffusion based on analyses of CO2 and SO2 diffusion in two different multivalent ionic liquid solvents. Various scaling approaches are initially evaluated, including single and separate thermostats for the solute and solvent, as well as the application of the Arrhenius relationship and the Speedy-Angell power law. A very strong logarithmic correlation is established between the solvent-accessible surface area and solute diffusion. This relationship, reflecting Danckwerts' surface renewal theory and the Vrentas-Duda free volume model, presents a valuable method for estimating diffusion behavior from short simulation trajectories at elevated temperatures. The approach may be beneficial for enhancing predictive modeling in similar challenging systems and should be more broadly evaluated.

Puckered Zigzag Monolayer Ice: Does a Confined Flat Four-Coordinated Monolayer Ice Always Have a Corresponding Puckered Phase?

We note that a flat, four-coordinated monolayer ice under confinement always has a corresponding puckered phase. Recently, a monolayer ice consisting of an array of zigzag water chains (ZZMI) predicted by first-principles calculations of water under confinement is a flat four-coordinated monolayer ice. Herein, to investigate whether puckered ZZMI exists stably, we perform molecular dynamics simulations of two-dimensional (2D) ice formation for water constrained in graphene nanocapillaries. We find a novel monolayer ice structure that can be viewed as the ZZMI puckered along the direction perpendicular to the zigzag chain (pZZMI). Unlike ZZMI that does not satisfy the ice rule, each water molecule in pZZMI can form four hydrogen bonds (HBs) via forming two stable intersublayer HBs and two intrasublayer HBs. This work provides a fresh perspective on 2D confined ice, highlighting the intrinsic connections between 2D confined ices.

Diffusion of hydrocarbons diluted in supercritical carbon dioxide

Mutual diffusion of six hydrocarbons (methane, ethane, isobutane, benzene, toluene or naphthalene) diluted in supercritical carbon dioxide ([Formula: see text]) is studied by molecular dynamics simulation near the Widom line, i.e., in the temperature range from 290 to 345 K along the isobar 9 MPa. The [Formula: see text] + aromatics mixtures are additionally sampled at 10 and 12 MPa and an experimental database with Fick diffusion coefficient data for those systems is provided. Taylor dispersion experiments of [Formula: see text] with benzene, toluene, n-dodecane and 1,2,3,4-tetrahydronaphthalene are conducted along the [Formula: see text] 10 MPa isobar. Maxwell-Stefan and Fick diffusion coefficients are analyzed, together with the thermodynamic factor that relates them. It is found that the peculiar behavior of the Fick diffusion coefficient of some [Formula: see text] mixtures in the extended critical region is a consequence of the thermodynamic factor minimum due to pronounced clustering on the molecular scale. Further, the strong dependence of the Fick diffusion coefficient on the molecular mass of the solute as well as the breakdown of the Stokes-Einstein relation near the Widom line are confirmed. Eleven correlations for the prediction of the Fick diffusion coefficient of [Formula: see text] mixtures are assessed. An alternative two-step approach for the prediction of the infinite dilution Fick diffusion coefficient of supercritical [Formula: see text] mixtures is proposed. It requires only the state point in terms of temperature and pressure (or density) as well as the molecular solute mass as input parameters. First, entropy scaling is applied to estimate the self-diffusion coefficient of [Formula: see text]. Subsequently, this coefficient is used to determine the infinite dilution Fick diffusion coefficient of the mixture, based on the finding that these two diffusion coefficients exhibit a linear relationship, where the slope depends only on the molecular solute mass.

Mass dipole contribution to the isotopic Soret effect in molecular mixtures

Temperature gradients induce mass separation in mixtures in a process called thermal diffusion and are quantified by the Soret coefficient ST. Thermal diffusion in fluid mixtures has been interpreted recently in terms of the so-called (pseudo-)isotopic Soret effect but only considering the mass and moment of inertia differences of the molecules. We demonstrate that the first moment of the molecular mass distribution, the mass dipole, contributes significantly to the isotopic Soret effect. To probe this physical effect, we investigate fluid mixtures consisting of rigid linear molecules that differ only by the first moment of their mass distributions. We demonstrate that such mixtures have non-zero Soret coefficients in contrast with ST = 0 predicted by current formulations. For the isotopic mixtures investigated in this work, the dependence of ST on the mass dipole arises mainly through the thermal diffusion coefficient DT. In turn, DT is correlated with the dependence of the molecular librational modes on the mass dipole. We examine the interplay of the mass dipole and the moment of inertia in defining the isotopic Soret effect and propose empirical equations that include the mass dipole contribution.

Computation of Electrical Conductivities of Aqueous Electrolyte Solutions: Two Surfaces, One Property

In this work, we computed electrical conductivities under ambient conditions of aqueous NaCl and KCl solutions by using the Einstein-Helfand equation. Common force fields (charge q = ±1 e) do not reproduce the experimental values of electrical conductivities, viscosities, and diffusion coefficients. Recently, we proposed the idea of using different charges to describe the potential energy surface (PES) and the dipole moment surface (DMS). In this work, we implement this concept. The equilibrium trajectories required to evaluate electrical conductivities (within linear response theory) were obtained by using scaled charges (with the value q = ±0.75 e) to describe the PES. The potential parameters were those of the Madrid-Transport force field, which accurately describe viscosities and diffusion coefficients of these ionic solutions. However, integer charges were used to compute the conductivities (thus describing the DMS). The basic idea is that although the scaled charge describes the ion-water interaction better, the integer charge reflects the value of the charge that is transported due to the electric field. The agreement obtained with experiments is excellent, as for the first time electrical conductivities (and the other transport properties) of NaCl and KCl electrolyte solutions are described with high accuracy for the whole concentration range up to their solubility limit. Finally, we propose an easy way to obtain a rough estimate of the actual electrical conductivity of the potential model under consideration using the approximate Nernst-Einstein equation, which neglects correlations between different ions.

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.

How soluble misfolded proteins bypass chaperones at the molecular level

Subpopulations of soluble, misfolded proteins can bypass chaperones within cells. The extent of this phenomenon and how it happens at the molecular level are unknown. Through a meta-analysis of the experimental literature we find that in all quantitative protein refolding studies there is always a subpopulation of soluble but misfolded protein that does not fold in the presence of one or more chaperones, and can take days or longer to do so. Thus, some misfolded subpopulations commonly bypass chaperones. Using multi-scale simulation models we observe that the misfolded structures that bypass various chaperones can do so because their structures are highly native like, leading to a situation where chaperones do not distinguish between the folded and near-native-misfolded states. More broadly, these results provide a mechanism by which long-time scale changes in protein structure and function can persist in cells because some misfolded states can bypass components of the proteostasis machinery.

Detecting Liquid-Liquid Phase Separations Using Molecular Dynamics Simulations and Spectral Clustering

A stringent test of the accuracy of empirical force fields is reproducing the phase diagram of bulk phases and mixtures. Exploring the phase diagram of mixtures requires the detection of phase boundaries and critical points. In contrast to most solid-liquid transitions, in which a global order parameter (average density) can be used to discriminate between two phases, some demixing transitions entail relatively subtle changes in the local environment of each molecule. In such cases, finite sampling errors and finite-size effects make the identification of trends in local order parameters extremely challenging. Here we analyze one such example, namely a methanol/hexane mixture, and compute several local and global structural properties. We simulate the system at various temperatures and study the structural changes associated with demixing. We show that despite a seemingly continuous transformation between mixed and demixed states, the topological properties of the H-bond network change abruptly as the system crosses the demixing line. In particular, by using spectral clustering, we show that the distribution of cluster sizes develops a fat tail (as expected from percolation theory) in the vicinity of the critical point. We illustrate a simple criterion to identify this behavior, which results from the emergence of large system-spanning clusters from a collection of aggregates. We further tested the spectral clustering analysis on a Lennard-Jones system as a standard example of a system with no H-bonds, and also, in this case, we were able to detect the demixing transition.

Ideal Conductor Model: An Analytical Finite-Size Correction for Nonequilibrium Molecular Dynamics Simulations of Ion Transport through Nanoporous Membranes

Modulating ion transport through nanoporous membranes is critical to many important chemical and biological separation processes. The corresponding transport timescales, however, are often too long to capture accurately using conventional molecular dynamics (MD). Recently, path sampling techniques, such as forward-flux sampling (FFS), have emerged as attractive alternatives for efficiently and accurately estimating arbitrarily long ionic passage times. Here, we use non-equilibrium MD and FFS to explore how the kinetics and mechanisms of pressure-driven chloride transport through a nanoporous graphitic membrane are affected by its lateral dimensions. We not only find ionic passage times and free energy barriers to decrease dramatically upon increasing the membrane surface area but also observe an abrupt and discontinuous change in the locus of the transition state. These strong finite size effects arise due to the cumulative effect of the periodic images of the leading ion entering the pore on the distribution of the induced excess charge at the membrane surface in the feed. By assuming that the feed is an ideal conductor, we analytically derive a finite size correction term that can be computed from the information obtained from a single simulation and successfully use it to obtain corrected free energy profiles with no dependence on the system size. We then estimate ionic passage times in the thermodynamic limit by assuming an Eyring-type dependence of rates on barriers with a size-independent prefactor. This approach constitutes a universal framework for removing finite size artifacts in molecular simulations of ion transport through nanoporous membranes and biological channel proteins.

Graphene Oxide-Carbon Nanotube (GO-CNT) Hybrid Mixed Matrix Membrane for Pervaporative Dehydration of Ethanol

The pervaporation process is an energy-conservative and environmentally sustainable way for dehydration studies. It efficiently separates close boiling point and azeotrope mixtures unlike the distillation process. The separation of ethanol and water is challenging as ethanol and water form an azeotrope at 95.6 wt.% of ethanol. In the last few decades, various polymers have been used as candidates in membrane preparation for pervaporation (PV) application, which are currently used in the preparation of mixed matrix membranes (MMMs) for ethanol recovery and ethanol dehydration but have not been able to achieve an enhanced performance both in terms of flux and selectivity. Composite membranes comprising of poly (vinyl alcohol) (PVA) incorporated with carboxylated carbon nanotubes (CNT-COOH), graphene oxide (GO) and GO-CNT-COOH mixtures were fabricated for the dehydration of ethanol by pervaporation (PV). The membranes were characterized with Scanning Electron Microscopy (SEM), Fourier Transform Infrared Spectroscopy (FTIR), Thermogravimetric Analysis (TGA), Differential Scanning Calorimetry (DSC), Raman spectroscopy, Raman imaging, contact angle measurement, and water sorption to determine the effects of various nanocarbons on the intermolecular interactions, surface hydrophilicity, and degrees of swelling. The effects of feed water concentration and temperature on the dehydration performance were investigated. The incorporation of nanocarbons led to an increase in the permeation flux and separation factor. At a feed water concentration of 10 wt.%, a permeation flux of 0.87 kg/m².h and a separation factor of 523 were achieved at 23 °C using a PVA-GO-CNT-COOH hybrid membrane.

Kirkwood-Buff integrals: From fluctuations in finite volumes to the thermodynamic limit

The Kirkwood-Buff theory is a cornerstone of the statistical mechanics of liquids and solutions. It relates volume integrals over the radial distribution function, so-called Kirkwood-Buff integrals (KBIs), to particle number fluctuations and thereby to various macroscopic thermodynamic quantities such as the isothermal compressibility and partial molar volumes. Recently, the field has seen a strong revival with breakthroughs in the numerical computation of KBIs and applications to complex systems such as bio-molecules. One of the main emergent results is the possibility to use the finite volume KBIs as a tool to access finite volume thermodynamic quantities. The purpose of this Perspective is to shed new light on the latest developments and discuss future avenues.

Modelling Sorption and Transport of Gases in Polymeric Membranes across Different Scales: A Review

Professor Giulio C. Sarti has provided outstanding contributions to the modelling of fluid sorption and transport in polymeric materials, with a special eye on industrial applications such as membrane separation, due to his Chemical Engineering background. He was the co-creator of innovative theories such as the Non-Equilibrium Theory for Glassy Polymers (NET-GP), a flexible tool to estimate the solubility of pure and mixed fluids in a wide range of polymers, and of the Standard Transport Model (STM) for estimating membrane permeability and selectivity. In this review, inspired by his rigorous and original approach to representing membrane fundamentals, we provide an overview of the most significant and up-to-date modeling tools available to estimate the main properties governing polymeric membranes in fluid separation, namely solubility and diffusivity. The paper is not meant to be comprehensive, but it focuses on those contributions that are most relevant or that show the potential to be relevant in the future. We do not restrict our view to the field of macroscopic modelling, which was the main playground of professor Sarti, but also devote our attention to Molecular and Multiscale Hierarchical Modeling. This work proposes a critical evaluation of the different approaches considered, along with their limitations and potentiality.

Toward Bottom-Up Understanding of Transport in Concentrated Battery Electrolytes

Bottom-up understanding of transport describes how molecular changes alter species concentrations and electrolyte voltage drops in operating batteries. Such an understanding is essential to predictively design electrolytes for desired transport behavior. We herein advocate building a structure-property-performance relationship as a systematic approach to accurate bottom-up understanding. To ensure generalization across salt concentrations as well as different electrolyte types and cell configurations, the property-performance relation must be described using Newman's concentrated solution theory. It uses Stefan-Maxwell diffusivity, _ij , to describe the role of molecular motions at the continuum scale. The key challenge is to connect _ij to the structure. We discuss existing methods for making such a connection, their peculiarities, and future directions to advance our understanding of electrolyte transport.

Symbolic regression development of empirical equations for diffusion in Lennard-Jones fluids

Symbolic regression (SR) with a multi-gene genetic program has been used to elucidate new empirical equations describing diffusion in Lennard-Jones (LJ) fluids. Examples include equations to predict self-diffusion in pure LJ fluids and equations describing the finite-size correction for self-diffusion in binary LJ fluids. The performance of the SR-obtained equations was compared to that of both the existing empirical equations in the literature and to the results from artificial neural net (ANN) models recently reported. It is found that the SR equations have improved predictive performance in comparison to the existing empirical equations, even though employing a smaller number of adjustable parameters, but show an overall reduced performance in comparison to more extensive ANNs.

Prediction of Self-Diffusion in Binary Fluid Mixtures Using Artificial Neural Networks

Artificial neural networks (ANNs) were developed to accurately predict the self-diffusion constants for individual components in binary fluid mixtures. The ANNs were tested on an experimental database of 4328 self-diffusion constants from 131 mixtures containing 75 unique compounds. The presence of strong hydrogen bonding molecules may lead to clustering or dimerization resulting in non-linear diffusive behavior. To address this, self- and binary association energies were calculated for each molecule and mixture to provide information on intermolecular interaction strength and were used as input features to the ANN. An accurate, generalized ANN model was developed with an overall average absolute deviation of 4.1%. Forward input feature selection reveals the importance of critical properties and self-association energies along with other fluid properties. Additional ANNs were developed with subsets of the full input feature set to further investigate the impact of various properties on model performance. The results from two specific mixtures are discussed in additional detail: one providing an example of strong hydrogen bonding and the other an example of extreme pressure changes, with the ANN models predicting self-diffusion well in both cases.

Ion Specificity of Confined Ion-Water Structuring and Nanoscale Surface Forces in Clays

Ion specificity and related Hofmeister effects, which are ubiquitous in aqueous systems, can have spectacular consequences in hydrated clays, where ion-specific nanoscale surface forces can determine large-scale cohesive swelling and shrinkage behaviors of soil and sediments. We have used a semiatomistic computational approach and examined sodium, calcium, and aluminum counterions confined with water between charged surfaces representative of clay materials to show that ion-water structuring in nanoscale confinement is at the origin of surface forces between clay particles which are intrinsically ion-specific. When charged surfaces strongly confine ions and water, the amplitude and oscillations of the net pressure naturally emerge from the interplay of electrostatics and steric effects, which cannot be captured by existing theories. Increasing confinement and surface charge densities promote ion-water structures that increasingly deviate from the ions' bulk hydration shells, being strongly anisotropic, persistent, and self-organizing into optimized, nearly solid-like assemblies where hardly any free water is left. Under these conditions, strongly attractive interactions can prevail between charged surfaces because of the dramatically reduced dielectric screening of water and the highly organized water-ion structures. By unravelling the ion-specific nature of these nanoscale interactions, we provide evidence that ion-specific solvation structures determined by confinement are at the origin of ion specificity in clays and potentially a broader range of confined aqueous systems.

Structure and Dynamics of Adsorbed Dopamine on Solvated Carbon Nanotubes and in a CNT Groove

Advanced carbon microelectrodes, including many carbon-nanotube (CNT)-based electrodes, are being developed for the in vivo detection of neurotransmitters such as dopamine (DA). Our prior simulations of DA and dopamine-o-quinone (DOQ) on pristine, flat graphene showed rapid surface diffusion for all adsorbed species, but it is not known how CNT surfaces affect dopamine adsorption and surface diffusivity. In this work, we use molecular dynamics simulations to investigate the adsorbed structures and surface diffusion dynamics of DA and DOQ on CNTs of varying curvature and helicity. In addition, we study DA dynamics in a groove between two aligned CNTs to model the spatial constraints at the junctions within CNT assemblies. We find that the adsorbate diffusion on a solvated CNT surface depends upon curvature. However, this effect cannot be attributed to changes in the surface energy roughness because the lateral distributions of the molecular adsorbates are similar across curvatures, diffusivities on zigzag and armchair CNTs are indistinguishable, and the curvature dependence disappears in the absence of solvent. Instead, adsorbate diffusivities correlate with the vertical placement of the adsorbate’s moieties, its tilt angle, its orientation along the CNT axis, and the number of waters in its first hydration shell, all of which will influence its effective hydrodynamic radius. Finally, DA diffuses into and remains in the groove between a pair of aligned and solvated CNTs, enhancing diffusivity along the CNT axis. These first studies of surface diffusion on a CNT electrode surface are important for understanding the changes in diffusion dynamics of dopamine on nanostructured carbon electrode surfaces.

Investigating finite-size effects in molecular dynamics simulations of ion diffusion, heat transport, and thermal motion in superionic materials

The effects of the finite size of the simulation box in equilibrium molecular dynamics simulations are investigated for prototypical superionic conductors of different types, namely, the fluorite-structure materials PbF₂, CaF₂, and UO₂ (type II), and the α phase of AgI (type I). Largely validated empirical force-fields are employed to run ns-long simulations and extract general trends for several properties, at increasing size and in a wide temperature range. This work shows that, for the considered type-II superionic conductors, the diffusivity dramatically depends on the system size and that the superionic regime is shifted to larger temperatures in smaller cells. Furthermore, only simulations of several hundred atoms are able to capture the experimentally observed, characteristic change in the activation energy of the diffusion process, occurring at the order-disorder transition to the superionic regime. Finite-size effects on ion diffusion are instead much weaker in α-AgI. The thermal conductivity is found generally smaller for smaller cells, where the temperature-independent (Allen-Feldman) regime is also reached at significantly lower temperatures. The finite-size effects on the thermal motion of the non-mobile ions composing the solid matrix follow the simple law that holds for solids.

Bootstrapping time correlation functions of molecular dynamics

Molecular dynamics is often considered as a numerical experiment. The error bars on the results are therefore mandatory, but sometimes difficult to determine and computationally demanding. As a low-cost approach, we describe the application of the bootstrap (BS) method to the quantification of uncertainties pertaining to the time correlation functions. We chose the autocorrelation functions of velocity and interdiffusion current for a binary ionic mixture as a test bed, and we assessed the merit of the Darken approximation relating both of them. The intrinsic errors related to phase space sampling is investigated comparing the BS method with the reference method of replica. We also study how the BS method can assist in addressing the finite-size effects.

Computational Screening of Physical Solvents for CO2 Pre-combustion Capture

A computational scheme was used to screen physical solvents for CO₂ pre-combustion capture by integrating the commercial NIST database, an in-house computational database, chem-informatics, and molecular modeling. A commercially available screened hydrophobic solvent, diethyl sebacate, was identified from the screening with favorable physical properties and promising absorption performance. The promising performance to use diethyl sebacate in CO₂ pre-combustion capture has also been confirmed from experiments. Water loading in diethyl sebacate is very low, and therefore, water is kept with H₂ in the gas stream. The favorable CO₂ interaction with diethyl sebacate and the intermediate solvent free volume fraction leads to both high CO₂ solubility and high CO₂/H₂ solubility selectivity in diethyl sebacate. An in-house NETL computational database was built to characterize CO₂, H₂, N₂, and H₂O interactions with 202 different chemical functional groups. It was found that 13% of the functional groups belong to the strong interaction category with the CO₂ interaction energy between -15 and -21 kJ/mol; 62% of the functional groups interact intermediately with CO₂ (-8 to -15 kJ/mol). The remaining 25% of functional groups interact weakly with CO₂ (below -8 kJ/mol). In addition, calculations show that CO₂ interactions with the functional groups are stronger than N₂ and H₂ interactions but are weaker than H₂O interactions. The CO₂ and H₂O interactions with the same functional groups exhibit a very strong linear positive correlation coefficient of 0.92. The relationship between CO₂ and H₂ gas solubilities and solvent fractional free volume (FFV) has been systematically studied for seven solvents at 298.2 K. A skewed bell-shaped relation was obtained between CO₂ solubility and solvent FFV. When an organic compound has a density approximately 10% lower than its density at 298.2 K and 1 bar, it exhibits the highest CO₂ loading at that specific solvent density and FFV. Note that the solvent densities were varied using simulations, which are difficult to be obtained from the experiment. In contrast, H₂ solubility results exhibit an almost perfect positive linear correlation with the solvent FFV. The theoretical maximum and minimum physical CO₂ solubilities in any organic compound at 298.2 K were estimated to be 11 and 0.4 mol/MPa L, respectively. An examination of 182 experimental CO₂ physical solubility data and 29 simulated CO₂ physical solubilities shows that all the CO₂ physical solubility data are within the maximum and minimum with only a few exceptions. Finally, simulations suggest that in order to develop physical solvents with both high CO₂ solubility and high CO₂/H₂ solubility selectivity, the solvents should contain functional groups which are available to interact strongly with CO₂ while minimizing FFV.

Water accelerates the hydrogen-bond dynamics and abates heterogeneity in deep eutectic solvent based on acetamide and lithium perchlorate

Deep eutectic solvents (DESs) have become a prevalent and promising medium in various industrial applications. The addition of water to DESs has attracted a lot of attention as a scheme to modulate their functionalities and improve their physicochemical properties. In this work, we study the effects of water on an acetamide based DES by probing its microscopic structure and dynamics using classical molecular dynamics simulation. It is observed that, at low water content, acetamide still remains the dominant solvate in the first solvation shell of lithium ions, however, beyond 10 wt. %, it is replaced by water. The increase in the water content in the solvent accelerates the H-bond dynamics by drastically decreasing the lifetimes of acetamide-lithium H-bond complexes. Additionally, water-lithium H-bond complexes are also found to form, with systematically longer lifetimes in comparison to acetamide-lithium complexes. Consequently, the diffusivity and ionic conductivity of all the species in the DES are found to increase substantially. Non-Gaussianity parameters for translational motions of acetamide and water in the DES show a conspicuous decrease with addition of water in the system. The signature of jump-like reorientation of acetamide is observed in the DES by quantifying the deviation from rotational Brownian motion. However, a notable decrease in the deviation is observed with an increase in the water content in the DES. This study demonstrates the intricate connection between H-bond dynamics and various microscopic dynamical parameters in the DES, by investigating the modulation of the former with addition of water.

How sensitive are physical properties of choline chloride-urea mixtures to composition changes: Molecular dynamics simulations and Kirkwood-Buff theory

Deep eutectic solvents (DESs) have emerged as a cheaper and greener alternative to conventional organic solvents. Choline chloride (ChCl) mixed with urea at a molar ratio of 1:2 is one of the most common DESs for a wide range of applications such as electrochemistry, material science, and biochemistry. In this study, molecular dynamics simulations are performed to study the effect of urea content on the thermodynamic and transport properties of ChCl and urea mixtures. With increased mole fraction of urea, the number of hydrogen bonds (HBs) between cation-anion and ion-urea decreases, while the number of HBs between urea-urea increases. Radial distribution functions (RDFs) for ChCl-urea and ChCl-ChCl pairs shows a significant decrease as the mole fraction of urea increases. Using the computed RDFs, Kirkwood-Buff Integrals (KBIs) are computed. KBIs show that interactions of urea-urea become stronger, while interactions of urea-ChCl and ChCl-ChCl pairs become slightly weaker with increasing mole fraction of urea. All thermodynamic factors are found larger than one, indicating a non-ideal mixture. Our results also show that self- and collective diffusivities increase, while viscosities decrease with increasing urea content. This is mainly due to the weaker interactions between ions and urea, resulting in enhanced mobilities. Ionic conductivities exhibit a non-monotonic behavior. Up to a mole fraction of 0.5, the ionic conductivities increase with increasing urea content and then reach a plateau.

Hyperdynamics simulations with ab initio forces

By applying the locally optimal rotation method to deal with the lowest eigenvalue of a Hessian matrix, we have efficiently incorporated the hyperdynamics method into the ab initio scheme. In the present method, we only need to calculate the first derivative of the potential and several more force calls in each molecular dynamics (MD) step, which makes hyperdynamics simulation applicable in ab initio MD simulations. With this implementation, we are able to simulate defect diffusion in silicon with boost factors up to 10⁵. We utilized both direct MD and the hyperdynamics method to investigate diffusion of lithium atoms and silicon vacancies in silicon. We identified the complex diffusion process. The obtained diffusion coefficients of Li atoms and Si vacancies are in good agreement with the direct MD results.

Fick Diffusion Coefficient in Binary Mixtures of [HMIM][NTf2] and Carbon Dioxide by Dynamic Light Scattering and Molecular Dynamics Simulations

Dynamic light scattering (DLS) experiments and equilibrium molecular dynamics (EMD) simulations were performed in the saturated liquid phase of the binary mixture of 1-hexyl-3-methylimidazolium bis(trifluormethylsulfonyl)imide ([HMIM][NTf₂]) and carbon dioxide (CO₂) to access the Fick diffusion coefficient (D₁₁). The investigations were performed within or close to saturation conditions at temperatures between (298.15 and 348.15) K and CO₂ mole fractions (x_CO2) up to 0.81. The DLS experiments were combined with polarization-difference Raman spectroscopy (PDRS) to simultaneously access the composition of the liquid phase. For the first time in an electrolyte-based system, D₁₁ was directly calculated from EMD simulations by accessing the Maxwell-Stefan (MS) diffusion coefficient and the thermodynamic factor. Agreement within combined uncertainties was found between D₁₁ from DLS and EMD simulations for CO₂ mole fractions up to 0.5. In general, an increasing D₁₁ with increasing x_CO2 could be observed, with a local maximum present at a CO₂ mole fraction of about 0.75. The local maximum could be explained by an increasing MS diffusion coefficient with increasing x_CO2 over the entire studied composition range and a decreasing thermodynamic factor at x_CO2 above 0.7. Finally, PDRS and EMD simulations were combined to investigate the influence of the fluid structure on the diffusive process.

Insights into the interactions and dynamics of a DES formed by phenyl propionic acid and choline chloride

Deep eutectic solvents (DESs) have received much attention in modern green chemistry as inexpensive and easy to handle analogous ionic liquids. This work employed molecular dynamics techniques to investigate the structure and dynamics of a DES system composed of choline chloride and phenyl propionic acid as a hydrogen bond donor and acceptor, respectively. Dynamical parameters such as mean square displacement, liquid phase self-diffusion coefficient and viscosity are calculated at the pressure of 0.1 MPa and temperatures 293, 321 and 400 K. The system size effect on the self-diffusion coefficient of DES species was also examined. Structural parameters such as liquid phase densities, hydrogen bonds, molecular dipole moment of species, and radial and spatial distribution functions (RDF and SDF) were investigated. The viscosity of the studied system was compared with the experimental values recently reported in the literature. A good agreement was observed between simulated and experimental values. The electrostatic and van der Waals nonbonding interaction energies between species were also evaluated and interpreted in terms of temperature. These investigations could play a vital role in the future development of these designer solvents.

Diffusion of the carbon dioxide-ethanol mixture in the extended critical region

The effect of traces of ethanol in supercritical carbon dioxide on the mixture's thermodynamic properties is studied by molecular simulations and Taylor dispersion measurements. This mixture is investigated along the isobar p = 10 MPa in the temperature range between T = 304 and 343 K. Along this path, the mixture undergoes two transitions: First, the Widom line is crossed, marking the transition from liquid-like to gas-like conditions. A second transition occurs from the supercritical gas-like domain to a subcritical gas. The Widom line crossover entails inflection points for most of the studied properties, i.e. density, enthalpy, shear viscosity, Maxwell-Stefan and intradiffusion coefficients. On the other hand, the transition between the super- and subcritical regions is found to be generally smooth, an observation that is qualitatively confirmed by experimental Taylor dispersion measurements. Dedicated atomistic simulations show the presence of microheterogeneities due to ethanol self-association along the investigated path, which lead to the mixture's anomalous behavior in its extended critical region.

Relative Resolution: A Computationally Efficient Implementation in LAMMPS

Recently, a novel type of multiscale simulation, called Relative Resolution (RelRes), was introduced. In a single system, molecules switch their resolution in terms of their relative separation, with near neighbors interacting via fine-grained potentials yet far neighbors interacting via coarse-grained potentials; notably, these two potentials are analytically parametrized by a multipole approximation. This multiscale approach is consequently able to correctly retrieve across state space the structural and thermal, as well as static and dynamic, behavior of various nonpolar mixtures. Our current work focuses on the practical implementation of RelRes in LAMMPS, specifically for the commonly used Lennard-Jones potential. By examining various correlations and properties of several alkane liquids, including complex solutions of alternate cooligomers and block copolymers, we confirm the validity of this automated LAMMPS algorithm. Most importantly, we demonstrate that this RelRes implementation gains almost an order of magnitude in computational efficiency, as compared with conventional simulations. We thus recommend this novel LAMMPS algorithm for anyone studying systems governed by Lennard-Jones interactions.