A Comparison of Classical Force-Fields for Molecular Dynamics Simulations of Lubricants

Temperature-Dependent Density and Viscosity Prediction for Hydrocarbons: Machine Learning and Molecular Dynamics Simulations

Machine learning-based predictive models allow rapid and reliable prediction of material properties and facilitate innovative materials design. Base oils used in the formulation of lubricant products are complex hydrocarbons of varying sizes and structure. This study developed Gaussian process regression-based models to accurately predict the temperature-dependent density and dynamic viscosity of 305 complex hydrocarbons. In our approach, strongly correlated/collinear predictors were trimmed, important predictors were selected by least absolute shrinkage and selection operator (LASSO) regularization and prior domain knowledge, hyperparameters were systematically optimized by Bayesian optimization, and the models were interpreted. The approach provided versatile and quantitative structure-property relationship (QSPR) models with relatively simple predictors for determining the dynamic viscosity and density of complex hydrocarbons at any temperature. In addition, we developed molecular dynamics simulation-based descriptors and evaluated the feasibility and versatility of dynamic descriptors from simulations for predicting the material properties. It was found that the models developed using a comparably smaller pool of dynamic descriptors performed similarly in predicting density and viscosity to models based on many more static descriptors. The best models were shown to predict density and dynamic viscosity with coefficient of determination (R2) values of 99.6% and 97.7%, respectively, for all data sets, including a test data set of 45 molecules. Finally, partial dependency plots (PDPs), individual conditional expectation (ICE) plots, local interpretable model-agnostic explanation (LIME) values, and trimmed model R2 values were used to identify the most important static and dynamic predictors of the density and viscosity.

Invariant dynamics in a united-atom model of an ionic liquid

We study a united-atom model of the ionic liquid 1-butyl-1-methylpyrrolidinium bis(trifluoromethyl)sulfonylamide to determine to what extent there exist curves in the phase diagram along which the microscopic dynamics are invariant when expressed in dimensionless, or reduced, form. The initial identification of these curves, termed isodynes, is made by noting that contours of reduced shear viscosity and reduced self-diffusion coefficient coincide to a good approximation. Choosing specifically the contours of reduced viscosity as nominal isodynes, further simulations were carried out for state points on these, and other aspects of dynamics were investigated to study their degree of invariance. These include the mean-squared displacement, shear-stress autocorrelation function, and various rotational correlation functions. These were invariant to a good approximation, with the main exception being rotations of the anion about its long axis. The dynamical features that are invariant have in common that they are aspects that would be relevant for a coarse-grained description of the system; specifically, removing the most microscopic degrees of freedom in principle leads to a simplification of the potential energy landscape, which allows for the existence of isodynes.

Extension of the MolMod Database to Transferable Force Fields

MolMod, a web-based database for classical force fields for molecular simulations of fluids [Mol. Sim. 45, 10 (2019), 806-814], was extended to transferable force fields. Eight transferable force fields, including all-atom and united-atom type force fields, were implemented in the MolMod database: OPLS-UA, OPLS-AA, COMPASS, CHARMM, GROMOS, TraPPE, Potoff, and TAMie. These transferable force fields cover a large variety of chemical substance classes. The system is designed such that new transferable force fields can be readily integrated. A graphical user interface was implemented that enables the construction of molecules. The MolMod database compiles the force field for the specified component and force field type and provides the corresponding data and meta data as well as ready-to-use input files for the molecule for different simulation engines. This helps the user to flexibly choose molecular models and integrate them swiftly in their individual workflows, reducing risks of input errors in molecular simulations.

Calculating shear viscosity with confined non-equilibrium molecular dynamics: a case study on hematite - PAO-2 lubricant

The behaviour of confined lubricants at the atomic scale as affected by the interactions at the surface-lubricant interface is relevant in a range of technological applications in areas such as the automotive industry. In this paper, by performing fully atomistic molecular dynamics, we investigate the regime where the viscosity starts to deviate from the bulk behaviour, a topic of great practical and scientific relevance. The simulations consist of setting up a shear flow by confining the lubricant between iron oxide surfaces. By using confined Non-Equilibrium Molecular Dynamics (NEMD) simulations at a pressure range of 0.1-1.0 GPa at 100 °C, we demonstrate that the film thickness of the fluid affects the behaviour of viscosity. We find that by increasing the number of lubricant molecules, we approach the viscosity value of the bulk fluid derived from previously published NEMD simulations for the same system. These changes in viscosity occurred at film thicknesses ranging from 10.12 to 55.93 Å. The viscosity deviations at different pressures between the system with the greatest number of lubricant molecules and the bulk simulations varied from -16% to 41%. The choice of the utilized force field for treating the atomic interactions was also investigated.

Molecular modeling of interfacial properties of the hydrogen + water + decane mixture in three-phase equilibrium

The understanding of interfacial phenomena between H2 and geofluids is of great importance for underground H2 storage, but requires further study. We report the first investigation on the three-phase fluid mixture containing H2, H2O, and n-C10H22. Molecular dynamics simulation and PC-SAFT density gradient theory are employed to estimate the interfacial properties under various conditions (temperature ranges from 298 to 373 K and pressure is up to around 100 MPa). Our results demonstrate that interfacial tensions (IFTs) of the H2-H2O interface in the H2 + H2O + C10H22 three-phase mixture are smaller than IFTs in the H2 + H2O two-phase mixture. This decrement of IFT can be attributed to C10H22 adsorption in the interface. Importantly, H2 accumulates in the H2O-C10H22 interface in the three-phase systems, which leads to weaker increments of IFT with increasing pressure compared to IFTs in the water + C10H22 two-phase mixture. In addition, the IFTs of the H2-C10H22 interface are hardly influenced by H2O due to the limited amount of H2O dissolved in nonaqueous phases. Nevertheless, positive surface excesses of H2O are seen in the H2-C10H22 interfacial region. Furthermore, the values of the spreading coefficient are mostly negative revealing the presence of the three-phase contact for the H2 + H2O + C10H22 mixture under studied conditions.

Molecular Dynamics: Investigating the Self-Association of Stearic Acid and Heteroassociation of Stearic Acid-Water in Cyclohexane

The self-association of molecular additives determines the chemical potential in the bulk and, in turn, the adsorbed amount onto a surface for a number of important commercial applications such as wind turbines. Molecular dynamics simulations have been utilized as a technique to study the self-association of model additive, stearic acid, and heteroassociation of stearic acid-water, in cyclohexane as a function of temperature. Reasonable values of the enthalpies and equilibrium constants were determined for stearic acid in cyclohexane. The role of water, nearly always present in commercial systems, in solution association was also studied to determine the thermodynamics parameters of hydration (i.e., acid-water heteroassociation). There are very few other studies reporting on these important heteroassociation parameters. The association constants and enthalpies of association obtained from molecular dynamics are in good agreement with experimental data in the literature. A combination of Fourier transform infrared (FTIR) data and molecular dynamics simulation results allows the fraction of open dimers (single hydrogen-bonded dimers) to be estimated in cyclohexane (which is not possible from the experimental FTIR data alone). The fraction of open dimers of stearic acid in cyclohexane at room temperature is ∼1.5% at 25 °C and ∼4% at 70 °C.

Data scheme and data format for transferable force fields for molecular simulation

A generalized data scheme for transferable classical force fields used in molecular simulations, i.e. molecular dynamics and Monte Carlo simulation, is presented. The data scheme is implemented in an SQL-based data format. The data scheme and data format is machine readable, re-usable, and interoperable. A transferable force field is a chemical construction plan specifying intermolecular and intramolecular interactions between different types of atoms or different chemical groups and can be used for building a model for a given component. The data scheme proposed in this work (named TUK-FFDat) formalizes digitally these chemical construction plans, i.e. transferable force fields. It can be applied to all-atom as well as united-atom transferable force fields. The general applicability of the data scheme is demonstrated for different types of force fields (TraPPE, OPLS-AA, and Potoff). Furthermore, conversion tools for translating the data scheme between .xls spread sheet format and the SQL-based data format are provided. The data format can readily be integrated in existing workflows, simulation engines, and force field databases as well as for linking such.

Molecular simulations of sliding on SDS surfactant films

We use molecular dynamics simulations to study the frictional response of monolayers of the anionic surfactant sodium dodecyl sulfate and hemicylindrical aggregates physisorbed on gold. Our simulations of a sliding spherical asperity reveal the following two friction regimes: at low loads, the films show Amonton's friction with a friction force that rises linearly with normal load, and at high loads, the friction force is independent of the load as long as no direct solid-solid contact occurs. The transition between these two regimes happens when a single molecular layer is confined in the gap between the sliding bodies. The friction force at high loads on a monolayer rises monotonically with film density and drops slightly with the transition to hemicylindrical aggregates. This monotonous increase of friction force is compatible with a traditional plowing model of sliding friction. At low loads, the friction coefficient reaches a minimum at the intermediate surface concentrations. We attribute this behavior to a competition between adhesive forces, repulsion of the compressed film, and the onset of plowing.

Molecular modelling of the thermophysical properties of fluids: expectations, limitations, gaps and opportunities

This manuscript provides an overview of the current state of the art in terms of the molecular modelling of the thermophysical properties of fluids. It is intended to manage the expectations and serve as guidance to practising physical chemists, chemical physicists and engineers in terms of the scope and accuracy of the more commonly available intermolecular potentials along with the peculiarities of the software and methods employed in molecular simulations while providing insights on the gaps and opportunities available in this field. The discussion is focused around case studies which showcase both the precision and the limitations of frequently used workflows.

Computing Viscosities of Mixtures of Ester-Based Lubricants at Different Temperatures

Synthetic esters are used as lubricants for applications at high temperatures, but their development can be a trial and error process. In this context, molecular dynamics simulations could be used as a tool to investigate the properties of new lubricants, in particular viscosity. We employ nonequilibrium molecular dynamics (NEMD) simulations to predict bulk Newtonian viscosities of a set of mixtures of two esters, di(2-ethylhexyl) sebacate (DEHS) and di(2-ethylhexyl) adipate (DEHA) at 293 and 343 K as well as equilibrium molecular dynamics (EMD) and NEMD at 393 K and compare these to experimental measurements. The simulations predict mixture densities within 5% of the experimental values, and we are able to retrieve between 99% and 75% of the experimental viscosities for all ranges of temperature. Experimental viscosities show a linear trend which we are able to capture using NEMD at low temperature and EMD at high temperature. Our work shows that, using EMD and NEMD simulations, and the workflows we developed, we can obtain reliable estimates of the viscosities of mixtures of industrially relevant ester-based lubricants at different temperatures.

Comparison of Force Fields for the Prediction of Thermophysical Properties of Long Linear and Branched Alkanes

The prediction of thermophysical properties at extreme conditions is an important application of molecular simulations. The quality of these predictions primarily depends on the quality of the employed force field. In this work, a systematic comparison of classical transferable force fields for the prediction of different thermophysical properties of alkanes at extreme conditions, as they are encountered in tribological applications, was carried out using molecular dynamics simulations. Nine transferable force fields from three different classes were considered (all-atom, united-atom, and coarse-grained force fields). Three linear alkanes (n-decane, n-icosane, and n-triacontane) and two branched alkanes (1-decene trimer and squalane) were studied. Simulations were carried out in a pressure range between 0.1 and 400 MPa at 373.15 K. For each state point, density, viscosity, and self-diffusion coefficient were sampled, and the results were compared to experimental data. The Potoff force field yielded the best results.

Combining Molecular Dynamics and Machine Learning to Analyze Shear Thinning for Alkane and Globular Lubricants in the Low Shear Regime

Lubricants with desirable frictional properties are important in achieving an energy-saving society. Lubricants at the interfaces of mechanical components are confined under high shear rates and pressures and behave quite differently from the bulk material. Computational approaches such as nonequilibrium molecular dynamics (NEMD) simulations have been performed to probe the molecular behavior of lubricants. However, the low-shear-velocity regions of the materials have rarely been simulated owing to the expensive calculations necessary to do so, and the molecular dynamics under shear velocities comparable with that in the experiments are not clearly understood. In this study, we performed NEMD simulations of extremely confined lubricants, i.e., two molecular layers for four types of lubricants confined in mica walls, under shear velocities from 0.001 to 1 m/s. While we confirmed shear thinning, the velocity profiles could not show the flow behavior when the shear velocity was much slower than thermal fluctuations. Therefore, we used an unsupervised machine learning approach to detect molecular movements that contribute to shear thinning. First, we extracted the simple features of molecular movements from large amounts of MD data, which were found to correlate with the effective viscosity. Subsequently, the extracted features were interpreted by examining the trajectories contributing to these features. The magnitude of diffusion corresponded to the viscosity, and the location of slips that varied depending on the spherical and chain lubricants was irrelevant. Finally, we attempted to apply a modified Stokes-Einstein relation at equilibrium to the nonequilibrium and confined systems. While systems with low shear rates obeyed the relation sufficiently, large deviations were observed under large shear rates.

A review of recent advances and applications of machine learning in tribology

In tribology, a considerable number of computational and experimental approaches to understand the interfacial characteristics of material surfaces in motion and tribological behaviors of materials have been considered to date. Despite being useful in providing important insights on the tribological properties of a system, at different length scales, a vast amount of data generated from these state-of-the-art techniques remains underutilized due to lack of analysis methods or limitations of existing analysis techniques. In principle, this data can be used to address intractable tribological problems including structure-property relationships in tribological systems and efficient lubricant design in a cost and time effective manner with the aid of machine learning. Specifically, data-driven machine learning methods have shown potential in unraveling complicated processes through the development of structure-property/functionality relationships based on the collected data. For example, neural networks are incredibly effective in modeling non-linear correlations and identifying primary hidden patterns associated with these phenomena. Here we present several exemplary studies that have demonstrated the proficiency of machine learning in understanding these critical factors. A successful implementation of neural networks, supervised, and stochastic learning approaches in identifying structure-property relationships have shed light on how machine learning may be used in certain tribological applications. Moreover, ranging from the design of lubricants, composites, and experimental processes to studying fretting wear and frictional mechanism, machine learning has been embraced either independently or integrated with optimization algorithms by scientists to study tribology. Accordingly, this review aims at providing a perspective on the recent advances in the applications of machine learning in tribology. The review on referenced simulation approaches and subsequent applications of machine learning in experimental and computational tribology shall motivate researchers to introduce the revolutionary approach of machine learning in efficiently studying tribology.

Comparison of the United- and All-Atom Representations of (Halo)alkanes Based on Two Condensed-Phase Force Fields Optimized against the Same Experimental Data Set

The level of accuracy that can be achieved by a force field is influenced by choices made in the interaction-function representation and in the relevant simulation parameters. These choices, referred to here as functional-form variants (FFVs), include for example the model resolution, the charge-derivation procedure, the van der Waals combination rules, the cutoff distance, and the treatment of the long-range interactions. Ideally, assessing the effect of a given FFV on the intrinsic accuracy of the force-field representation requires that only the specific FFV is changed and that this change is performed at an optimal level of parametrization, a requirement that may prove extremely challenging to achieve in practice. Here, we present a first attempt at such a comparison for one specific FFV, namely the choice of a united-atom (UA) versus an all-atom (AA) resolution in a force field for saturated acyclic (halo)alkanes. Two force-field versions (UA vs AA) are optimized in an automated way using the CombiFF approach against 961 experimental values for the pure-liquid densities ρ_liq and vaporization enthalpies ΔH_vap of 591 compounds. For the AA force field, the torsional and third-neighbor Lennard-Jones parameters are also refined based on quantum-mechanical rotational-energy profiles. The comparison between the UA and AA resolutions is also extended to properties that have not been included as parameterization targets, namely the surface-tension coefficient γ, the isothermal compressibility κ_T, the isobaric thermal-expansion coefficient α_P, the isobaric heat capacity c_P, the static relative dielectric permittivity ϵ, the self-diffusion coefficient D, the shear viscosity η, the hydration free energy ΔG_wat, and the free energy of solvation ΔG_che in cyclohexane. For the target properties ρ_liq and ΔH_vap, the UA and AA resolutions reach very similar levels of accuracy after optimization. For the nine other properties, the AA representation leads to more accurate results in terms of η; comparably accurate results in terms of γ, κ_T, α_P, ϵ, D, and ΔG_che; and less accurate results in terms of c_P and ΔG_wat. This work also represents a first step toward the calibration of a GROMOS-compatible force field at the AA resolution.

Molecular Dynamics Simulation of the Crystallization Behavior of Octadecane on a Homogeneous Nucleus

Latent heat storages have the ability to contribute to a more sustainable energy supply network. However, phase change materials (PCM) used for latent heat storages often show supercooling. This phenomenon takes place whenever the PCM begins crystallizing below the freezing point and is one of the biggest drawbacks holding back the widespread use of PCM. Nucleation agents (NA) can be used to avoid the supercooling, yet the choice of an effective NA is not straightforward. In this work, molecular dynamics (MD) simulation was tested in order to simulate the crystallization of Octadecane on a NA. The simulation results include density, phase change temperature and enthalpy as well as the crystal structure and lie in good agreement with literature values and the authors’ own experimental data. Further simulations of the crystallization process on different surfaces of homogeneous nuclei acting as a NA were performed. The results reflect the hypothesis that liquid molecules start crystallizing easier on surfaces exposing the whole chain side rather than the chain ends. With the result, that the choice of parameters for the MD simulation represent the Octadecane system reliably and further studies can be performed including heterogeneous NA.

Molecular Modeling is an Enabling Approach to Complement and Enhance Channelopathy Research

Hundreds of human membrane proteins form channels that transport necessary ions and compounds, including drugs and metabolites, yet details of their normal function or how function is altered by genetic variants to cause diseases are often unknown. Without this knowledge, researchers are less equipped to develop approaches to diagnose and treat channelopathies. High-resolution computational approaches such as molecular modeling enable researchers to investigate channelopathy protein function, facilitate detailed hypothesis generation, and produce data that is difficult to gather experimentally. Molecular modeling can be tailored to each physiologic context that a protein may act within, some of which may currently be difficult or impossible to assay experimentally. Because many genomic variants are observed in channelopathy proteins from high-throughput sequencing studies, methods with mechanistic value are needed to interpret their effects. The eminent field of structural bioinformatics integrates techniques from multiple disciplines including molecular modeling, computational chemistry, biophysics, and biochemistry, to develop mechanistic hypotheses and enhance the information available for understanding function. Molecular modeling and simulation access 3D and time-dependent information, not currently predictable from sequence. Thus, molecular modeling is valuable for increasing the resolution with which the natural function of protein channels can be investigated, and for interpreting how genomic variants alter them to produce physiologic changes that manifest as channelopathies. © 2022 American Physiological Society. Compr Physiol 12:3141-3166, 2022.

Molecular Simulations of Surfactant Adsorption on Iron Oxide from Hydrocarbon Solvents

The performance of organic friction modifiers (OFMs) depends on their ability to adsorb onto surfaces and form protective monolayers. Understanding the relationship between OFM concentration in the base oil and the resulting surface coverage is important for improving lubricant formulations. Here, we use molecular dynamics (MD) simulations to study the adsorption of three OFMs─stearic acid (SA), glycerol monoostearate (GMS), and glycerol monooleate (GMO)─onto a hematite surface from two hydrocarbon solvents─n-hexadecane and poly(α-olefin) (PAO). We calculate the potential of mean force of the adsorption process using the adaptive biasing force algorithm, and the adsorption strength increases in the order SA < GMS < GMO. We estimate the minimum area occupied by OFM molecules on the surface using annealing MD simulations and obtained a similar hard-disk area for GMS and GMO but a lower value for SA. Using the MD results, we determine the adsorption isotherms using the molecular thermodynamic theory (MTT), which agree well with one previous experimental data set for SA on hematite. For two other experimental data sets for SA, lateral interactions between surfactant molecules need to be accounted for within the MTT framework. SA forms monolayers with lower surface coverage than GMO and GMS at low concentrations but also has the highest plateau coverage. We validate the adsorption energies from the MD simulations using high-frequency reciprocating rig friction experiments with different concentrations of the OFMs in PAO. For OFMs with saturated tailgroups (SA and GMS), we obtain good agreement between the simulations and the experiments. The results deviate for OFMs containing Z-unsaturated tailgroups (GMO) due to the additional steric hindrance, which is not accounted for in the current simulation framework. This study demonstrates that MD simulations, alongside MTT, are an accurate and efficient tool to predict adsorption isotherms at solid-liquid interfaces.

Scale-Dependent Friction-Coverage Relations and Nonlocal Dissipation in Surfactant Monolayers

Surfactant molecules, known as organic friction modifiers (OFMs), are routinely added to lubricants to reduce friction and wear between sliding surfaces. In macroscale experiments, friction generally decreases as the coverage of OFM molecules on the sliding surfaces increases; however, recent nanoscale experiments with sharp atomic force microscopy (AFM) tips have shown increasing friction. To elucidate the origin of these opposite trends, we use nonequilibrium molecular dynamics (NEMD) simulations and study kinetic friction between OFM monolayers and an indenting nanoscale asperity. For this purpose, we investigate various coverages of stearamide OFMs on iron oxide surfaces and silica AFM tips with different radii of curvature. We show that the differences between the friction-coverage relations from macroscale and nanoscale experiments are due to molecular plowing in the latter. For our small tip radii, the friction coefficient and indentation depth both have a nonmonotonic dependence on OFM surface coverage, with maxima occurring at intermediate coverage. We rationalize the nonmonotonic relations through a competition of two effects (confinement and packing density) that varying the surface coverage has on the effective stiffness of the OFM monolayers. We also show that kinetic friction is not very sensitive to the sliding velocity in the range studied, indicating that it originates from instabilities. Indeed, we find that friction predominately originates from plowing of the monolayers by the leading edge of the tip, where gauche defects are created, while thermal dissipation is mostly localized in molecules toward the trailing edge of the tip, where the chains return to a more extended conformation.

Benchmark assessment of molecular geometries and energies from small molecule force fields

Background: Force fields are used in a wide variety of contexts for classical molecular simulation, including studies on protein-ligand binding, membrane permeation, and thermophysical property prediction. The quality of these studies relies on the quality of the force fields used to represent the systems. Methods: Focusing on small molecules of fewer than 50 heavy atoms, our aim in this work is to compare nine force fields: GAFF, GAFF2, MMFF94, MMFF94S, OPLS3e, SMIRNOFF99Frosst, and the Open Force Field Parsley, versions 1.0, 1.1, and 1.2. On a dataset comprising 22,675 molecular structures of 3,271 molecules, we analyzed force field-optimized geometries and conformer energies compared to reference quantum mechanical (QM) data. Results: We show that while OPLS3e performs best, the latest Open Force Field Parsley release is approaching a comparable level of accuracy in reproducing QM geometries and energetics for this set of molecules. Meanwhile, the performance of established force fields such as MMFF94S and GAFF2 is generally somewhat worse. We also find that the series of recent Open Force Field versions provide significant increases in accuracy. Conclusions: This study provides an extensive test of the performance of different molecular mechanics force fields on a diverse molecule set, and highlights two (OPLS3e and OpenFF 1.2) that perform better than the others tested on the present comparison. Our molecule set and results are available for other researchers to use in testing.

Critical Shear Rate of Polymer-Enhanced Hydraulic Fluids

Many application-relevant fluids exhibit shear thinning, where viscosity decreases with shear rate above some critical shear rate. For hydraulic fluids formulated with polymeric additives, the critical shear rate is a function of the molecular weight and concentration of the polymers. Here we present a model for predicting the critical shear rate and Newtonian viscosity of fluids, with the goal of identifying a fluid that shear thins in a specific range relevant to hydraulic pumps. The model is applied to predict the properties of fluids comprising polyisobutene polymer and polyalphaolefin base oil. The theoretical predictions are validated by comparison to viscosities obtained from experimental measurements and molecular dynamics simulations across many decades of shear rates. Results demonstrate that the molecular weight of the polymer plays a key role in determining the critical shear rate, whereas the concentration of polymer primarily affects the Newtonian viscosity. The simulations are further used to show the molecular origins of shear thinning and critical shear rate. The atomistic simulations and simple model developed in this work can ultimately be used to formulate polymer-enhanced fluids with ideal shear thinning profiles that maximize the efficiency of hydraulic systems.

Wax Formation in Linear and Branched Alkanes with Dissipative Particle Dynamics

We present a dissipative particle dynamics (DPD) model for wax formation (i.e., the freezing transition) in linear and branched alkanes at room temperature (298 K) and atmospheric pressure. We parametrize the model using pure liquid phase densities and the onset of wax formation as a function of alkyl chain length. Significant emphasis is placed on building an accurate representation of the underlying molecular architecture by careful consideration of bond lengths and angles, aided by distributions obtained from molecular dynamics simulation. Using the derived model, we observe wax formation in n-alkanes when the alkyl chain length is greater than 18 (n-octadecane), in excellent agreement with experimental observations. Further, we reproduce the behavior of branched alkanes and mixtures including solubilities of heavy alkanes in light alkane solvents.

Probing the high-pressure viscosity of hydrocarbon mixtures using molecular dynamics simulations

Computational predictions of the high-pressure viscosity of hydrocarbon mixtures could help to accelerate the development of fuels and lubricants with improved performance. In this study, we use molecular dynamics simulations to study the viscosity and density of methylcyclohexane, 1-methylnaphthalene, and their binary mixtures at 323 K and pressures of up to 500 MPa. The simulation results are in excellent agreement with previous experiments available up to 100 MPa for both pure compounds (200 MPa for 1-methylnaphthalene) and the binary mixtures. For 1-methylnaphthalene, the viscosity initially increases slower-than-exponential with pressure before it reaches an inflection point and then increases faster-than-exponential. The inflection point (300 MPa) occurs at a pressure slightly below the one at which 1-methylnaphthalene is expected to enter the supercooled phase (400 MPa). For methylcyclohexane, the increase in viscosity with pressure is slower-than-exponential over the entire pressure range studied. The binary mixtures show intermediate pressure-viscosity responses between the two pure cases. The applicability of equations commonly used to describe the pressure dependence of viscosity, as well as the viscosity of binary mixtures, is evaluated against the computational predictions.

Are all-atom any better than united-atom force fields for the description of liquid properties of alkanes?

Alkanes are a fundamental part in empirical force fields (FF) not only due to their technological relevance, but also due to the prevalence of alkane moieties in organic molecules, e.g., compounds containing a saturated carbon chain. Therefore, a good description of alkane interactions is crucial for determining the quality of a FF. In this study, the performance of 12 empirical force fields (FF) was evaluated in the context of reproducing liquid properties of alkanes. More specifically, n-octane was chosen as a reference compound since it is a liquid in a broad temperature range and it has numerous experimental data for thermodynamic, transport, and structural properties, as well as for their temperature dependencies. A normalized root-mean-square deviation (NRMSD) analysis was used to rank the force fields in their ability to reproduce the experimental data. Five out of the six best force fields considered were united-atom models. The GROMOS force field showed the smallest deviation in terms of NRMSD, followed by TRAPPE-EH, NERD, CHARMM-UA, TRAPPE-UA, and OPLS-UA. This overall better performance of the united-atom force fields indicates that complexity does not always bring quality.

Molecular Dynamics Simulation on Thin-Film Lubrication of a Mixture of Three Alkanes

We used the COMPASS forcefield to perform molecular dynamics (MD) simulation of a mixture composed of three alkanes as the lubricant for the thin-film lubrication. The viscosity of the lubrication film in the non-working state, the final film thickness, and density distribution were investigated. The results reveal that the viscosity error among different initial film thicknesses in the non-working state is within 5%, which confirms the applicability of the model and the forcefield. The viscosity decreases oscillating as temperature increases. Whatever the initial film thickness is, the film thickness change rate with respect to pressure load is almost the same. When pressure increases, the density peaks increase. As the initial film thickness increases, the normalized thicknesses of adsorption and ordered layers decrease. In nanoscale, the density predicted by the MD simulation is higher than the prediction of the Tait equation, even if the adsorption layers is excluded.

Understanding Adsorption Behaviors of Organic Friction Modifiers on Hydroxylated SiO2 (001) Surfaces: Effects of Molecular Polarity and Temperature

Molecular dynamics simulations are used to investigate the physisorption of organic friction modifiers (OFMs) lubricated by 1-decene trimer (PAO4) representing a base oil and confined between hydroxylated SiO₂ (001) surfaces. The results indicate that OFM molecules form dense, tendentiously vertical monolayer films at low temperature but loose adsorption layers at high temperature, particularly for R-NH₂ with weaker molecular polarity. The structural information is quantitatively clarified by mass density profiles, radial distribution function, and probability distributions of an end-to-end distance at a perpendicular-to-surface direction. The movement performance of lubricant, reflected by the thickness of the organic part and radius of gyration of PAO4 molecules, strongly depends on temperature. The adsorption amount of OFM molecules decreases dramatically with lowering OFM polarity and increasing temperature above the critical desorption temperatures of about 320, 373, and 453 K for amine (R-NH₂), alcohol (R-OH), and acid (R-COOH), respectively. The interaction energies of the OFM-surface decrease continuously for the R-NH₂ system with temperature and decrease rapidly as temperature exceeds a critical value for both R-OH and R-COOH systems. The single-molecule geometry optimization validates the significant role of the electrostatic and hydrogen-bond attractions in molecular adsorption. Therefore, the OFMs with stronger polarity (like R-COOH) present stronger adsorption and better temperature resistance. The findings in this work are of particular value and provide a guideline in designing and engineering novel OFM additives for extreme lubrication conditions.

Transport coefficients of model lubricants up to 400 MPa from molecular dynamics

In this paper, the predictive power of molecular dynamics methods is demonstrated for the cases of model paraffinic and aromatic lubricant liquids at pressures up to 400 MPa. The shear viscosity and self-diffusion coefficients are calculated for 2,2,4-trimethylpentane (C₈H₁₈) at 298 K and 1,1-diphenylethane (C₁₄H₁₄) at 333 K. Three force fields with different levels of accuracy are compared by the ability to predict the experimental data. The Stokes-Einstein correlation between viscosity and self-diffusion is demonstrated for both compounds.

Density and viscosity of a polyol ester lubricant: Measurement and molecular dynamics simulation

Polyol ester (POE) is the main component of many refrigeration lubricants. In this work, the density and the viscosity of a typical, pure polyol ester, pentaerythritol tetrahexanoate (PEC6), were measured over 258.15 K to 373.15 K and predicted with molecular dynamics simulations. Nonequilibrium molecular dynamics (NEMD) was employed to compute the shear viscosities for different shear rates. The Eyring model was used to fit the shear viscosities and to extrapolate to the Newtonian viscosity. A protocol was proposed to perform a NEMD-Eyring fit for a low-error, reproducible and robust Newtonian viscosity calculation. Three force fields, i.e., OPLS, LOPLS, and DREIDING, were tested in terms of their density and viscosity prediction accuracy. OPLS gave the best density prediction (within ± 0.2 %), while LOPLS showed the best viscosity prediction accuracy (within - 4 % to 20 %). This work illustrates the value of molecular simulation in predicting lubricant properties and its potential in guiding the design of POE lubricants for desired properties.

Contributions of force field interaction forms to Green-Kubo viscosity integral in n-alkane case

Decades of molecular simulation history proved that the Green-Kubo method for shear viscosity converges without any problems in atomic and simple molecular liquids, unlike liquids with high values of viscosity. In the case of highly viscous liquids, the time decomposition method was developed in 2015 by Maginn and co-authors [Y. Zhang, A. Otani, and E. J. Maginn, J. Chem. Theory Comput. 11, 3537-3546 (2015)] which allows us to improve the convergence of the Green-Kubo integral. In this paper, the contributions of intramolecular and intermolecular force field parts to the viscosity integral are discovered to gain the understanding of the Green-Kubo method. The n-alkanes from n-ethane to n-pentane at 330 K in the optimized potentials for liquid simulations-all atom force field are used as reference models. The dependencies of these contributions and decay times of the corresponding correlation functions on the chain length are observed. The nonequilibrium simulations are carried out to verify the Green-Kubo results. The obtained values of viscosity are compared with experimental data.

Interactions between Friction Modifiers and Dispersants in Lubricants: The Case of Glycerol Monooleate and Polyisobutylsuccinimide-Polyamine

The structural and frictional properties of 10 wt % solutions of the amphiphilic molecules glycerol monooleate (GMO) and polyisobutylsuccinimide-polyamine (PIBSA-PAM) in squalane are studied using molecular dynamics simulations in bulk and under confinement between iron oxide surfaces. GMO is a friction modifier, PIBSA-PAM is a dispersant, and squalane is a good model for typical base oils. A range of liquid compositions and applied pressures is explored, and the formation and stability of reverse micelles are determined under quiescent and shear conditions. Micellization is observed mainly in systems with a high GMO content, but PIBSA-PAM may also form small aggregates on its own. In the confined systems under both static and shear conditions, some surfactant molecules adsorb onto the surfaces, with the rest of the molecules forming micelles or aggregates. Shearing the liquid layer under high pressure causes almost all of the micelles and aggregates to break, except in systems with around 7.5 wt % GMO and 2.5 wt % PIBSA-PAM. The presence of micelles and adsorbed surfactants is found to be correlated with a low kinetic friction coefficient, and hence, there is an optimum composition range for friction reduction. This work highlights the importance of cooperative interactions between lubricant additives.

Molecular Dynamics Simulation of Pure n-Alkanes and Their Mixtures at Elevated Temperatures Using Atomistic and Coarse-Grained Force Fields

The properties of higher n-alkanes and their mixtures is a topic of significant interest for the oil and chemical industry. However, the experimental data at high temperatures are scarce. The present study focuses on simulating n-dodecane, n-octacosane, their binary mixture at a n-dodecane mole fraction of 0.3, and a model mixture of the commercially available hydrocarbon wax SX-70 to evaluate the performance of several force fields on the reproduction of properties such as liquid densities, surface tension, and viscosities. Molecular dynamics simulations over a broad temperature range from 323.15 to 573.15 K were employed in examining a broad set of atomistic molecular models assessed for the reproduction of experimental data. The well-established united atom TraPPE (TraPPE-UA) was compared against the all atom optimized potentials for liquid simulations (OPLS) reparametrization for long n-alkanes, L-OPLS, as well as Lipid14 and MARTINI force fields. All models qualitatively reproduce the temperature dependence of the aforementioned properties, but TraPPE-UA was found to reproduce liquid densities most accurately and consistently over the entire temperature range. TraPPE-UA and MARTINI were very successful in reproducing surface tensions, and L-OPLS was found to be the most accurate in reproducing the measured viscosities as compared to the other models. Our simulations show that these widely used force fields originating from the world of biomolecular simulations are suitable candidates in the study of n-alkane properties, both in the pure and mixture states.

Shear heating, flow, and friction of confined molecular fluids at high pressure

Understanding the molecular-scale behavior of fluids confined and sheared between solid surfaces is important for many applications, particularly tribology where this often governs the macroscopic frictional response. In this study, nonequilibrium molecular dynamics simulations are performed to investigate the effects of fluid and surface properties on the spatially resolved temperature and flow profiles, as well as friction. The severe pressure and shear rate conditions studied are representative of the elastohydrodynamic lubrication regime. In agreement with tribology experiments, flexible lubricant molecules give low friction, which increases linearly with logarithmic shear rate, while bulky traction fluids show higher friction, but a weaker shear rate dependence. Compared to lubricants, traction fluids show more significant shear heating and stronger shear localization. Models developed for macroscopic systems can be used to describe both the spatially resolved temperature profile shape and the mean film temperature rise. The thermal conductivity of the fluids increases with pressure and is significantly higher for lubricants compared to traction fluids, in agreement with experimental results. In a subset of simulations, the efficiency of the thermostat in one of the surfaces is reduced to represent surfaces with lower thermal conductivity. For these unsymmetrical systems, the flow and the temperature profiles become strongly asymmetric and some thermal slip can occur at the solid-fluid interface, despite the absence of velocity slip. The larger temperature rises and steeper velocity gradients in these cases lead to large reductions in friction, particularly at high pressure and shear rate.

Adsorption of Stearic Acid at the Iron Oxide/Oil Interface: Theory, Experiments, and Modeling

Improved friction performance is an important objective of equipment manufacturers for meeting improved energy efficiency demands. The addition of friction-reducing additives, or friction modifiers (FMs), to lubricants is a key part of the strategy. The performance of these additives is related to their surface activity and their ability to form adsorbed layers on the metal surface. However, the extent of surface coverage (mass per unit area) required for effective friction reduction is currently unknown. In this article, we show that full coverage is not necessary for significant friction reduction. We first highlight various features of surface adsorption that can influence the surface coverage, packing, and free energy of adsorption of organic FMs on iron oxide surfaces. Using stearic acid in heptane and hexadecane as model lubricant formulations, we employ a combination of experiments and molecular dynamics (MD) simulations to show how the dimerization of acid molecules in the bulk solvent and the crystallographic orientation of the surface modifies surface adsorption. In addition, we show that the solvent can strongly influence the adsorption kinetics, and MD simulations reveal that hexadecane tends to align on the surface, increasing the energy barrier for the adsorption of stearic acid to the surface. Furthermore, we present a combined approach using MD and molecular thermodynamic theory to calculate adsorption isotherms for stearic acid on iron oxide surfaces, which agrees well with experimental data obtained with a quartz crystal microbalance (QCM). Our results suggest that while the friction of systems lubricated with organic FMs decreases with increasing coverage, complete coverage of the surface is neither practically achievable nor necessary for effective friction reduction for the systems and conditions studied here.

Composition effect on thermophobicity of ternary mixtures: An enhanced molecular dynamics method

Thermodiffusion or the Ludwig-Soret effect is known as the cross effect between the temperature gradient and induced separation of mixture species in multicomponent mixtures. The performance of the boundary driven non-equilibrium molecular dynamics enhanced heat exchange (eHEX) algorithm was validated by evaluating the sign and magnitude of the thermodiffusion process in methane/n-butane/n-dodecane (nC₁-nC₄-nC₁₂) ternary mixtures. The eHEX algorithm consists of an extended version of the HEX algorithm with an improved energy conservation property. In addition to this, the transferable potentials for phase equilibria-united atom augmented force field was employed in all molecular dynamics (MD) simulations to accurately represent molecular interactions in the fluid. Our newly employed MD algorithm was capable to appropriately reflect the thermophobicity concept and the coupled effect of relative density and mole fraction of the mixture species on the thermodiffusion process. The separation ratio of the ternary mixture for five different compositions (at 333.15 K and 35 MPa) showed good agreement with experimental data and better accuracy in predicting the sign change of the intermediate component (nC₄) as its concentration in the mixture increases, when compared to other MD models.

Impact of Molecular Structure on Properties of n-Hexadecane and Alkylbenzene Binary Mixtures

Because of the complexity of petroleum-based fuels, researchers typically use simplified mixtures, known as surrogates, to study combustion behavior and to attempt to identify how physical properties are related to combustion. The process of determining the surrogate composition to yield a desired set of thermophysical properties can be a complicated and time-consuming task. As a result, the use of computer simulations to narrow the number of possible surrogate compositions is beginning to be explored. Herein, molecular dynamics (MD) simulations are used to model binary mixtures of n-hexadecane with either benzene, toluene, n-ethylbenzene, n-propylbenzene, or n-butylbenzene. Calculated densities are in quantitative agreement with experimental values. With the exception of the mixtures containing benzene, simulated excess molar volumes are also in very good agreement with measured values. Isentropic bulk moduli are in qualitative agreement with experiment, and reproduce interesting trends observed in the experimental data. Specifically, minima in the bulk moduli at intermediate compositions of several of the alkylbenzenes are correctly reproduced. In addition, the structures of the fluids are also examined. For mixtures of n-hexadecane with alkylbenzenes with longer chains, the orientation of the aromatic rings is not substantially impacted by composition. In contrast, increasing n-hexadecane content increases the ratio of parallel to perpendicular arrangements of benzene and toluene molecules. In those mixtures, this change in orientation of the aromatic rings could be responsible for the minima observed in the bulk moduli data. These results show that MD simulations can assist in development of fuel surrogates, both by predicting thermophysical properties and by providing insight into how molecular structure and composition affect those properties.

Self-assembly and friction of glycerol monooleate and its hydrolysis products in bulk and confined non-aqueous solvents

Molecular dynamics simulations are used to study the interplay between self-assembly, adsorption, and friction in solutions of amphiphilic additives dissolved in non-aqueous solvents.

On the effect of confined fluid molecular structure on nonequilibrium phase behaviour and friction

Atomistic simulations and tribology experiments uncover the effect of molecular structure on the flow and friction behaviour of confined films under extreme conditions.