Recent advances in molecular simulation: A chemical engineering perspective

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.

Deriving force fields with a multiscale approach:from ab initio calculations to molecular-based equations of state

Using theoretical and computational tools for predicting thermophysical properties of fluid systems and the soft matter has always been of interest to the physical, chemical, and engineering sciences. And certainly, the ultimate goal is to be able to compute these macroscopic properties from first principle calculations beginning with the very atomic constitution of matter. In this work, Mie potential parameters were obtained through dimer interaction energy curves derived from ab initio calculations to represent methane and methane-substituted molecules in a spherical 1-site coarse-grained model. Bottom-up-based Mie potential parameters of this work were compared to top-down-based ones from the statistical associating fluid theory (SAFT) models for the calculation of thermodynamic properties and critical point by molecular dynamics simulations and SAFT-VR Mie equation of state. Results demonstrated that bottom-up-based Mie potential parameters when averaging the Mie potential parameters of a representative population of conformers provide values close to the top-down-based ones from SAFT models and predict well properties of tetrahedral molecules. This shows the level of consistency embedded in the SAFT-VR Mie family of models and confers a status of a purely predictive equation of state for SAFT-VR Mie when a reasonable model is considered to represent a molecule of interest.

Adsorptive removal of gas phase naphthalene on ordered mesoporous carbon

Adsorptive removal of gas phase low concentration macromolecular organic component, represented by naphthalene, from the enclosed space using ordered mesoporous carbon (OMC) has been studied by molecular simulation and experimental investigation. The simulation results indicated that both adsorption capacity and adsorption stability of the OMCs for naphthalene decreased with the increase of pore sizes from 2 nm to 8 nm. Characterizations showed that the prepared OMCs had the pore structure similar to the simulated OMCs except for the rough surface. In particular, the adsorption performance of the prepared OMCs was significantly lower than that of the simulated OMCs when pore size was 2 nm and 3 nm, which was attributed to the rough inner surface of these adsorbents, blocking the narrow pore channels and significantly reducing the pore volume. OMC with pore size of 4 nm had the highest adsorption amount for naphthalene. The co-adsorption experiments in the presence of both naphthalene and toluene, acetone or water showed the adsorption performance of OMCs for naphthalene were almost unaffected by the presence of low concentration toluene and acetone, as well as high relative humidity.

The interplay between surface-functionalized gold nanoparticles and negatively charged lipid vesicles

The comprehensive understanding of the interactions between gold nanoparticles (AuNPs) and phospholipid vesicles has important implications in various biomedical applications; however, this is not yet well understood. Here, coarse-grained molecular dynamics (CGMD) simulations were performed to study the interactions between functionalized AuNPs and negatively charged lipid vesicles, and the effects of the surface chemistry and surface charge density (SCD) of AuNPs were analyzed. It is revealed that AuNPs with different surface ligands adhere to the membrane surface (anionic AuNPs) or get into the vesicle bilayer (hydrophobic and cationic AuNPs). Due to the loose arrangement of lipid molecules, AuNPs penetrate curved vesicle membranes more easily than planar lipid bilayers. Cationic AuNPs present three different interaction modes with the vesicle, namely insertion, partial penetration and complete penetration, which are decided by the SCD difference. Both hydrophobic interaction and electrostatic interaction play crucial roles in the interplay between cationic AuNPs and lipid vesicles. For the cationic AuNP with a low SCD, it gets into the lipid bilayer without membrane damage through the hydrophobic interaction, and it is finally stabilized in the hydrophobic interior of the vesicle membrane in a thermodynamically stable "snorkeling" configuration. For the cationic AuNP with a high SCD, it crosses the vesicle membrane and gets into the vesicle core through a membrane pore induced by strong electrostatic interaction. In this process, the membrane structure is destroyed. These findings provide a molecular-level understanding of the interplay between AuNPs and lipid vesicles, which may further expand the application of functional AuNPs in modern biomedicine.

Algorithm to minimize MPI communications in the parallelized fast multipole method combined with molecular dynamics calculations

In the era of exascale supercomputers, large-scale, and long-time molecular dynamics (MD) calculations are expected to make breakthroughs in various fields of science and technology. Here, we propose a new algorithm to improve the parallelization performance of message passing interface (MPI)-communication in the MPI-parallelized fast multipole method (FMM) combined with MD calculations under three-dimensional periodic boundary conditions. Our approach enables a drastic reduction in the amount of communication data, including the atomic coordinates and multipole coefficients, both of which are required to calculate the electrostatic interaction by using the FMM. In communications of multipole coefficients, the reduction rate of communication data in the new algorithm relative to the amount of data in the conventional one increases as both the number of FMM levels and the number of MPI processes increase. The aforementioned rate increase could exceed 50% as the number of MPI processes becomes larger for very large systems. The proposed algorithm, named the minimum-transferred data (MTD) method, should enable large-scale and long-time MD calculations to be calculated efficiently, under the condition of massive MPI-parallelization on exascale supercomputers.

Acidic Polysaccharides as Green Alternatives for Barite Scale Dissolution

Barium sulfate (barite) scale poses significant challenges for processes ranging from water treatment to fossil fuel production. Here, we identify alginate (a polysaccharide derived from brown algae) as a potent, "green" alternative to commercial barite demineralizing agents. Unlike conventional treatments of inorganic scales that require caustic conditions, alginate polymers dissolve barite at near-neutral conditions. In this study, we benchmark the demineralizing efficacy of alginate against a commercial dissolver, diethylenetriaminepentaacetic acid (DTPA), using a combination of bulk dissolution assays, scanning probe microscopy, and molecular dynamics simulations. Time-resolved rates of dissolution measured in a microfluidic device show that demineralization is enhanced more than an order of magnitude under flow. In situ atomic force microscopy reveals that alginate and DTPA exhibit distinct mechanisms of surface dissolution; and surprisingly, their binary combination in alkaline media results in a synergistic cooperativity that enhances the overall rate of barite dissolution. These studies collectively demonstrate a unique approach to demineralization using an inexpensive and abundant biopolymer that enables environmentally friendly treatment of inorganic scales.

Molecular modelling techniques for predicting liquid-liquid interfacial properties of methanol plus alkane (n-hexane, n-heptane, n-octane) mixtures

In this work, the liquid-liquid interfacial properties of methanol plus n-alkane (n-hexane, n-heptane, n-octane) mixtures are investigated at atmospheric pressure by two complementary molecular modelling techniques; namely, molecular dynamic simulations (MD) and density gradient theory (DGT) coupled with the PC-SAFT (perturbed-chain statistical associating fluid theory) equation of state. Furthermore, two molecular models of methanol are used, which are based on a non-polarisable three site approach. On the one hand, is the original (flexible) TraPPE-UA model force field. On the other hand, is the rigid approximation denoted as OPLS/2016. In both cases, n-alkanes are modelled using the TraPPE-UA model. Simulations are performed using the direct coexistence technique in the ensemble. Special attention is paid to the comparison between the estimations obtained from different methanol models, the available experimental data and theoretical calculations. In all cases, the rigid model is capable of predicting the experimental phase equilibrium and interfacial properties accurately. Unsurprisingly, the methanol-rich density and interfacial tension are overestimated using the TraPPE model combined with Lorentz-Berthelot mixing rules for predicting the mixture behaviour. Accurate comparison between MD and DGT plus PC-SAFT requires consideration of the cross-interactions between individual influence parameters and fitting the βij values. This latter aspect is particularly important because it allows the exploitation of the link between the EOS model and the direct molecular simulation of the corresponding fluid. At the same time, it was demonstrated that the key property defining the interfacial tension value is the absolute concentration of methanol in the methanol-rich phase. This behaviour indicates that there are more hydrogens bonded with each other, and they interact favourably with an increasing number of carbon atoms in the alkane.

Extrapolation and interpolation strategies for efficiently estimating structural observables as a function of temperature and density

Thermodynamic extrapolation has previously been used to predict arbitrary structural observables in molecular simulations at temperatures (or relative chemical potentials in open-system mixtures) different from those at which the simulation was performed. This greatly reduces the computational cost in mapping out phase and structural transitions. In this work, we explore the limitations and accuracy of thermodynamic extrapolation applied to water, where qualitative shifts from anomalous to simple-fluid-like behavior are manifested through shifts in the liquid structure that occur as a function of both temperature and density. We present formulas for extrapolating in volume for canonical ensembles and demonstrate that linear extrapolations of water's structural properties are only accurate over a limited density range. On the other hand, linear extrapolation in temperature can be accurate across the entire liquid state. We contrast these extrapolations with classical perturbation theory techniques, which are more conservative and slowly converging. Indeed, we show that such behavior is expected by demonstrating exact relationships between extrapolation of free energies and well-known techniques to predict free energy differences. An ideal gas in an external field is also studied to more clearly explain these results for a toy system with fully analytical solutions. We also present a recursive interpolation strategy for predicting arbitrary structural properties of molecular fluids over a predefined range of state conditions, demonstrating its success in mapping qualitative shifts in water structure with density.

Surrogate Models for Studying the Wettability of Nanoscale Natural Rough Surfaces Using Molecular Dynamics

A molecular modeling methodology is presented to analyze the wetting behavior of natural surfaces exhibiting roughness at the nanoscale. Using atomic force microscopy, the surface topology of a Ketton carbonate is measured with a nanometer resolution, and a mapped model is constructed with the aid of coarse-grained beads. A surrogate model is presented in which surfaces are represented by two-dimensional sinusoidal functions defined by both an amplitude and a wavelength. The wetting of the reconstructed surface by a fluid, obtained through equilibrium molecular dynamics simulations, is compared to that observed by the different realizations of the surrogate model. A least-squares fitting method is implemented to identify the apparent static contact angle, and the droplet curvature, relative to the effective plane of the solid surface. The apparent contact angle and curvature of the droplet are then used as wetting metrics. The nanoscale contact angle is seen to vary significantly with the surface roughness. In the particular case studied, a variation of over 65° is observed between the contact angle on a flat surface and on a highly spiked (Cassie–Baxter) limit. This work proposes a strategy for systematically studying the influence of nanoscale topography and, eventually, chemical heterogeneity on the wettability of surfaces.

Hybrid Monte Carlo with LAMMPS

We describe a strategy for performing canonical and isothermal-isobaric ensemble hybrid Monte Carlo (HMC) simulations with the widely-used Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) molecular dynamics (MD) software package. The overall workflow for the HMC simulations is handled using an external Python driver script, which invokes LAMMPS’ library interface to perform numerically intensive tasks such as MD integration. We document several rigorous consistency checks that have been used to validate our HMC implementation. We also demonstrate that our approach can be readily extended to implement biased HMC sampling schemes for computing free energies. Codes and input files from the documented examples are available on the web.

Coarse-grained models using local-density potentials optimized with the relative entropy: Application to implicit solvation

Bottom-up multiscale techniques are frequently used to develop coarse-grained (CG) models for simulations at extended length and time scales but are often limited by a compromise between computational efficiency and accuracy. The conventional approach to CG nonbonded interactions uses pair potentials which, while computationally efficient, can neglect the inherently multibody contributions of the local environment of a site to its energy, due to degrees of freedom that were coarse-grained out. This effect often causes the CG potential to depend strongly on the overall system density, composition, or other properties, which limits its transferability to states other than the one at which it was parameterized. Here, we propose to incorporate multibody effects into CG potentials through additional nonbonded terms, beyond pair interactions, that depend in a mean-field manner on local densities of different atomic species. This approach is analogous to embedded atom and bond-order models that seek to capture multibody electronic effects in metallic systems. We show that the relative entropy coarse-graining framework offers a systematic route to parameterizing such local density potentials. We then characterize this approach in the development of implicit solvation strategies for interactions between model hydrophobes in an aqueous environment.

Molecular-level insight of hindered phenol AO-70/nitrile-butadiene rubber damping composites through a combination of a molecular dynamics simulation and experimental method

The damping properties of AO-70/NBR composites get a noteworthy increase with the introduction of AO-70—max tan δincreased by 66.9%.

Interfacial tension of oil/water emulsions with mixed non-ionic surfactants: comparison between experiments and molecular simulations

Smaller Span molecules occupy the free spaces between bulkier Tween molecules thus lowering interfacial tension as compared to those obtained for single surfactant systems.

Molecular simulation of homogeneous nucleation of crystals of an ionic liquid from the melt

The homogeneous nucleation of crystals of the ionic liquid [dmim(+)][Cl(-)] from its supercooled liquid phase in the bulk (P = 1 bar, T = 340 K, representing a supercooling of 58 K) was studied using molecular simulations. The string method in collective variables [Maragliano et al., J. Chem. Phys. 125, 024106 (2006)] was used in combination with Markovian milestoning with Voronoi tessellations [Maragliano et al., J. Chem. Theory Comput. 5, 2589-2594 (2009)] and order parameters for molecular crystals [E. E. Santiso and B. L. Trout, J. Chem. Phys. 134, 064109 (2011)] to sketch a minimum free energy path connecting the supercooled liquid and the monoclinic crystal phases, and to determine the free energy and the rates involved in the homogeneous nucleation process. The physical significance of the configurations found along this minimum free energy path is discussed with the help of calculations based on classical nucleation theory and with additional simulation results obtained for a larger system. Our results indicate that, at a supercooling of 58 K, the liquid has to overcome a free energy barrier of the order of 60 kcal/mol and to form a critical nucleus with an average size of about 3.6 nm, before it reaches the thermodynamically stable crystal phase. A simulated homogeneous nucleation rate of 5.0 × 10(10) cm(-3) s(-1) was obtained for our system, which is in reasonable agreement with experimental and simulation rates for homogeneous nucleation of ice at similar degrees of supercooling. This study represents our first step in a series of studies aimed at understanding the nucleation and growth of crystals of organic salts near surfaces and inside nanopores.