Determining the shear viscosity of model liquids from molecular dynamics simulations

Synergistic Modeling of Liquid Properties: Integrating Neural Network-Derived Molecular Features with Modified Kernel Models

A significant challenge in applying machine learning to computational chemistry, particularly considering the growing complexity of contemporary machine learning models, is the scarcity of available experimental data. To address this issue, we introduce an approach that derives molecular features from an intricate neural network-based model and applies them to a simpler conventional machine learning model that is robust to overfitting. This method can be applied to predict various properties of a liquid system, including viscosity or surface tension, based on molecular features drawn from the ab initio calculated free energy of solvation. Furthermore, we propose a modified kernel model that includes Arrhenius temperature dependence to incorporate theoretical principles and diminish extreme nonlinearity in the model. The modified kernel model demonstrated significant improvements in certain scenarios and possible extensions to various theoretical concepts of molecular systems.

Molecular diffusion in aqueous methanol solutions: The combined influence of hydrogen bonding and hydrophobic ends

Although the nonmonotonic variation in the diffusion coefficients of alcohol and water with changing alcohol concentrations in aqueous solutions has been reported for many years, the underlying physical mechanisms remain unclear. Using molecular dynamics simulations, we investigated the molecular diffusion mechanisms in aqueous methanol solutions. Our findings reveal that the molecular diffusion is co-influenced by hydrogen bonding and the hydrophobic ends of methanol molecules. A stronger hydrogen bond (HB) network and a higher concentration of hydrophobic ends of methanol molecules both enhance molecular correlations, thereby slowing molecular diffusion in the solution. As methanol concentration increases, the HB network weakens, facilitating molecular diffusion. However, the increased concentration of hydrophobic ends counteracts this effect. Consequently, the diffusion coefficients of water and methanol molecules exhibit nonmonotonic changes. Previous studies have only focused on the role of HB networks. For the first time, we have identified the impact of the hydrophobic ends of alcohol on molecular diffusion in aqueous alcohol solutions. Our research contributes to a better understanding and manipulation of the properties of aqueous alcohol solutions and even liquids with complex compositions.

Origin of Pressure Resistance in Deep-Sea Lactate Dehydrogenase

High hydrostatic pressure has a dramatic effect on biochemical systems, as exposure to high pressure can result in structural perturbations ranging from dissociation of protein complexes to complete denaturation. The deep ocean presents an interesting paradox since it is teeming with life despite the high-pressure environment. This is due to evolutionary adaptations in deep-sea organisms, such as amino acid substitutions in their proteins, which aid in resisting the denaturing effects of pressure. However, the physicochemical mechanism by which these substitutions can induce pressure resistance remains unknown. Here, we use molecular dynamics simulations to study pressure-adapted lactate dehydrogenase from the deep-sea abyssal grenadier (Coryphaenoides armatus), in comparison with that of the shallow-water Atlantic cod (Gadus morhua). We examined structural, thermodynamic and volumetric contributions to pressure resistance, and report that the amino acid substitutions result in a decrease in volume of the deep-sea protein accompanied by a decrease in thermodynamic stability of the native protein. Our simulations at high pressure also suggest that differences in compressibility may be important for understanding pressure resistance in deep-sea proteins.

Molecular Dynamics Simulation of the Viscosity Enhancement Mechanism of P-n Series Vinyl Acetate Polymer-CO2

Carbon dioxide (CO2) drive is one of the effective methods to develop old oil fields with high water content for tertiary oil recovery and to improve the recovery rate. However, due to the low viscosity of pure CO2, it is not conducive to expanding the wave volume of the mixed phase, which leads to difficulty utilizing the residual oil in vertical distribution and a low degree of recovery in the reservoir. By introducing viscosity enhancers, it is possible to reduce the two-phase fluidity ratio, expanding the degree of longitudinal rippling and oil recovery efficiency. It has been proven that the acetate scCO2 tackifier PVE can effectively tackify CO2 systems. However, little research has been reported on the microscopic viscosity enhancement mechanism of scCO2 viscosity enhancers. To investigate the influence of a vinyl acetate (VAc) functional unit on the viscosity enhancement effect of the CO2 system, PVE (Polymer-Viscosity-Enhance, P-3) was used as the parent, the proportion of VAc was changed, and the molecules P-1 and P-2 were designed to establish a molecular dynamics simulation model for the P-n-CO2 system. The molecules in the system under the conditions of 70 °C-10 MPa, 80 °C-10 MPa, and 70 °C-20 MPa were simulated; the viscosity of the system was calculated; and the error between the theoretical and simulated values of the viscosity in the CO2 system was relatively small. The difference between P-n molecular structure and system viscosity was analyzed at multiple scales through polymer molecular dynamics simulations and used the molecular radial distribution function, system density, accessible surface area, radius of gyration, minimum intermolecular distance, and minimum number of intermolecular contacts as indicators. This study aimed to elucidate the viscosity enhancement mechanism, and the results showed that the higher the proportion of VAc introduced into the molecules of P-n-scCO2 viscosities, the larger the molecular amplitude, the larger the effective contact area, and the greater the viscosity of the system. Improvement in the contact efficiency between the ester group on the P-n molecule and CO2 promotes the onset of solvation behavior. This study on the microscopic mechanism of scCO2 tackifiers provides a theoretical approach for the design of new CO2 tackifiers.

Structure and Dynamics of Water in Polysaccharide (Alginate) Solutions and Gels Explained by the Core-Shell Model

In both biological and engineered systems, polysaccharides offer a means of establishing structural stiffness without altering the availability of water. Notable examples include the extracellular matrix of prokaryotes and eukaryotes, artificial skin grafts, drug delivery materials, and gels for water harvesting. Proper design and modeling of these systems require detailed understanding of the behavior of water confined in pores narrower than about 1 nm. We use molecular dynamics simulations to investigate the properties of water in solutions and gels of the polysaccharide alginate as a function of the water content and polymer cross-linking. We find that a detailed understanding of the nanoscale dynamics of water in alginate solutions and gels requires consideration of the discrete nature of water. However, we also find that the trends in tortuosity, permeability, dielectric constant, and shear viscosity can be adequately represented using the "core-shell" conceptual model that considers the confined fluid as a continuum.

Diffusion and Viscosity in Mixed Protein Solutions

The viscosity and diffusion properties of crowded protein systems were investigated with molecular dynamics simulations of SH3 mixtures with different crowders, and results were compared with experimental data. The simulations accurately reproduced experimental trends across a wide range of protein concentrations, including highly crowded environments up to 300 g/L. Notably, viscosity increased with crowding but varied little between different crowder types, while diffusion rates were significantly reduced depending on protein-protein interaction strength. Analysis using the Stokes-Einstein relation indicated that the reduction in diffusion exceeded what was expected from viscosity changes alone, with the additional slow-down attributable to transient cluster formation driven by weakly attractive interactions. Contact kinetics analysis further revealed that longer-lived interactions contributed more significantly to reduced diffusion rates than short-lived interactions. This study also highlights the accuracy of current computational methodologies for capturing the dynamics of proteins in highly concentrated solutions and provides insights into the molecular mechanisms affecting protein mobility in crowded environments.

Microscopic derivation of the thin film equation using the Mori-Zwanzig formalism

The hydrodynamics of thin films is typically described using macroscopic models whose connection to the microscopic particle dynamics is a subject of ongoing research. Existing methods based on density functional theory provide a good description of static thin films but are not sufficient for understanding nonequilibrium dynamics. In this work, we present a microscopic derivation of the thin film equation using the Mori-Zwanzig projection operator formalism. This method allows to directly obtain the correct gradient dynamics structure along with microscopic expressions for mobility and free energy. Our results are verified against molecular dynamics simulations for both simple fluids and polymers.

Drag on nanoparticles in a liquid: from slip to stick boundary conditions

Stokes' law with stick boundary conditions has been widely accepted for the transport of microscale particles in a liquid. For nanoparticles, however, the hydrodynamic boundary conditions become unclear. In this work, the drag force acting on nanoparticles suspended in a liquid and the hydrodynamic boundary coefficient were calculated by using molecular dynamics simulations. For weak interfacial couplings, slip boundary conditions can be used to describe the particle transport, whereas at strong interfacial couplings, the hydrodynamic boundary coefficient converges to a value greater than the prediction by Stokes' law. In the present paper, we propose a density accumulation length to determine the effective particle size, which makes Stokes' law valid for nanoparticles. For a copper nanoparticle suspended in an argon liquid, the density accumulation length increases to 0.32 nm with increasing solid-liquid coupling strength. Furthermore, it is found that there exists a transition from slip to stick boundary conditions as the solid-liquid intermolecular coupling strength increases. The results presented in this work provide guidance for the prediction and manipulation of the transport properties of nanoparticles in a liquid.

Reversible Hydrophobic Deep Eutectic Solvent-Based Uranyl-Sensing Optode Film in Aqueous Streams: Color Transformation and Reusability

A hydrophobic deep eutectic solvent (HDES)-based optode was designed for the preconcentration and determination of the UO22+ ion in aqueous media using spectroscopic techniques [energy-dispersive X-ray fluorescence (EDXRF) and solid-state absorption]. The optode was developed by incorporation of HDES (tri-n-octyl phosphine oxide and decanoic acid in an equimolar ratio), tri-(2-ethylhexyl) phosphate, and 2-(5-bromo-2-pyridylazo)-5-diethylaminophenol into a cellulose triacetate matrix. Characterization studies were carried out using different techniques to understand the roles of HDES as a plasticizer, UO22+ extractant, and Br-PADAP immobilizer. Uptake studies revealed that the optimal pH was 3 and sorption followed the type II adsorption isotherm. Uranium in the U-sorbed optode can be directly analyzed over a large concentration range of 0.021 × 10-3-2.1 × 10-3 Mol L-1 using EDXRF. The optode film exhibited a linear dynamic range of 0.84 × 10-6-84 × 10-6 Mol L-1 for uranium, with a lowest limit of detection of 0.084 × 10-6 Mol L-1 by colorimetric analysis. This optode-based method was employed for seawater analysis for its UO22+ concentration without any matrix separation, and the concentration was found to be 1.30 ± 0.06 × 10-8 Mol L-1. The optode exhibited better selectivity for UO22+ in the presence of various cations including Sr2+ and Cs+ in an aqueous medium. Compared to other prevailing optical sensors, this optode performed better in terms of key factors like pH, equilibration time, reusability, and detection limit.

Estimating water transport in carbon nanotubes: a critical review and inclusion of scale effects

The quasi-frictionless water flow across graphitic surfaces offers vast opportunities for a wide range of applications from biomedical science to energy. However, the conflicting experimental results impede a clear understanding of the transport mechanism and desired flow control. Existing literature proposes numerous modifications and updated boundary conditions to extend classical hydrodynamic theories for nanoflows, yet a consensus or definitive conclusion remains elusive. This study presents a critical review of the proposed modifications of the pressure driven flow or the Hagen-Poiseuille (HP) equations to estimate the flow enhancement through carbon nanotubes (CNTs). For such a case, we performed (semi-)classical molecular dynamics simulations of water flow in various sizes of CNTs, applied the different forms of boundary definitions from the literature, and derived HP equation models by implementing these modifications. By aggregating seven distinct experimental datasets, we tested various flow enhancement models against our measurements. Our findings indicate that including the interfacial layering-based dynamic slip-definition in the proposed HP equations yields accurate estimations. While considering interfacial viscosity predicts the individual CNT experiments well, using the experimental viscosity yields better estimations of measurements for the water flow enhancement through membranes of CNTs. This critical review testing existing literature demonstrates how to refine continuum fluid mechanics to predict water flow enhancement at the nanoscale providing holistic multiscale modeling.

O-glycans Expand Lubricin and Attenuate Its Viscosity and Shear Thinning

Lubricin, an intrinsically disordered glycoprotein, plays a pivotal role in facilitating smooth movement and ensuring the enduring functionality of synovial joints. The central domain of this protein serves as a source of this excellent lubrication and is characterized by its highly glycosylated, negatively charged, and disordered structure. However, the influence of O-glycans on the viscosity of lubricin remains unclear. In this study, we employ molecular dynamics simulations in the absence and presence of shear, along with continuum simulations, to elucidate the intricate interplay between O-glycans and lubricin and the impact of O-glycans on lubricin's conformational properties and viscosity. We found the presence of O-glycans to induce a more extended conformation in fragments of the disordered region of lubricin. These O-glycans contribute to a reduction in solution viscosity but at the same time weaken shear thinning at high shear rates, compared to nonglycosylated systems with the same density. This effect is attributed to the steric and electrostatic repulsion between the fragments, which prevents their conglomeration and structuring. Our computational study yields a mechanistic mechanism underlying previous experimental observations of lubricin and paves the way to a more rational understanding of its function in the synovial fluid.

A Reverse Nonequilibrium Molecular Dynamics Algorithm for Coupled Mass and Heat Transport in Mixtures

We present a new method for introducing stable nonequilibrium concentration gradients in molecular dynamics simulations of mixtures. This method extends earlier reverse nonequilibrium molecular dynamics (RNEMD) methods, which use kinetic energy scaling moves to create temperature or velocity gradients. In the new scaled particle flux (SPF-RNEMD) algorithm, energies and forces are computed simultaneously for a molecule existing in two nonadjacent regions of a simulation box, and the system evolves under a linear combination of these interactions. A continuously increasing particle scaling variable is responsible for the migration of the molecule between the regions as the simulation progresses, allowing for simulations under an applied particle flux. To test the method, we investigate diffusivity in mixtures of identical but distinguishable particles and in a simple mixture of multiple Lennard-Jones particles. The resulting concentration gradients provide Fick diffusion constants for mixtures. We also discuss using the new method to obtain coupled transport properties using simultaneous particle and thermal fluxes to compute the temperature dependence of the diffusion coefficient and activation energies for diffusion from a single simulation. Lastly, we demonstrate the use of this new method in interfacial systems by computing the diffusive permeability of a molecular fluid moving through a nanoporous graphene membrane.

Quantifying uncertainty in trans-membrane stresses and moments in simulation

The lateral stress profile of a lipid bilayer constitutes a valuable link between molecular simulation and mesoscopic elastic theory. Even though it is frequently calculated in simulations, its statistical precision (or that of observables derived from it) is often left unspecified. This omission can be problematic, as uncertainties are prerequisite to assessing statistical significance. In this chapter, we provide a comprehensive yet accessible overview of the statistical error analysis for the lateral stress profile. We detail two relatively simple but powerful techniques for generating error bars: block-averaging and bootstrapping. Combining these methods allows us to reliably estimate uncertainties, even in the presence of both temporal and spatial correlations, which are ubiquitous in simulation data. We illustrate these techniques with simple examples like stress moments, but also more complex observables such as the location of stress profile extrema and the monolayer neutral surface.

MDs-NP: a property prediction model construction procedure for naphtha based on molecular dynamics simulation

In the context of carbon neutrality and carbon peaking, molecular management has become a focus of the petrochemical industry. The key to achieving molecular management is molecular reconstruction, which relies on rapid and accurate calculation of oil properties. Focusing on naphtha, we proposed a novel property prediction model construction procedure (MDs-NP) employing molecular dynamics simulations for property collections and gamma distribution from real analytical data for calculating mole fractions of simulation mixtures. We calculated 348 sets of mixture properties data in the range of 273 K-300 K by molecular dynamics simulations. Molecular feature extraction was based on molecular descriptors. In addition to descriptors based on open-source toolkits (RDKit and Mordred), we designed 12 naphtha knowledge (NK) descriptors with a focus on naphtha. Three machine learning algorithms (support vector regression, extreme gradient boosting and artificial neural network) were applied and compared to establish models for the prediction of the density and viscosity of naphtha. Mordred and NK descriptors + support vector regression algorithm achieved the best performance for density. The selected RDKFp and NK descriptors + artificial neural network algorithm achieved the best performance for viscosity. Using ablation studies, T, P_w and CC(C)C are three effective descriptors in NK that can improve the performance of the property prediction models. MDs-NP has the potential to be extended to more properties as well as more-complex petroleum systems. The models from MDs-NP can be used for rapid molecular reconstruction to facilitate construction of data-driven models and intelligent transformation of petrochemical processes.

Vehicular Motions Dominate the Ion Transport in Concentrated LiTFSI Aqueous Solutions?

Water-in-salt electrolytes (WiSEs) show great promise for applications in grid-scale energy storage. The design of high-performance WiSEs requires a comprehensive understanding of their microstructures and ion transport properties. In the present work, based on the CL&Pol force field, we have developed a polarizable force field (PFF) tailored for high-concentration LiTFSI aqueous solutions, which accurately reproduces the structural and dynamical properties. Unlike the literature, we do not observe the presence of bulk-like water in LiTFSI solutions exceeding 19 mol/kg. Furthermore, we find that the vast majority of Li(H20)n+ are short-lived, and thus, the structural motion rather than the vehicular motion is the main mode of ion transport. Our results have significant implications for understanding the ion dynamics in WiSEs. Additionally, further in-depth experimental analyses are imperative.

A molecular dynamics simulation study of glycine/serine octapeptides labeled with 2,3-diazabicyclo[2.2.2]oct-2-ene fluorophore

The compound 2,3-diazabicyclo[2.2.2]oct-2-ene (DBO) is a versatile fluorophore widely used in Förster resonance energy transfer (FRET) spectroscopy studies due to its remarkable sensitivity, enabling precise donor-acceptor distance measurements, even for short peptides. Integrating time-resolved and FRET spectroscopies with molecular dynamics simulations provides a robust approach to unravel the structure and dynamics of biopolymers in a solution. This study investigates the structural behavior of three octapeptide variants: Trp-(Gly-Ser)3-Dbo, Trp-(GlyGly)3-Dbo, and Trp-(SerSer)3-Dbo, where Dbo represents the DBO-containing modified aspartic acid, using molecular dynamics simulations. Glycine- and serine-rich amino acid fragments, common in flexible protein regions, play essential roles in functional properties. Results show excellent agreement between end-to-end distances, orientational factors from simulations, and the available experimental and theoretical data, validating the reliability of the GROMOS force field model. The end-to-end distribution, modeled using three Gaussian distributions, reveals a complex shape, confirmed by cluster analysis highlighting a limited number of significant conformations dominating the peptide landscape. All peptides predominantly adopt a disordered state in the solvent, yet exhibit a compact shape, aligning with the model of disordered polypeptide chains in poor solvents. Conformations show marginal dependence on chain composition, with Ser-only chains exhibiting slightly more elongation. This study enhances our understanding of peptide behavior, providing valuable insights into their structural dynamics in solution.

Boron-containing fullerene-based salts with cyclic carbonate solvents as electrolytes for Li-ion batteries and beyond

Replacement of carbon atoms by a heteroatom in fullerene is a promising route that enhances the electronic properties of fullerenes and results in hetero fullerene-based effective agents ensuring applications in vivid fields of the solar cell, cathode materials for batteries, etc. Towards the development of new electrolyte salts, attention has been paid to facilitating ion mobility in particular and moderate stability of the anions in addition. From the atomistic molecular dynamics simulation studies, for the first time, we uncover that the boron-containing hetero fullerene, C59B- anion-based LiC59B, and NaC59B salts in cyclic carbonate solvents can act as efficient electrolytes by improving the transport phenomenon of the metal ions in solution, importantly for Li+ and satisfactorily for Na+ as compared to their commonly used BF4- anion based salts. Additionally, our study revealed that apart from LiC59B, and NaC59B salts, C58B22- based MgC58B2 salt can facilitate the ionic conductivity of the electrolyte. The properties of the proposed electrolyte under an electric field and different temperatures were investigated. Some of the bulk properties of the used electrolytes to some extent were found to be improved in the presence of these salts. The first principle-based electrochemical calculations further justify the stability of the proposed anions. The initial investigation from the Reactive force-field (ReaxFF) based atomistic simulations study elucidates that LiC59B reduces the decomposition of the EC solvent compared to LiBF4 and facilitates solvent stability.

Sensing membrane voltage by reorientation of dipolar transmembrane peptides

Membrane voltage plays a vital role in the behavior and functions of the lipid bilayer membrane. For instance, it regulates the exchange of molecules across the membrane through transmembrane proteins such as ion channels. In this paper, we study the membrane voltage-sensing mechanism, which entails the reorientation of α-helices with a change in the membrane voltage. We consider a helix having a large electrical macrodipole embedded in a lipid bilayer as a model system. We performed extensive molecular dynamics simulations to study the effect of variation of membrane voltage on the tilt angle of peptides and ascertain the optimal parameters for designing such a voltage-sensing peptide. A theoretical model for the system is also developed to investigate the interplay of competing effects of hydrophobic mismatch and dipole-electric field coupling on the tilt of the peptide and further explore the parameter space. This work opens the possibility for the design and fabrication of artificial dipolar membrane voltage-sensing elements for biomedical applications.

Designing and preparing supramolecular encapsulation systems based on fraxetin and cyclodextrins for highly selective detection of nicotine

Herein, a series of water-soluble supramolecular inclusion complexes (ICs) probes were prepared using cyclodextrins (CDs) and fraxetin (FRA) to detect nicotine (NT) with high selectivity in vitro and in vivo. The FRA/CD ICs prepared through the saturated solution method exhibited excellent water solubility, stability, and biocompatibility. A clear host-guest inclusion model was provided by the theoretical calculations. The investigation revealed that NT was able to enter into the cavities of FRA/β-CD IC and FRA/γ-CD IC, and further formed charge transfer complexes with FRA in the CD cavities, resulting in a rapid and highly selective fluorescence-enhanced response with the lowest detection limits of 1.9 × 10-6 M and 9.7 × 10-7 M, and the linear response ranged from 0.02 to 0.3 mM and 0.01-0.05 mM, respectively. The IC probes showed good anti-interference performance to common interferents or different pH environments, with satisfactory reproducibility and repeatability of response to NT. Furthermore, the potentiality of the probes was confirmed through fluorescence imaging experiments using human lung cancer cells and the lung tissue of mice. This study offers a fresh perspective for detecting NT in environmental and biomedical analysis.

Structure and dynamics of dissociated and undissociated forms of nitric acid and their implications in interfacial mass transfer: insights from molecular dynamics simulations

Nitric acid (HNO3) is widely used in various chemical and nuclear industries. Therefore, it is important to develop an understanding of the different forms of nitric acid for its practical applications. Molecular dynamics (MD) simulation is one of the best tools to investigate the behavior of concentrated nitric acid in aqueous solution with various forms together with pure nitric acid to identify a suitable model of nitric acid for use in simulations of biphasic systems for interfacial mass transfer. The Mulliken partial charge embedded OPLS-AA force field was used to model the neutral nitric acid, hydronium ion and nitrate ion, and it was found that the Mulliken partial charge embedded force field works quite well. The computed density of the dissociated and mixed-form acid was in good agreement with the experimental values. In water, the HNO3 molecule was seen to be coordinated with three water molecules in the first sphere of coordination. The distribution of water surrounding the HNO3 molecule and nitrate ion was corroborated by the DFT-optimized hydrated cluster. The calculated diffusivity values of the neutral acid and ions were significantly higher in the mixed form of nitric acid, which is an important dynamic quantity controlling the kinetics of the liquid-liquid interfacial extraction. The structural analysis revealed that the local aggregation is minimized when both forms of acid are present together in the solution. The water-ion and water-neutral acid interactions were predicted to be enhanced, as confirmed by H-bond studies. The shear viscosity of the mixed acid exhibited excellent agreement with the experimental values, which again confirms the consideration of the mixed form of nitric acid. The simulated value of surface tension for the mixed form of acid also appeared to be quite accurate based on the surface tension of water. The mixed form of nitric acid comprising both forms of acid is the best representation for nitric acid to be considered for MD simulations of biphasic systems. The mixed form of nitric acid established that the concentrated nitric acid may not be present either in the fully dissociated form or fully undissociated form in the solution.

Ion transport mechanisms in pectin-containing EC-LiTFSI electrolytes

Using all-atom molecular dynamics simulations, we report the structure and ion transport characteristics of a new class of solid polymer electrolytes that contain the biodegradable and mechanically stable biopolymer pectin. We used highly conducting ethylene carbonate (EC) as a solvent for simulating lithium-trifluoromethanesulfonimide (LiTFSI) salt containing different weight percentages of pectin. Our simulations reveal that the pectin chains reduce the coordination number of lithium ions around their counterions (and vice versa) because of stronger lithium-pectin interactions compared to lithium-TFSI interactions. Furthermore, the pectin is found to promote smaller ionic aggregates over larger ones, in contrast to the results typically reported for liquid and polymer electrolytes. We observed that the loading of pectin in EC-LiTFSI electrolytes increases their viscosity (η) and relaxation timescales (τc), indicating higher mechanical stability, and, consequently, a decrease of the mean squared displacement, diffusion coefficient (D), and Nernst-Einstein conductivity (σNE). Interestingly, while the lithium diffusivities are related to the ion-pair relaxation timescales as D+ ∼ τc-3.1, the TFSI- diffusivities exhibit excellent correlations with ion-pair relaxation timescales as D- ∼ τc-0.95. On the other hand, the NE conductivities are dictated by distinct transport mechanisms and scales with ion-pair relaxation timescales as σNE ∼ τc-1.85.

Computing Accurate True Self-Diffusion Coefficients and Shear Viscosities Using the OrthoBoXY Approach

In a recent paper [Busch, J.; Paschek, D. J. Phys. Chem. B 2023, 127, 7983-7987], we have shown that for molecular dynamics (MD) simulations using orthorhombic periodic boundary conditions with "magic" box length ratios of Lz/Lx = Lz/Ly = 2.7933596497, the self-diffusion coefficients Dx and Dy in x- and y-directions are independent of the system size. They both represent the true self-diffusion coefficient D0 = (Dx + Dy)/2, while the shear viscosity can be calculated from diffusion coefficients in x-, y-, and z-directions, using η = kBT·8.1711245653/[3πLz(Dx + Dy - 2Dz)]. In this contribution, we test this "OrthoBoXY" approach by its application to a variety of different systems: liquid water, dimethyl ether, methanol, triglyme, water/methanol mixtures, water/triglyme mixtures, and imidazolium-based ionic liquids. The chosen systems range from small-sized molecular liquids to complex mixtures and ionic liquids, while spanning a viscosity range of almost 3 orders of magnitude. We assess the efficiency of the method for computing true self-diffusion and viscosity data and provide simple formulas for estimating the required MD simulation lengths and sizes for delivering reliable data with targeted uncertainty levels. Our analysis of the system size dependence of statistical uncertainties for both the viscosity and the self-diffusion coefficient leads us to the conclusion that it is preferable to extend the simulation length instead of increasing the system size. MD simulations consisting of 768 molecules or ion pairs seem to be perfectly adequate.

Application of Polymeric CO2 Thickener Polymer-Viscosity-Enhance in Extraction of Low-Permeability Tight Sandstone

The conventional production technique employed for low-permeability tight reservoirs exhibits limited productivity. To solve the problem, an acetate-type supercritical carbon dioxide (scCO2) thickener, PVE, which contains a large number of microporous structures, was prepared using the atom transfer radical polymerization (ATRP) method. The product exhibited an ability to decrease the minimum miscibility pressure of scCO2 during a solubility test and demonstrated a favorable extraction efficiency in a low-permeability tight core displacement test. At 15 MPa and 70 °C, PVE-scCO2 at a concentration of 0.2% exhibits effective oil recovery rates of 5.61% for the 0.25 mD core and 2.65% for the 5 mD core. The result demonstrates that the incorporation of the thickener PVE can effectively mitigate gas channeling, further improve oil displacement efficiency, and inflict minimal damage to crude oil. The mechanism of thickening was analyzed through molecular simulation. The calculated trend of thickening exhibited excellent agreement with the experimental measurement rule. The simulation results demonstrate that the contact area between the polymer and CO2 increases in direct proportion to both the number of thickener molecules and the viscosity of the system. The study presents an effective strategy for mitigating gas channeling during scCO2 flooding and has a wide application prospect.

Efficient single-run implementation of generalized Einstein relation to compute transport coefficients: A binary-based time sampling

A robust and simple implementation of the generalized Einstein formulation using single equilibrium molecular dynamics simulation is introduced to compute diffusion and shear viscosity. The unique features underlying this framework are as follows: (1) The use of a simple binary-based method to sample time-dependent transport coefficients results in a uniform distribution of data on a logarithmic time scale. Although we sample "on-the-fly," the algorithm is readily applicable for post-processing analysis. Overlapping same-length segments are not sampled as they indicate strong correlations. (2) Transport coefficients are estimated using a power law fitting function, a generalization of the standard linear relation, that accurately describes the long-time plateau. (3) The use of a generalized least squares (GLS) fitting estimator to explicitly consider correlations between fitted data points results in a reliable estimate of the statistical uncertainties in a single run. (4) The covariance matrix for the GLS method is estimated analytically using the Wiener process statistics and computed variances. (5) We provide a Python script to perform the fits and automate the procedure to determine the optimal fitting domain. The framework is applied to two fluids, binary hard sphere and a Lennard-Jones near the triple point, and the validity of the single-run estimates is verified against multiple independent runs. The approach should be applicable to other transport coefficients since the diffusive limit is universal to all of them. Given its rigor and simplicity, this methodology can be readily incorporated into standard molecular dynamics packages using on-the-fly or post-processing analysis.

Effect of Fe-O ReaxFF on Liquid Iron Oxide Properties Derived from Reactive Molecular Dynamics

As iron powder nowadays attracts research attention as a carbon-free, circular energy carrier, molecular dynamics (MD) simulations can be used to better understand the mechanisms of liquid iron oxidation at elevated temperatures. However, prudence must be practiced in the selection of a reactive force field. This work investigates the influence of currently available reactive force fields (ReaxFFs) on a number of properties of the liquid iron-oxygen (Fe-O) system derived (or resulting) from MD simulations. Liquid Fe-O systems are considered over a range of oxidation degrees ZO, which represents the molar ratio of O/(O + Fe), with 0 < ZO < 0.6 and at a constant temperature of 2000 K, which is representative of the combustion temperature of micrometric iron particles burning in air. The investigated properties include the minimum energy path, system structure, (im)miscibility, transport properties, and the mass and thermal accommodation coefficients. The properties are compared to experimental values and thermodynamic calculation results if available. Results show that there are significant differences in the properties obtained with MD using the various ReaxFF parameter sets. Based on the available experimental data and equilibrium calculation results, an improved ReaxFF is required to better capture the properties of a liquid Fe-O system.

Computation of Shear Viscosity by a Consistent Method in Equilibrium Molecular Dynamics Simulations: Applications to 1-Decene Oligomers

Accurate computation of shear viscosity is fundamental for describing fluid flow and designing and developing new processes. Poly-α-olefins (PAO's), particularly from 1-decene, have been applied to a variety of industrial processes. Recently, these molecules have been applied as carbon dioxide thickeners, enhancing carbon dioxide viscosity, which is important in carbon dioxide injection, either for enhanced oil recovery or sequestration in geological formations. For these applications, knowledge of the pure oligomer viscosity is crucial to design and operate the oligomer upstream pipelines before mixing them with carbon dioxide. Using Green-Kubo formalism with equilibrium molecular dynamics simulations, two methods are presented in the literature to generate the traceless, symmetric pressure tensor. In this work, we show that these two methods provide different values of shear viscosity, from the analysis of how the diagonal components of the traceless, symmetric pressure tensor are computed in each method. Then, we examine the consistency and correctness of each method: one is found to be consistent. The other is corrected by scaling the fluctuations of the diagonal components. Shear viscosities of supercritical carbon dioxide, vapor and liquid n-pentane, and liquid n-decane are computed to illustrate the analysis. We also apply the consistent method to compute the viscosity of 1-decene oligomers, including for the first time larger-than-dimer oligomers (trimer, tetramer, hexamer, and decamer).

Toward a molecular understanding of the conductivity of lithium-ion conducting polyanion polymer electrolytes by molecular dynamics simulation

With the improved lithium-ion transference number near unity, the low conductivity of single lithium-ion conducting solid polymer electrolytes (SLIC-SPEs) still hinders their application in high-rate batteries. Though some empirical conclusions on the conducting mechanism of SLIC-SPEs have been obtained, a more comprehensive study on the quantitative relationship between the molecular structure factors and ionic conduction performance is expected. In this study, a model structure that contains adjustable main chain and anion groups in the polyethylene oxide (PEO) matrix was used to clarify the influence of molecular structural factors on ionic conductivity and electrochemical stability of SLIC-SPEs. The anionic group was further disassembled into the intermediate group and end group while the main chain structure was distinguished into different degrees of polymerization and various lengths of the spacers between anions. Therefore, a well-defined molecular structure was employed to describe its relationship with ionic conductivity. In addition, the dissociation degree of salts and mobility of ions changing with the molecular structure were also discussed to explore the fundamental causes of conductivity. It can be concluded that the anion group affects the conductivity mainly via the dissociation degree, while the main chain structure impacts the conductivity by both dissociation degree and mobility.

Modeling the influence of the external electric fields on water viscosity inside carbon nanotubes

Equilibrium molecular dynamics simulations were performed to explore the effects of external electric fields and confinement on water properties inside various carbon nanotubes (CNTs). Using different GHz electric field frequencies as well as various constant electric field strengths, the radial distribution function and density profile were investigated, by which the impact of the electric fields and confinement on the water structure are revealed. The results indicated water molecules inside the CNT form layered structures due to topological confinement applying external electric fields can disturb this ordered water molecules structure and increase the viscosity of confined water, particularly in the case of CNTs with a radius less than 13.5 Å. Conversely, for CNTs with a radius greater than13.5 Å, the viscosity decreases under the influence of external oscillating or constant electric fields. How dose the synergism of confinement and external electric fields affect the water properties inside the CNTs?

Viscosity Prediction of High-Concentration Antibody Solutions with Atomistic Simulations

The computational prediction of the viscosity of dense protein solutions is highly desirable, for example, in the early development phase of high-concentration biopharmaceutical formulations where the material needed for experimental determination is typically limited. Here, we use large-scale atomistic molecular dynamics (MD) simulations with explicit solvation to de novo predict the dynamic viscosities of solutions of a monoclonal IgG1 antibody (mAb) from the pressure fluctuations using a Green-Kubo approach. The viscosities at simulated mAb concentrations of 200 and 250 mg/mL are compared to the experimental values, which we measured with rotational rheometry. The computational viscosity of 24 mPa·s at the mAb concentration of 250 mg/mL matches the experimental value of 23 mPa·s obtained at a concentration of 213 mg/mL, indicating slightly different effective concentrations (or activities) in the MD simulations and in the experiments. This difference is assigned to a slight underestimation of the effective mAb-mAb interactions in the simulations, leading to a too loose dynamic mAb network that governs the viscosity. Taken together, this study demonstrates the feasibility of all-atom MD simulations for predicting the properties of dense mAb solutions and provides detailed microscopic insights into the underlying molecular interactions. At the same time, it also shows that there is room for further improvements and highlights challenges, such as the massive sampling required for computing collective properties of dense biomolecular solutions in the high-viscosity regime with reasonable statistical precision.

Probing the Origin of Viscosity of Liquid Electrolytes for Lithium Batteries

Viscosity is an extremely important property for ion transport and wettability of electrolytes. Easy access to viscosity values and a deep understanding of this property remain challenging yet critical to evaluating the electrolyte performance and tailoring electrolyte recipes with targeted properties. We proposed a screened overlapping method to efficiently compute the viscosity of lithium battery electrolytes by molecular dynamics simulations. The origin of electrolyte viscosity was further comprehensively probed. The viscosity of solvents exhibits a positive correlation with the binding energy between molecules, indicating viscosity is directly correlated to intermolecular interactions. Salts in electrolytes enlarge the viscosity significantly with increasing concentrations while diluents serve as the viscosity reducer, which is attributed to the varied binding strength from cation-anion and cation-solvent associations. This work develops an accurate and efficient method for computing the electrolyte viscosity and affords deep insight into viscosity at the molecular level, which exhibits the huge potential to accelerate advanced electrolyte design for next-generation rechargeable batteries.

Coarse-grained explicit-solvent molecular dynamics simulations of semidilute unentangled polyelectrolyte solutions

We present results from explicit-solvent coarse-grained molecular dynamics (MD) simulations of fully charged, salt-free, and unentangled polyelectrolytes in semidilute solutions. The inclusion of a polar solvent in the model allows for a more physical representation of these solutions at concentrations, where the assumptions of a continuum dielectric medium and screened hydrodynamics break down. The collective dynamic structure factor of polyelectrolytes, S(q, t), showed that at [Formula: see text], where [Formula: see text] is the polyelectrolyte peak in the structure factor S(q) and [Formula: see text] is the correlation length, the relaxation time obtained from fits to stretched exponential was [Formula: see text], which describes unscreened Zimm-like dynamics. This is in contrast to implicit-solvent simulations using a Langevin thermostat where [Formula: see text]. At [Formula: see text], a crossover region was observed that eventually transitions to another inflection point [Formula: see text] at length scales larger than [Formula: see text] for both implicit- and explicit-solvent simulations. The simulation results were also compared to scaling predictions for correlation length, [Formula: see text], specific viscosity, [Formula: see text], and diffusion coefficient, [Formula: see text], where [Formula: see text] is the polyelectrolyte concentration. The scaling prediction for [Formula: see text] holds; however, deviations from the predictions for [Formula: see text] and D were observed for systems at higher [Formula: see text], which are in qualitative agreements with recent experimental results. This study highlights the importance of explicit-solvent effects in molecular dynamics simulations, particularly in semidilute solutions, for a better understanding of polyelectrolyte solution behavior.

Investigating the Behavior of Various Lubrication Regimes under Dynamic Conditions Using Nonequilibrium Molecular Dynamics

It is crucial to comprehend how the oil film varies under dynamic operating conditions and the accompanying friction properties to better grasp the friction mechanism and control friction behavior. To model the friction characteristics under boundary lubrication (BL) and elastohydrodynamic lubrication (EHL), nonequilibrium molecular dynamics simulations with various numbers of hexadecane molecules as lubricating oil were conducted in this research under the conditions of dynamic speed and dynamic load. All the dynamic operating conditions have the form of sine waves, with various frequencies and amplitudes. According to the findings, the friction force is strongly connected with interfaces where relative sliding takes place, whose number, velocity difference, and the degree of solidification have significant influences. The variation of amplitude under dynamic load can cause a regular change in the density of the lubricating layer, while the variation of frequency can cause a change in molecular layer's range of motion. Both effects are crucial for friction. The structure of the lubricating layer with lower friction varies with various frequencies for dynamic velocity. Both high and small amplitudes of velocity offer advantages to form a stable film structure at low frequencies in the BL and EHL regions, while the amplitude in the BL area has minimal association with friction at high frequencies. At high frequencies in the EHL region, the friction rises as the amplitude of velocity grows and the lubricating layer becomes more unstable.

Protein compactness and interaction valency define the architecture of a biomolecular condensate across scales

Non-membrane-bound biomolecular condensates have been proposed to represent an important mode of subcellular organization in diverse biological settings. However, the fundamental principles governing the spatial organization and dynamics of condensates at the atomistic level remain unclear. The Saccharomyces cerevisiae Lge1 protein is required for histone H2B ubiquitination and its N-terminal intrinsically disordered fragment (Lge11-80) undergoes robust phase separation. This study connects single- and multi-chain all-atom molecular dynamics simulations of Lge11-80 with the in vitro behavior of Lge11-80 condensates. Analysis of modeled protein-protein interactions elucidates the key determinants of Lge11-80 condensate formation and links configurational entropy, valency, and compactness of proteins inside the condensates. A newly derived analytical formalism, related to colloid fractal cluster formation, describes condensate architecture across length scales as a function of protein valency and compactness. In particular, the formalism provides an atomistically resolved model of Lge11-80 condensates on the scale of hundreds of nanometers starting from individual protein conformers captured in simulations. The simulation-derived fractal dimensions of condensates of Lge11-80 and its mutants agree with their in vitro morphologies. The presented framework enables a multiscale description of biomolecular condensates and embeds their study in a wider context of colloid self-organization.

Mechanistic understanding of the correlation between structure and dynamics of liquid carbonate electrolytes: impact of polarization

Liquid electrolyte design and modelling is an essential part of the development of improved lithium ion batteries. For mixed organic carbonates (ethylene carbonate (EC) and ethyl-methyl carbonate (EMC) mixtures)-based electrolytes with LiPF₆ as salt, we have compared a polarizable force field with the standard non-polarizable force field with and without charge rescaling to model the structural and dynamic properties. The result of our molecular dynamics simulations shows that both polarizable and non-polarizable force fields have similar structural factors, which are also in agreement with X-ray diffraction experimental results. In contrast, structural differences are observed for the lithium neighborhood, while the lithium-anion neighbourhood is much more pronounced for the polarizable force field. Comparison of EC/EMC coordination statistics with Fourier transformed infrared spectroscopy (FTIR) shows the best agreement for the polarizable force field. Also for transport quantities such as ionic conductivities, transference numbers, and viscosities, the agreement with the polarizable force field is by far better for a large range of salt concentrations and EC : EMC ratios. In contrast, for the non-polarizable variants, the dynamics are largely underestimated. The excellent performance of the polarizable force field is explored in different ways to pave the way to a realistic description of the structure-dynamics relationships for a wide range of salt and solvent compositions for this standard electrolyte. In particular, we can characterize the distinct correlation terms between like and unlike ions, relate them to structural properties, and explore to which degree the transport in this electrolyte is mass or charge limited.

A Neural-Network-Optimized Hydrogen Peroxide Pairwise Additive Model for Classical Simulations

We have developed an all-atom pairwise additive model for hydrogen peroxide using an optimization procedure based on artificial neural networks (ANNs). The model is based on experimental molecular geometry and includes a dihedral potential that hinders the cis-type configuration and allows for crossing the trans one, defined between the planes that have the two oxygen atoms and each hydrogen. The model's parametrization is achieved by training simple ANNs to minimize a target function that measures the differences between various thermodynamic and transport properties and the corresponding experimental values. Finally, we evaluated a range of properties for the optimized model and its mixtures with SPC/E water, including bulk-liquid properties (density, thermal expansion coefficient, adiabatic compressibility, etc.) and properties of systems at equilibrium (vapor and liquid density, vapor pressure and composition, surface tension, etc.). Overall, we obtained good agreement with experimental data.

Assessing the Validity of NMR Relaxation Rates Obtained from Coarse-Grained Simulations of PEG-Water Mixtures

NMR relaxometry is a powerful and well-established experimental approach for characterizing dynamic processes in soft matter systems. All-atom (AA) resolved simulations are typically employed to gain further microscopic insights while reproducing the relaxation rates R₁. However, such approaches are limited to time and length scales that prevent to model systems such as long polymer chains or hydrogels. Coarse graining (CG) can overcome this barrier at the cost of losing atomistic details that impede the calculation of NMR relaxation rates. Here, we address this issue by performing a systematic characterization of dipolar relaxation rates R₁ on a PEG-H₂O mixture at two different levels of details: AA and CG. Remarkably, we show that NMR relaxation rates R₁ obtained at the CG level obey the same trends when compared to AA calculations but with a systematic offset. This offset is due to, on the one hand, the lack of an intramonomer component and, on the other hand, the inexact positioning of the spin carriers. We show that the offset can be corrected for quantitatively by reconstructing a posteriori the atomistic details for the CG trajectories.

Contribution of air-water interface in removing PFAS from drinking water: Adsorption, stability, interaction and machine learning studies

As a class of synthetic persistent organic pollutants, contamination of Per-and poly-fluoroalkyl substances (PFAS) in drinking water has attracted widespread concern. Aeration has been confirmed to enhance the removal of PFAS in drinking water by activated carbon (AC). However, the contribution of the air-water interface in removing PFAS is not yet to be fully understood at the molecular level. In this work, molecular dynamics (MD) simulations were employed to investigate the role of nanobubble in removing PFAS in the aqueous environment. The result suggests that the free energies of the air-water interface are about 3-7 kcal mol^-1 lower than that of the bulk water region, indicating that the transformation of PFAS from the water phase into the air-water interface is favorable from the viewpoint of thermodynamics. The interface-water partition coefficients (P_sur/wat) of PFAS are in the order of PFOS > PFOA > PFHxS > PFBS. On the air-water-AC three-phase interface, PFBS can not only move along the interface region but also leave the interface region into water phase, while PFOS tended to move along the interface region until it was captured by AC. Finally, the ΔG_{water-interface} quantitative structure-activity relationships (QSAR) models were developed to predict the removal efficiencies of PFAS enhanced by aeration in aquatic systems. The proposed mechanism promotes the understanding of the contribution of air-water interface in removing PFAS from drinking water by activated carbon.

Theoretical study on the solvation mechanism of camptothecin in ionic liquids

To reduce the environmental pollution caused by organic solvents and improve the extraction efficiency, a range of imidazolium-based ionic liquid (IL) combinations of [Omim]⁺ paired with [Br]^-, [BF₄]^-, [Cl]^-, [ClO₄]^-, [HsO₄]^-, [NO₃]^-, [NTf₂]^-, [OAc]^-, [PF₆]^-, and [TsO]^- are explored for the extraction of camptothecin (CPT) using molecular dynamics (MD) simulation and density functional theory (DFT) calculations. It is found that the ILs containing [Br]^-, [OAc]^-, and [TsO]^- anions are the most promising solvents for CPT solvation because they exhibit stronger interaction energy and the lowest self-diffusion coefficient of CPT among all ILs. The microscopic mechanism at the molecular level is revealed based on DFT calculations and MD simulations, and the results demonstrate that the IL (i.e., [Omim][TsO]) containing anions with strong hydrogen bond (HB) acceptability and aromatic ring structure corresponds to both the strongest van der Waals interaction and strongest HB interaction of CPT-anions. Therefore, it is recommended that anions with aromatic ring structures or strong HB acceptability are promising anion candidates, while anions containing electron withdrawing groups and bulky substituents should be avoided. This work provides intermolecular insight into designing and selecting effective ILs for natural insoluble active pharmaceutical ingredient dissolution and extraction in further research.

Molecular Dynamics Study of Cured ED-20 Epoxy Resin for Predicting the Glass Transition Temperature and Relationship with Structure Features

A structural model of ED-20 epoxy resin cured by triethylenetetramine was constructed using a molecular dynamics (MD) simulation method. In order to model the epoxy resin hardening, we modified a typical stepwise protocol introducing cross-links between the amino groups and epoxide carbon atoms that allowed us to reproduce experimentally observed glass transition temperature at the value of 360-364 K. The set of MD trajectories of the final molecular-mechanical model can be useful for analysis of alterations in structural and physical properties of the epoxy resin depending on scaleable parameters. The relationships among qualitative alterations in macromolecular structure, the glass transition temperature, and the number of imposed cross-links were elucidated. Analysis of intermolecular interactions between the largest macromolecules and other molecules of a system made it possible to observe the features of the transition from glassy to the viscoelastic state of the studied polymer during the temperature rise.

Surface viscosities of lipid bilayers determined from equilibrium molecular dynamics simulations

Lipid membrane viscosity is critical to biological function. Bacterial cells grown in different environments alter their lipid composition in order to maintain a specific viscosity, and membrane viscosity has been linked to the rate of cellular respiration. To understand the factors that determine the viscosity of a membrane, we ran equilibrium all-atom simulations of single component lipid bilayers and calculated their viscosities. The viscosity was calculated via a Green-Kubo relation, with the stress-tensor autocorrelation function modeled by a stretched exponential function. By simulating a series of lipids at different temperatures, we establish the dependence of viscosity on several aspects of lipid chemistry, including hydrocarbon chain length, unsaturation, and backbone structure. Sphingomyelin is found to have a remarkably high viscosity, roughly 20 times that of DPPC. Furthermore, we find that inclusion of the entire range of the dispersion interaction increases viscosity by up to 140%. The simulated viscosities are similar to experimental values obtained from the rotational dynamics of small chromophores and from the diffusion of integral membrane proteins but significantly lower than recent measurements based on the deformation of giant vesicles.

Extension of the TraPPE Force Field for Battery Electrolyte Solvents

Optimizing electrolyte formulations is key to improving performance of Li-/Na-ion batteries, where transport properties (diffusion coefficient, viscosity) and permittivity need to be predicted as functions of temperature, salt concentration and solvent composition. More efficient and reliable simulation models are urgently needed, owing to the high cost of experimental methods and the lack of united-atom molecular dynamics force fields validated for electrolyte solvents. Here the computationally efficient TraPPE united-atom force field is extended to be compatible with carbonate solvents, optimizing the charges and dihedral potential. Computing the properties of electrolyte solvents, ethylene carbonate (EC), propylene carbonate (PC), dimethyl carbonate (DMC), diethyl carbonate (DEC), and dimethoxyethane (DME), we observe that the average absolute errors in the density, self-diffusion coefficient, permittivity, viscosity, and surface tension are approximately 15% of the corresponding experimental values. Results compare favorably to all-atom CHARMM and OPLS-AA force fields, offering computational performance improvement of at least 80%. We further use TraPPE to predict the structure and properties of LiPF₆ salt in these solvents and their mixtures. EC and PC form complete solvation shells around Li⁺ ions, while the salt in DMC forms chain-like structures. In the poorest solvent, DME, LiPF₆ forms globular clusters despite DME's higher permittivity than DMC.

Toward Force Fields with Improved Base Stacking Descriptions

Recent DNA force fields indicate good performance in describing flexibility and structural stability of double-stranded B-DNA. However, it is not clear how accurately base stacking interactions are represented that are critical for simulating structure formation processes and conformational changes. Based on the equilibrium nucleoside association and base pair nicking, we find that the recent Tumuc1 force field improves the description of base stacking compared to previous state-of-the-art force fields. Nevertheless, base pair stacking is still overstabilized compared to experiment. We propose a rapid method to reweight calculated free energies of stacking upon force field modifications in order to generate improved parameters. A decrease of the Lennard-Jones attraction between nucleo-bases alone appears insufficient; however, adjustments in the partial charge distribution on base atoms could help to further improve the force field description of base stacking.

Molecular Insights into Cyclodextrin-Adamantane-Modified Copolymer Host-Guest Interactions

Supramolecular polymer flooding has great potential in solving the problems of difficult injection and low recovery in low-permeability polymer reservoirs. However, the self-assembly mechanism of supramolecular polymers is not yet to be fully understood at the molecular level. In this work, molecular dynamics simulations were used to explore the formation of cyclodextrin and adamantane-modified supramolecular polymer hydrogels; the self-assembly mechanism was summarized; and the effect of concentration on the oil displacement index was evaluated. The assembly mechanism of supramolecular polymers can be attributed to the "node-rebar-cement" mode of action. At the same time, Na⁺ can form intermolecular and intramolecular salt bridges with supramolecular polymers, and together with the "node-rebar-cement" mode of action, the supramolecular polymers can form a more compact 3D network structure. When the polymer concentration was increased, especially up to its critical association concentration (CAC), the association increased significantly. Besides, the construction of a 3D network was promoted, which results in a higher viscosity. This work investigated the assembly process of supramolecular polymers from the molecular scale and explained its mechanism of action, which makes up for the deficiencies of other research methods and provides a theoretical basis for screening out functional units that can be used for the supramolecular polymer assembly.

Development of Deep Potentials of Molten MgCl2-NaCl and MgCl2-KCl Salts Driven by Machine Learning

Molten MgCl2-based chlorides have emerged as potential thermal storage and heat transfer materials due to high thermal stabilities and lower costs. In this work, deep potential molecular dynamics (DPMD) simulations by a method combination of the first principle, classical molecular dynamics, and machine learning are performed to systemically study the relationships of structures and thermophysical properties of molten MgCl2-NaCl (MN) and MgCl2-KCl (MK) eutectic salts at the temperature range of 800-1000 K. The densities, radial distribution functions, coordination numbers, potential mean forces, specific heat capacities, viscosities, and thermal conductivities of these two chlorides are successfully reproduced under extended temperatures by DPMD with a larger size (5.2 nm) and longer timescale (5 ns). It is concluded that the higher specific heat capacity of molten MK is originated from the strong potential mean force of Mg-Cl bonds, whereas the molten MN performs better in heat transfer due to the larger thermal conductivity and lower viscosity, attributed to the weak interaction between Mg and Cl ions. Innovatively, the plausibility and reliability of microscopic structures and macroscopic properties for molten MN and MK verify the extensibilities of these two deep potentials in temperatures, and these DPMD results also provide detailed technical parameters to the simulations of other formulated MN and MK salts.

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.

Calculation of the Transport and Relaxation Properties of the Ar···HCl van der Waals Complex Using a New Potential Energy Surface: Comparison of the Classical and Full Quantum Mechanical Kinetic Theory Results with Molecular Dynamics Simulations

The intermolecular potential energy surface (PES) of the Ar···HCl complex was calculated at the RCCSD(T)/aug-cc-pvQz-BF level of theory. The obtained potential was expanded in terms of Legendre polynomials and fitted to a mathematical model. The fitting results are highly correlated with the ab initio PES data with SD = 5.9 × 10^-3 cm^-1 and average absolute deviation (AAD) = 4.0 × 10^-6 cm^-1. The interaction second virial coefficients (B₁₂) in the temperature range of 190-480 K were calculated by considering classical and first quantum corrections and compared with the available experimental data. A reasonable agreement with the experimental and calculated B₁₂ was obtained. The PES was also used to obtain the rovibrational energy levels, and the spectroscopic rovibrational constants were obtained. It was found that the D₀ values differ ∼2.25 cm^-1 from the experimental values of the ground rovibrational state. Furthermore, the obtained potential was used to calculate the transport and relaxation properties using full quantum close-coupling (CC) formalism and the classical kinetic theory methods based on the Mason-Monchik approximation (MMA). It was found that the deviation between MMA and CC calculations is increased with increasing the temperature due to the higher influence of the rotational degrees of freedom on the transport properties. Also, the contribution of the inelastic (off-diagonal) transitions for diffusion coefficient is higher than the viscosity. Furthermore, the classical molecular dynamics simulations were performed using LJ(12,6) and Vashishta models, to calculate the interaction diffusion and viscosity coefficients, and compared with the results of the full quantum CC calculations. The obtained results confirm that the Vashishta model is better fitted to the ab initio potentials and is more accurate than LJ(12,6) in calculation of the diffusion coefficients.

On the Behavior of the Ethylene Glycol Components of Polydisperse Polyethylene Glycol PEG200

Molecular dynamics (MD) simulations are reported for [polyethylene glycol (PEG)200], a polydisperse mixture of ethylene glycol oligomers with an average molar weight of 200 g·mol^-1. As a first step, available force fields for describing ethylene glycol oligomers were tested on how accurately they reproduced experimental properties. They were found to all fall short on either reproducing density, a static property, or the self-diffusion coefficient, a dynamic property. Discrepancies with the experimental data increased with the increasing size of the tested ethylene glycol oligomer. From the available force fields, the optimized potential for liquid simulation (OPLS) force field was used to further investigate which adjustments to the force field would improve the agreement of simulated physical properties with experimental ones. Two parameters were identified and adjusted, the (HO)-C-C-O proper dihedral potential and the polarity of the hydroxy group. The parameter adjustments depended on the size of the ethylene glycol oligomer. Next, PEG200 was simulated with the OPLS force field with and without modifications to inspect their effects on the simulation results. The modifications to the OPLS force field significantly decreased hydrogen bonding overall and increased the propensity of intramolecular hydrogen bond formation at the cost of intermolecular hydrogen bond formation. Moreover, some of the tri- and more so tetraethylene glycol formed intramolecular hydrogen bonds between the hydroxy end groups while still maintaining strong intramolecular interactions with the ether oxygen atoms. These observations allowed the interpretation of the obtained RDFs as well as structural properties such as the average end-to-end distances and the average radii of gyration. The MD simulations with and without the modifications showed no evidence of preferential association of like-oligomers to form clusters nor any evidence of long-range ordering such as a side-by-side stacking of ethylene glycol oligomers. Instead, the simulation results support the picture of PEG200 being a random mixture of its ethylene glycol oligomer components. Finally, additional MD simulations of a binary mixture of tri-and hexaethylene glycol with the same average molar weight as PEG200 revealed very similar structural and physical properties as for PEG200.

Design of CO2 Thickeners and Role of Aromatic Rings in Enhanced Oil Recovery Using Molecular Dynamics

Oligomers of PDMS (M1), polyFast (M2), modified PVEE (M3 and M4), and two new molecules with cyclic cores (M5 and M6) were studied to understand their ability to thicken the sc-CO2 at 377 K and 55 MPa, without any cosolvent. It was observed that PDMS and polyFast behaved in the known ways. PDMS does not improve the viscosity of the system without a cosolvent and PolyFast enhances the viscosity by a large margin. M3 and M4 also have not improved the viscosity significantly even with the introduction of a styrene component, but which has improved their solubilities in the fluid. M5 and M6, however, are observed to have enhanced the viscosity similar to that of polyFast due to their structural advantage and π-π interactions between the molecules. These molecules were also tested for their synthesizability, and their synthesis is found to be moderately easy.