In situ investigation of water on MXene interfaces.

A continuum of water populations can exist in nanoscale layered materials, which impacts transport phenomena relevant for separation, adsorption, and charge storage processes. Quantification and direct interrogation of water structure and organization are important in order to design materials with molecular-level control for emerging energy and water applications. Through combining molecular simulations with ambient-pressure X-ray photoelectron spectroscopy, X-ray diffraction, and diffuse reflectance infrared Fourier transform spectroscopy, we directly probe hydration mechanisms at confined and nonconfined regions in nanolayered transition-metal carbide materials. Hydrophobic (K+) cations decrease water mobility within the confined interlayer and accelerate water removal at nonconfined surfaces. Hydrophilic cations (Li+) increase water mobility within the confined interlayer and decrease water-removal rates at nonconfined surfaces. Solutes, rather than the surface terminating groups, are shown to be more impactful on the kinetics of water adsorption and desorption. Calculations from grand canonical molecular dynamics demonstrate that hydrophilic cations (Li+) actively aid in water adsorption at MXene interfaces. In contrast, hydrophobic cations (K+) weakly interact with water, leading to higher degrees of water ordering (orientation) and faster removal at elevated temperatures.

Investigation of Multilayered Structures of Ionic Liquids on Graphite and Platinum Using Atomic Force Microscopy and Molecular Simulations.

The molecular-level orientation and structure of ionic liquids (ILs) at liquid-solid interfaces are significantly different than in the bulk. The interfacial ordering influences both IL properties, such as dielectric constants and viscosity, and their efficacy in devices, such as fuel cells and electrical capacitors. Here, we report the layered structures of four ILs on unbiased, highly ordered pyrolytic graphite (HOPG) and Pt(111) surfaces, as determined by atomic force microscopy. The ILs investigated are 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([emim][Tf2N]), 1-ethyl-3-methylimidazolium perfluorobutylsulfonate ([emim][C4F9SO3]), 7-methyl-1,5,7-triazabicyclo[4.4.0]dec-5-ene bis(trifluoromethylsulfonyl)imide ([MTBD][Tf2N]), and 7-methyl-1,5,7-triazabicyclo[4.4.0]dec-5-ene perfluorobutylsulfonate ([MTBD][C4F9SO3]). Molecular dynamics simulations provide complementary information on the position and orientation of the ions. These ILs form a cation layer at the IL-solid interface, followed by a layer of anions. [Emim]+ and [MTBD]+ have similar orientations at the surface, but [MTBD]+ forms a thinner layer compared to [emim]+ on both HOPG and Pt(111). In addition, [Tf2N]- shows stronger interactions with Pt(111) surfaces than [C4F9SO3]-.

Tuning Potential Functions to Host-Guest Binding Data.

Software to more rapidly and accurately predict protein-ligand binding affinities is of high interest for early-stage drug discovery, and physics-based methods are among the most widely used technologies for this purpose. The accuracy of these methods depends critically on the accuracy of the potential functions that they use. Potential functions are typically trained against a combination of quantum chemical and experimental data. However, although binding affinities are among the most important quantities to predict, experimental binding affinities have not to date been integrated into the experimental data set used to train potential functions. In recent years, the use of host-guest complexes as simple and tractable models of binding thermodynamics has gained popularity due to their small size and simplicity, relative to protein-ligand systems. Host-guest complexes can also avoid ambiguities that arise in protein-ligand systems such as uncertain protonation states. Thus, experimental host-guest binding data are an appealing additional data type to integrate into the experimental data set used to optimize potential functions. Here, we report the extension of the Open Force Field Evaluator framework to enable the systematic calculation of host-guest binding free energies and their gradients with respect to force field parameters, coupled with the curation of 126 host-guest complexes with available experimental binding free energies. As an initial application of this novel infrastructure, we optimized generalized Born (GB) cavity radii for the OBC2 GB implicit solvent model against experimental data for 36 host-guest systems. This refitting led to a dramatic improvement in accuracy for both the training set and a separate test set with 90 additional host-guest systems. The optimized radii also showed encouraging transferability from host-guest systems to 59 protein-ligand systems. However, the new radii are significantly smaller than the baseline radii and lead to excessively favorable hydration free energies (HFEs). Thus, users of the OBC2 GB model currently may choose between GB cavity radii that yield more accurate binding affinities and GB cavity radii that yield more accurate HFEs. We suspect that achieving good accuracy on both will require more far-reaching adjustments to the GB model. We note that binding free-energy calculations using the OBC2 model in OpenMM gain about a 10× speedup relative to corresponding explicit solvent calculations, suggesting a future role for implicit solvent absolute binding free-energy (ABFE) calculations in virtual compound screening. This study proves the principle of using host-guest systems to train potential functions that are transferrable to protein-ligand systems and provides an infrastructure that enables a range of applications.

Development and Benchmarking of Open Force Field 2.0.0: The Sage Small Molecule Force Field.

We introduce the Open Force Field (OpenFF) 2.0.0 small molecule force field for drug-like molecules, code-named Sage, which builds upon our previous iteration, Parsley. OpenFF force fields are based on direct chemical perception, which generalizes easily to highly diverse sets of chemistries based on substructure queries. Like the previous OpenFF iterations, the Sage generation of OpenFF force fields was validated in protein-ligand simulations to be compatible with AMBER biopolymer force fields. In this work, we detail the methodology used to develop this force field, as well as the innovations and improvements introduced since the release of Parsley 1.0.0. One particularly significant feature of Sage is a set of improved Lennard-Jones (LJ) parameters retrained against condensed phase mixture data, the first refit of LJ parameters in the OpenFF small molecule force field line. Sage also includes valence parameters refit to a larger database of quantum chemical calculations than previous versions, as well as improvements in how this fitting is performed. Force field benchmarks show improvements in general metrics of performance against quantum chemistry reference data such as root-mean-square deviations (RMSD) of optimized conformer geometries, torsion fingerprint deviations (TFD), and improved relative conformer energetics (ΔΔE). We present a variety of benchmarks for these metrics against our previous force fields as well as in some cases other small molecule force fields. Sage also demonstrates improved performance in estimating physical properties, including comparison against experimental data from various thermodynamic databases for small molecule properties such as ΔHmix, ρ(x), ΔGsolv, and ΔGtrans. Additionally, we benchmarked against protein-ligand binding free energies (ΔGbind), where Sage yields results statistically similar to previous force fields. All the data is made publicly available along with complete details on how to reproduce the training results at https://github.com/openforcefield/openff-sage.

Pregnant women's knowledge of obesity and ideal weight gain in pregnancy, and health behaviours of pregnant women and their partners.

We conducted a survey among a convenience sample of 149 women and their partners (n = 136) attending antenatal services in the Canberra Hospital in 2010. Over one-third (39%) of women and 63.6% of their partners were overweight/obese, and 69.2% of women had not received advice from their caregiver on their weight. Pregnant women and their partners' health behaviours including smoking, and fruit and vegetable intake were strongly correlated (P ≤ 0.01). Pregnant women require targeted advice on their weight, ideal weight gain and impact of these on pregnancy.

Investigating the Accuracy of Water Models through the Van Hove Correlation Function.

We present molecular-simulation-based calculations of the Van Hove correlation function (VHF) of water using multiple modeling approaches: classical molecular dynamics with simple three-site nonpolarizable models, with a polarizable model, and with a reactive force field; density functional tight-binding molecular dynamics; and ab initio molecular dynamics. Due to the many orders of magnitude difference in the computational cost of these approaches, we investigate how small and short the simulations can be while still yielding sufficiently accurate and interpretable results for the VHF. We investigate the accuracy of the different models by comparing them to recently published inelastic X-ray scattering measurements of the VHF. We find that all of the models exhibit qualitative agreement with the experiments, and in some models and for some properties, the agreement is quantitative. This work lays the foundation for future simulation approaches to calculating the VHF for aqueous solutions in bulk and under nanoconfinement.

Towards Molecular Simulations that are Transparent, Reproducible, Usable By Others, and Extensible (TRUE).

Systems composed of soft matter (e.g., liquids, polymers, foams, gels, colloids, and most biological materials) are ubiquitous in science and engineering, but molecular simulations of such systems pose particular computational challenges, requiring time and/or ensemble-averaged data to be collected over long simulation trajectories for property evaluation. Performing a molecular simulation of a soft matter system involves multiple steps, which have traditionally been performed by researchers in a "bespoke" fashion, resulting in many published soft matter simulations not being reproducible based on the information provided in the publications. To address the issue of reproducibility and to provide tools for computational screening, we have been developing the open-source Molecular Simulation and Design Framework (MoSDeF) software suite. In this paper, we propose a set of principles to create Transparent, Reproducible, Usable by others, and Extensible (TRUE) molecular simulations. MoSDeF facilitates the publication and dissemination of TRUE simulations by automating many of the critical steps in molecular simulation, thus enhancing their reproducibility. We provide several examples of TRUE molecular simulations: All of the steps involved in creating, running and extracting properties from the simulations are distributed on open-source platforms (within MoSDeF and on GitHub), thus meeting the definition of TRUE simulations.

Ion Pairing Controls Physical Properties of Ionic Liquid-Solvent Mixtures.

The dissolution of room temperature ionic liquids (RTILs) in organic solvents has been shown to enhance ion dynamics. We previously used molecular dynamics (MD) simulations to study the ionic liquid ([BMIM+][Tf2N-]) in 22 unique solvents over a wide range of concentrations. By screening over a large parameter space, we reached several conclusions: (1) ion diffusivity increases monotonically as a function of increasing ionic liquid composition, (2) pure solvent diffusivity strongly correlates with ion diffusivity, and (3) conductivity predicted by the Nernst-Einstein (NE) equation has a maximum at intermediate compositions of ionic liquid. Building off this work, we now utilize the same parameter space to study the structure of ([BMIM+][Tf2N-]) solvated in organic solvents. We explore ion correlations through a number of structural and thermodynamic properties, including liquid densities, pair correlation functions, ion pairing and ion caging lifetimes, and free energy calculations. Through these analyses, we find that some solvents are much more effective at screening ion-ion interactions than others and that these differences impact the ion dynamics in these mixtures. In general, the strong pairing of ionic liquids negatively impacts transport properties, but some solvents can robustly screen these interactions, resulting in greatly enhanced ion dynamics. These results uncover trends connecting ionic liquid structure to transport, which can help in the design of new electrolytes for energy storage devices, such as electrical double layer capacitors and batteries.

Scalable Screening of Soft Matter: A Case Study of Mixtures of Ionic Liquids and Organic Solvents.

Room-temperature ionic liquids (RTILs) are a class of organic salts that are liquid at room temperature. Their physiochemical properties, including low vapor pressure and wide electrochemical stability window, have driven their use as electrolytes in many electrochemical applications; however, the slow transport properties of many RTILs have limited their utility in some applications. This issue is often mitigated by solvating ionic liquids in neutral organic solvents. To date, however, solvent interactions have only been explored for a small number of solvents, particularly acetonitrile and propylene carbonate, at only a few compositions. In this work, we use molecular dynamics simulations in the context of a computational screening approach to study mixtures of ionic liquids in many different solvents at a range of concentrations. Building on prior work, we again find that ionic liquid diffusivity increases monotonically with greater solvent concentration. In contrast to prior work, we find that pure solvent diffusivity, not polarity, is the most influential solvent property on mixture behavior. We also explore the concentration dependence of ionic conductivity and find maxima at intermediate concentrations. Experimental conductivity measurements, inspired by the computational screening study, support this observation with qualitatively consistent results. These results can further guide the selection of solvents for electrochemical applications of RTILs.

Identifying Water-Anion Correlated Motion in Aqueous Solutions through Van Hove Functions.

Electrolyte solutions are ubiquitous in materials in daily use and in biological systems. However, the understanding of their molecular and ionic dynamics, particularly those of their correlated motions, are elusive despite extensive experimental, theoretical, and numerical studies. Here we report the real-space observations of the molecular/ionic-correlated dynamics of aqueous salt (NaCl, NaBr, and NaI) solutions using the Van Hove functions obtained by high-resolution inelastic X-ray scattering measurement and molecular dynamics simulation. Our results directly depict the distance-dependent dynamics of aqueous salt solutions on the picosecond time scale and identify the changes in the anion-water correlations. This study demonstrates the capability of the real-space Van Hove function analysis to describe the local correlated dynamics in aqueous salt solutions.

Computational Insights into Materials and Interfaces for Capacitive Energy Storage.

Supercapacitors such as electric double-layer capacitors (EDLCs) and pseudocapacitors are becoming increasingly important in the field of electrical energy storage. Theoretical study of energy storage in EDLCs focuses on solving for the electric double-layer structure in different electrode geometries and electrolyte components, which can be achieved by molecular simulations such as classical molecular dynamics (MD), classical density functional theory (classical DFT), and Monte-Carlo (MC) methods. In recent years, combining first-principles and classical simulations to investigate the carbon-based EDLCs has shed light on the importance of quantum capacitance in graphene-like 2D systems. More recently, the development of joint density functional theory (JDFT) enables self-consistent electronic-structure calculation for an electrode being solvated by an electrolyte. In contrast with the large amount of theoretical and computational effort on EDLCs, theoretical understanding of pseudocapacitance is very limited. In this review, we first introduce popular modeling methods and then focus on several important aspects of EDLCs including nanoconfinement, quantum capacitance, dielectric screening, and novel 2D electrode design; we also briefly touch upon pseudocapactive mechanism in RuO2. We summarize and conclude with an outlook for the future of materials simulation and design for capacitive energy storage.

Solvent Polarity Governs Ion Interactions and Transport in a Solvated Room-Temperature Ionic Liquid.

We explore the influence of the solvent dipole moment on cation-anion interactions and transport in 1-butyl-3-methyl-imidazolium bis(trifluoromethylsulfonyl), [BMIM+][Tf2N-]. Free energy profiles derived from atomistic molecular dynamics (MD) simulations show a correlation of the cation-anion separation and the equilibrium depth of the potential of mean force with the dipole moment of the solvent. Correlations of the ion diffusivity with the dipole moment and the concentration of the solvent were further demonstrated by classical MD simulations. Quasi-elastic neutron scattering experiments with deuterated solvents reveal a complex picture of nanophase separation into the ionic liquid-rich and solvent-rich phases. The experiment corroborates the trend of concentration- and dipole moment-dependent enhancement of ion mobility by the solvent, as suggested by the simulations. Despite the considerable structural complexity of ionic liquid-solvent mixtures, we can rationalize and generalize the trends governing ionic transport in these complex electrolytes.