Self-diffusion coefficient of bulk and confined water: a critical review of classical molecular simulation studies

On the temperature dependence of the density of states of liquids at low energies

We report neutron-scattering measurements of the density of states (DOS) of water and liquid Fomblin in a wide range of temperatures. In the liquid phase, we confirm the presence of a universal low-energy linear scaling of the experimental DOS as a function of the frequency, g ( ω ) = a ( T ) ω , which persists at all temperatures. The low-frequency scaling of the DOS exhibits a sharp jump at the melting point of water, below which the standard Debye's law, g ( ω ) ∝ ω 2 , is recovered. On the contrary, in Fomblin, we observe a continuous transition between the two exponents reflecting its glassy dynamics, which is confirmed by structure measurements. More importantly, in both systems, we find that the slope a(T) grows with temperature following an exponential Arrhenius-like form, a ( T ) ∝ exp ( - ⟨ E ⟩ / T ) . We confirm this experimental trend using molecular dynamics simulations and show that the prediction of instantaneous normal mode (INM) theory for a(T) is in qualitative agreement with the experimental data.

Universality in the Structure and Dynamics of Water under Lipidic Mesophase Soft Nanoconfinement

Water under soft nanoconfinement features physical and chemical properties fundamentally different from bulk water; yet, the multitude and specificity of confining systems and geometries mask any of its potentially universal traits. Here, we advance in this quest by resorting to lipidic mesophases as an ideal nanoconfinement system, allowing inspecting the behavior of water under systematic changes in the topological and geometrical properties of the confining medium, without altering the chemical nature of the interfaces. By combining Terahertz absorption spectroscopy experiments and molecular dynamics simulations, we unveil the presence of universal laws governing the physics of nanoconfined water, recapitulating the data collected at varying levels of hydration and nanoconfinement topologies. This geometry-independent universality is evidenced by the existence of master curves characterizing both the structure and dynamics of simulated water as a function of the distance from the lipid-water interface. Based on our theoretical findings, we predict a parameter-free law describing the amount of interfacial water against the structural dimension of the system (i.e., the lattice parameter), which captures both the experimental and numerical results within the same curve, without any fitting. Our results offer insight into the fundamental physics of water under soft nanoconfinement and provide a practical tool for accurately estimating the amount of nonbulk water based on structural experimental data.

Electrokinetic properties of NaCl solution via molecular dynamics simulations with scaled-charge electrolytes

Scaling ionic charges has become an alternative to polarizable force fields for representing indirect charge transfer effects in molecular simulations. In our work, we apply molecular dynamics simulations to investigate the properties of NaCl aqueous solutions in homogeneous and confined media. We compare classical integer- and scaled-charge force fields for the ions. In the bulk, we validate the force fields by computing equilibrium and transport properties and comparing them with experimental data. Integer-charge ions overestimate dielectric saturation and ionic association. Both force fields present an excess in ion-ion correlation, which leads to a deviation in the ionic conductivity at higher ionic strengths. Negatively charged quartz is used to simulate the confinement effect. Electrostatic interactions dominate counter-ion adsorption. Full-charge ions have stronger and more defined adsorption planes. We obtain the electroosmotic mobility of the solution by combining the shear plane location from non-equilibrium simulations with the ionic distribution from equilibrium simulations. From the Helmholtz-Smoluchowski equation, the zeta potential and the streaming potential coupling coefficient are computed. From an atomic-scale perspective, our molecular dynamics simulations corroborate the hypothesis of maximum packing of the Stern layer, which results in a stable and non-zero zeta potential at high salinity. The scaled-charge model representation of both properties is in excellent qualitative and quantitative agreement with experimental data. With our work, we demonstrate how useful and precise simple scaled-charge models for electrolytes can be to represent complex systems, such as the electrical double layer.

Influence of the Water Model on the Structure and Interactions of the GPR40 Protein with the Lipid Membrane and the Solvent: Rigid versus Flexible Water Models

G protein-coupled receptors (GPCR) are responsible for modulating various physiological functions and are thus related to the pathophysiology of different diseases. Being potential therapeutic targets, multiple computational methodologies have been developed to analyze their behavior and interactions with other species. The solvent, on the other hand, has received much less attention. In this work, we analyzed the effect of four explicit water models on the structure and interactions of the GPR40 receptor in its apo form. We employed the rigid SPC/E and TIP4P models, and their flexible versions, the FBA/ϵ and TIP4P/ϵflex. We explored the structural changes and their correlation with some bulk dynamic properties of water. Our results showed an adverse effect on the conservation of the secondary structure of the receptor with all the models due to the breaking of the intramolecular hydrogen bond network, being more evident for the TIP4P models. Notably, all four models brought the receptor to states similar to the active one, modifying the intracellular part of the TM5 and TM6 domains in a "hinge" type movement, allowing the opening of the structure. Regarding the dynamic properties, the rigid models showed results comparable to those obtained in other studies on membrane systems. However, flexible models exhibit disparities in the molecular representation of systems. Surprisingly, the FBA/ϵ model improves the molecular picture of several properties, even though their agreement with bulk diffusion is poorer. These findings reinforce our idea that exploring other water models or improving the current ones, to better represent the membrane interface, can lead to a positive impact on the description of the signal transduction mechanisms and the search of new drugs by targeting these receptors.

Hierarchical Multicriteria Optimization of Molecular Models of Water

Many widely used molecular models of water are built from a single Lennard-Jones site on which three point charges are positioned, one negative and two positive ones. Models from that class, denoted LJ3PC here, are computationally efficient, but it is well known that they cannot represent all relevant properties of water simultaneously with good accuracy. Despite the importance of the LJ3PC water model class, its inherent limitations in simultaneously describing different properties of water have never been studied systematically. This task can only be solved by multicriteria optimization (MCO). However, due to its computational cost, applying MCO to molecular models is a formidable task. We have recently introduced the reduced units method (RUM) to cope with this problem. In the present work, we apply the RUM in a hierarchical scheme to optimize LJ3PC water models taking into account five objectives: the representation of vapor pressure, saturated liquid density, self-diffusion coefficient, shear viscosity, and relative permittivity. Of the six parameters of the LJ3PC models, five were varied; only the H-O-H bond angle, which is usually chosen based on physical arguments, was kept constant. Our hierarchical RUM-based approach yields a Pareto set that contains attractive new water models. Furthermore, the results give an idea of what can be achieved by molecular modeling of water with models from the LJ3PC class.

Atomic-Scale Insights into the Phase Behavior of Carbon Dioxide and Water from 313 to 573 K and 8 to 30 MPa

We performed molecular dynamics (MD) simulations of CO2 + H2O systems by employing widely used force fields (EPM2, TraPPE, and PPL models for CO2; SPC/E and TIP4P/2005 models for H2O). The phase behavior observed in our MD simulations is consistent with the coexistence lines obtained from previous experiments and SAFT-based theoretical models for the equations of state. Our structural analysis reveals a pronounced correlation between phase transitions and the structural orderliness. Specifically, the coordination number of Ow (oxygen in H2O) around other Ow significantly correlates with phase changes. In contrast, coordination numbers pertaining to the CO2 molecules show less sensitivity to the thermodynamic state of the system. Furthermore, our data indicate that a predominant number of H2O molecules exist as monomers without forming hydrogen bonds, particularly in a CO2-rich mixture, signaling a breakdown in the hydrogen bond network's orderliness, as evidenced by a marked decrease in tetrahedrality. These insights are crucial for a deeper atomic-level understanding of phase behaviors, contributing to the well-grounded design of CO2 injection under high-pressure and high-temperature conditions, where an atomic-scale perspective of the phase behavior is still lacking.

Determination of self-diffusion coefficients in mixtures with benchtop 13C NMR spectroscopy via polarization transfer

Nuclear magnetic resonance (NMR) is an established method to determine self-diffusion coefficients in liquids with high precision. The development of benchtop NMR spectrometers makes the method accessible to a wider community. In most cases, 1H NMR spectroscopy is used to determine self-diffusion coefficients due to its high sensitivity. However, especially when using benchtop NMR spectrometers for the investigation of complex mixtures, the signals in 1H NMR spectra can overlap, hindering the precise determination of self-diffusion coefficients. In 13C NMR spectroscopy, the signals of different compounds are generally well resolved. However, the sensitivity of 13C NMR is significantly lower than that of 1H NMR spectroscopy leading to very long measurement times, which makes diffusion coefficient measurements based on 13C NMR practically infeasible with benchtop NMR spectrometers. To circumvent this problem, we have combined two known pulse sequences, one for polarization transfer from 1H to the 13C nuclei (PENDANT) and one for the measurement of diffusion coefficients (PFG). The new method (PENPFG) was used to measure the self-diffusion coefficients of three pure solvents (acetonitrile, ethanol and 1-propanol) as well as in all their binary mixtures and the ternary mixture at various compositions. For comparison, also measurements of the same systems were carried out with a standard PFG-NMR routine on a high-field NMR instrument. The results are in good agreement and show that PENPFG is a useful tool for the measurement of the absolute value of the self-diffusion coefficients in complex liquid mixtures with benchtop NMR spectrometers.

Accurate Free Energies of Aqueous Electrolyte Solutions from Molecular Simulations with Non-polarizable Force Fields

Non-polarizable force fields fail to accurately predict free energies of aqueous electrolytes without compromising the predictive ability for densities and transport properties. A new approach is presented in which (1) TIP4P/2005 water and scaled charge force fields are used to describe the interactions in the liquid phase and (2) an additional Effective Charge Surface (ECS) is used to compute free energies at zero additional computational expense. The ECS is obtained using a single temperature-independent charge scaling parameter per species. Thereby, the chemical potential of water and the free energies of hydration of various aqueous salts (e.g., NaCl and LiCl) are accurately described (deviations less than 5% from experiments), in sharp contrast to calculations where the ECS is omitted (deviations larger than 20%). This approach enables accurate predictions of free energies of aqueous electrolyte solutions using non-polarizable force fields, without compromising liquid-phase properties.

Structure and self-diffusivity of mixed-cation electrolytes between neutral and charged graphene sheets

Graphene-based applications, such as supercapacitors or capacitive deionization, take place in an aqueous environment, and they benefit from molecular-level insights into the behavior of aqueous electrolyte solutions in single-digit graphene nanopores with a size comparable to a few molecular diameters. Under single-digit graphene nanoconfinement (smallest dimension <2 nm), water and ions behave drastically different than in the bulk. Most aqueous electrolytes in the graphene-based applications as well as in nature contain a mix of electrolytes. We study several prototypical aqueous mixed alkali-chloride electrolytes containing an equimolar fraction of Li/Na, Li/K, or Na/K cations confined between neutral and positively or negatively charged parallel graphene sheets. The strong hydration shell of small Li+ vs a larger Na+ or large K+ with weaker or weak hydration shells affects the interplay between the ions's propensity to hydrate or dehydrate under the graphene nanoconfinement and the strength of the ion-graphene interactions mediated by confinement-induced layered water. We perform molecular dynamics simulations of the confined mixed-cation electrolytes using the effectively polarizable force field for electrolyte-graphene systems and focused on a relation between the electrochemical adsorption and structural properties of the water molecules and ions and their diffusion behavior. The simulations show that the one-layer nanoslits have the biggest impact on the ions' adsorption and the water and ions' diffusion. The positively charged one-layer nanoslits only allow for Cl- adsorption and strengthen the intermolecular bonding, which along with the ultrathin confinement substantially reduces the water and Cl- diffusion. In contrast, the negatively charged one-layer nanoslits only allow for adsorption of weakly hydrated Na+ or K+ and substantially break up the non-covalent bond network, which leads to the enhancement of the water and Na+ or K+ diffusion up to or even above the bulk diffusion. In wider nanoslits, cations adsorb closer to the graphene surfaces than Cl-'s with preferential adsorption of a weakly hydrated cation over a strongly hydrated cation. The positive graphene charge has an intuitive effect on the adsorption of weakly hydrated Na+'s or K+'s and Cl-'s and a counterintuitive effect on the adsorption of strongly hydrated Li+'s. On the other hand, the negative surface charge has an intuitive effect on the adsorption of both types of cations and only mild intuitive or counterintuitive effects on the Cl- adsorption. The diffusion of water molecules and ions confined in the wider nanoslits is reduced with respect to the bulk diffusion, more for the positive graphene charge, which strengthened the intermolecular bonding, and less for the negative surface charge, which weakened the non-covalent bond network.

Anisotropic molecular diffusion in confinement II: A model for structurally complex particles applied to transport in thin ionic liquid films

HYPOTHESIS

Diffusion in confinement is an important fundamental problem with significant implications for applications of supported liquid phases. However, resolving the spatially dependent diffusion coefficient, parallel and perpendicular to interfaces, has been a standing issue and for objects of nanometric size, which structurally fluctuate on a similar time scale as they diffuse, no methodology has been established so far. We hypothesise that the complex, coupled dynamics can be captured and analysed by using a model built on the 2-dimensional Smoluchowski equation and systematic coarse-graining.

METHODS AND SIMULATIONS

For large, flexible species, a universal approach is offered that does not make any assumptions about the separation of time scales between translation and other degrees of freedom. The method is validated on Molecular Dynamics simulations of bulk systems of a family of ionic liquids with increasing cation sizes where internal degrees of freedom have little to major effects.

FINDINGS

After validation on bulk liquids, where we provide an interpretation of two diffusion constants for each species found experimentally, we clearly demonstrate the anisotropic nature of diffusion coefficients at interfaces. Spatial variations in the diffusivities relate to interface-induced structuring of the ionic liquids. Notably, the length scales in strongly confined ionic liquids vary consistently but differently at the solid-liquid and liquid-vapour interfaces.

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

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

Ice-Like Dynamics of Water Clusters

Understanding certain behaviors of water, e.g., its dynamics, is extremely important in various fields. Recently, using 1H nuclear magnetic resonance spectroscopy, we have identified a metastable state of water molecules, i.e., water clusters, in hydrophobic solvents in addition to dissolved water molecules and a small bulk water domain. However, the low abundance of water clusters made observing their dynamics challenging. In this study, the dynamics of water clusters in benzene-d6 were investigated by quasi-elastic neutron scattering measurements using the AGNES time-of-flight spectrometer of the Japan Research Reactor JRR-3. The diffusion dynamics of the hydrogen atoms were much slower than those of bulk water (with a self-diffusion coefficient of 1.15 × 10-9 m2/s at 273 K) and even slower than the upper-limit dynamics at the observable scale (10-10 m2/s). The dynamics of water clusters are slow, "like ice", even at 283-303 K, which is above the freezing point of water (273 K).

Using NMR diffusion data to validate MD models of disordered proteins: Test case of N-terminal tail of histone H4

MD simulations can provide uniquely detailed models of intrinsically disordered proteins (IDPs). However, these models need careful experimental validation. The coefficient of translational diffusion Dtr, measurable by pulsed field gradient NMR, offers a potentially useful piece of experimental information related to the compactness of the IDP's conformational ensemble. Here, we investigate, both experimentally and via the MD modeling, the translational diffusion of a 25-residue N-terminal fragment from histone H4 (N-H4). We found that the predicted values of Dtr, as obtained from mean-square displacement of the peptide in the MD simulations, are largely determined by the viscosity of the MD water (which has been reinvestigated as a part of our study). Beyond that, our analysis of the diffusion data indicates that MD simulations of N-H4 in the TIP4P-Ew water give rise to an overly compact conformational ensemble for this peptide. In contrast, TIP4P-D and OPC simulations produce the ensembles that are consistent with the experimental Dtr result. These observations are supported by the analyses of the 15N spin relaxation rates. We also tested a number of empirical methods to predict Dtr based on IDP's coordinates extracted from the MD snapshots. In particular, we show that the popular approach involving the program HYDROPRO can produce misleading results. This happens because HYDROPRO is not intended to predict the diffusion properties of highly flexible biopolymers such as IDPs. Likewise, recent empirical schemes that exploit the relationship between the small-angle x-ray scattering-informed conformational ensembles of IDPs and the respective experimental Dtr values also prove to be problematic. In this sense, the first-principle calculations of Dtr from the MD simulations, such as demonstrated in this work, should provide a useful benchmark for future efforts in this area.

Estimation of the ice melting point in molecular dynamics simulations based on the finite-size effects

Predicting the ice melting point using molecular dynamics (MD) simulations is nontrivial due to uncertainty associated with the stochastic nature of the simulation and effect of finite domain sizes on the simulated ice-water phase transition. We developed a method based on the percolation theory to make use of the finite size effects to allow determination of a unique critical phase transition temperature as the melting point. The method involves construction of melting/freezing probability curves from multiple simulations with varying temperatures for different domain sizes. While the domain sizes affect the apparent melting/freezing probability and hence generate different curves with a wider probability distribution for a smaller size, the intersection of these curves is unique and locates the melting point. Based on MD simulations using the Tip4p/Ice water model, we tested and demonstrated the effectiveness of this method in locating the critical ice-water phase transition at a melting temperature of 268.78 K. Our analysis also showed that the apparent melting probability at this critical point is ∼0.69, not 0.5 assumed in the ad hoc method used previously. Our method, making no assumption about the system size, may provide a generic framework for analyzing phase transitions influenced by the finite size effects in MD simulations.

Trajectory-Extending Kinetic Monte Carlo Simulations to Evaluate Pure and Gas Mixture Diffusivities through a Dense Polymeric Membrane

With renewed interest in CO2 separations, carbon molecular sieving (CMS) membrane performance evaluation requires diffusion coefficients as inputs to have a reliable estimate of the permeability. An optimal material is desired to have both high selectivity and permeability. Gases diffusing through dense CMS and polymeric membranes experience extended subdiffusive regimes, which hinders reliable extraction of diffusion coefficients from mean squared displacement data. We improve the sampling of the diffusive landscape by implementing the trajectory-extending kinetic Monte Carlo (TEKMC) technique to efficiently extend molecular dynamics (MD) trajectories from ns to μs time scales. The obtained self-diffusion coefficient of pure CO2 in CMS membranes derived from a 6FDA/BPDA-DAM precursor polymer melt is found to linearly increase from 0.8-1.3 × 10-6 cm2 s-1 in the pressure range of 1-20 bar, which supports previous experimental findings. We also extended the TEKMC algorithm to evaluate the mixture diffusivities in binary mixtures to determine the permselectivity of CO2 in CH4 and N2 mixtures. The mixture diffusion coefficient of CO2 ranges from 1.3-7 × 10-6 cm2 s-1 in the binary mixture CO2/CH4, which is significantly higher than the pure gas diffusion coefficient. Robeson plot comparisons show that the permselectivity obtained from pure gas diffusion data is significantly lower than that predicted using mixture diffusivity data. Specifically, in the case of the CO2/N2 mixture, we find that using mixture diffusivities led to permselectivities lying above the Robeson limit highlighting the importance of using mixture diffusivity data for an accurate evaluation of the membrane performance. Combined with gas solubilities obtained from grand canonical Monte Carlo (GCMC) simulations, our work shows that simulations with the TEKMC method can be used to reliably evaluate the performance of materials for gas separations.

Anisotropic molecular diffusion in confinement I: Transport of small particles in potential and density gradients

HYPOTHESIS

Diffusion in confinement is an important fundamental problem with significant implications for applications of supported liquid phases. However, resolving the spatially dependent diffusion coefficient, parallel and perpendicular to interfaces, has been a standing issue. In the vicinity of interfaces, density fluctuations as a consequence of layering locally impose statistical drift, which impedes the analysis of spatially dependent diffusion coefficients even further. We hypothesise, that we can derive a model to spatially resolve interface-perpendicular diffusion coefficients based on local lifetime statistics with an extension to explicitly account for the effect of local drift using the Smoluchowski equation, that allows us to resolve anisotropic and spatially dependent diffusivity landscapes at interfaces.

METHODS AND SIMULATIONS

An analytic relation between local crossing times in system slices and diffusivity as well as an explicit term for calculating drift-induced systematic errors is presented. The method is validated on Molecular Dynamics simulations of bulk water and applied to simulations of water in slit pores.

FINDINGS

After validation on bulk liquids, we clearly demonstrate the anisotropic nature of diffusion coefficients at interfaces. Significant spatial variations in the diffusivities correlate with interface-induced structuring but cannot be solely attributed to the drift induced by local density fluctuations.

Molecular Modeling of Water-in-Salt Electrolytes: A Comprehensive Analysis of Polarization Effects and Force Field Parameters in Molecular Dynamics Simulations

Accurate modeling of highly concentrated aqueous solutions, such as water-in-salt (WiS) electrolytes in battery applications, requires proper consideration of polarization contributions to atomic interactions. Within the force field molecular dynamics (MD) simulations, the atomic polarization can be accounted for at various levels. Nonpolarizable force fields implicitly account for polarization effects by incorporating them into their van der Waals interaction parameters. They can additionally mimic electron polarization within a mean-field approximation through ionic charge scaling. Alternatively, explicit polarization description methods, such as the Drude oscillator model, can be selectively applied to either a subset of polarizable atoms or all polarizable atoms to enhance simulation accuracy. The trade-off between simulation accuracy and computational efficiency highlights the importance of determining an optimal level of accounting for atomic polarization. In this study, we analyze different approaches to include polarization effects in MD simulations of WiS electrolytes, with an example of a Na-OTF solution. These approaches range from a nonpolarizable to a fully polarizable force field. After careful examination of computational costs, simulation stability, and feasibility of controlling the electrolyte properties, we identify an efficient combination of force fields: the Drude polarizable force field for salt ions and non-polarizable models for water. This cost-effective combination is sufficiently flexible to reproduce a broad range of electrolyte properties, while ensuring simulation stability over a relatively wide range of force field parameters. Furthermore, we conduct a thorough evaluation of the influence of various force field parameters on both the simulation results and technical requirements, with the aim of establishing a general framework for force field optimization and facilitating parametrization of similar systems.

The influence of force fields on the structure and dynamics of water confined in ZIF-8 from atomistic simulations

The complexity of modeling flexible crystals, such as ZIF-8, mainly stems from the handling of intramolecular interactions. Numerous force fields have been proposed in the literature to describe the interactions between atoms in ZIF-8. We employ seven force fields to examine the structure and dynamic behavior of water molecules confined in ZIF-8, with the aim of investigating the impact of force fields on simulation results. Various structural characterization methods consistently indicate that the choice of different force fields has quantitative effects but no qualitative effects on the structural characteristics of confined water. Additionally, the force fields do not impact the qualitative description of the diffusion mechanism. Both mean-square displacement and van Hove autocorrelation function reveal two characteristic movements of water molecules diffusing in ZIF-8: a short-time intra-cavity hopping process and a long-time inter-cavity hopping process. However, the framework flexibility is found to play a crucial role in determining the order of spatial arrangement and local structure, self-diffusion coefficient and reorientational dynamics of confined water. Specifically, the DREIDING force field gives rise to an unrealistic stiff framework, enhancing the order of spatial arrangement and diminishing the local ordered structure of confined water. Meanwhile, it results in much slower translational and reorientational dynamics. Hence, the general DREIDING force field cannot be considered for providing a quantitative description of the water structure and dynamics.

Origin of the Hydrophobic Behaviour of Hydrophilic CeO2

The nature of the hydrophobicity found in rare-earth oxides is intriguing. The CeO2 (100) surface, despite its strongly hydrophilic nature, exhibits hydrophobic behaviour when immersed in water. In order to understand this puzzling and counter-intuitive effect we performed a detailed analysis of the confined water structure and dynamics. We report here an ab-initio molecular dynamics simulation (AIMD) study which demonstrates that the first adsorbed water layer, in immediate contact with the hydroxylated CeO2 surface, generates a hydrophobic interface with respect to the rest of the liquid water. The hydrophobicity is manifested in several ways: a considerable diffusion enhancement of the confined liquid water as compared with bulk water at the same thermodynamic condition, a weak adhesion energy and few H-bonds above the hydrophobic water layer, which may also sustain a water droplet. These findings introduce a new concept in water/rare-earth oxide interfaces: hydrophobicity mediated by specific water patterns on a hydrophilic surface.

Diffusion Dynamics of Water and Ethanol in Graphene Oxide

We utilized the momentum transfer (Q)-dependence of quasi-elastic neutron scattering (QENS) to measure the dynamics of water and ethanol confined in graphene oxide (GO) powder or membranes at different temperatures and in different orientations. We found reduced diffusivities (up to 30% in the case of water) and a depression of dynamic transition temperatures. While water showed near Arrhenius behavior with an almost bulk-like activation barrier in a temperature range of 280-310 K, the diffusivity of ethanol showed little temperature dependence. For both water and ethanol, we found evidence for immobile and mobile fractions of the confined liquid. The mobile fraction exhibited jump diffusion, with a jump length consistent with the expected average spacing of hydroxide groups in the GO surfaces. From anisotropy measurements, we found weak anisotropy in the diffusivity of the mobile species and in the fraction and geometry of immobile species.

Structure and self-diffusivity of alkali-halide electrolytes in neutral and charged graphene nanochannels

Understanding the microscopic behaviour of aqueous electrolyte solutions in graphene-based ultrathin nanochannels is important in nanofluidic applications such as water purification, fuel cells, and molecular sensing. Under extreme confinement (<2 nm), the properties of water and ions differ drastically from those in the bulk phase. We studied the structural and diffusion behaviour of prototypical aqueous solutions of electrolytes (LiCl, NaCl, and KCl) confined in both neutral and positively-, and negatively-charged graphene nanochannels. We performed molecular dynamics simulations of the solutions in the nanochannels with either one, two- or three-layer water structures using the effectively polarisable force field for graphene. We analysed the structure and intermolecular bond network of the confined solutions along with their relation to the self-diffusivity of water and ions. The simulations show that Na and K cations can more easily rearrange their solvation shells under the graphene nanoconfinement and adsorb on the graphene surfaces or dissolve in the confinement-induced layered water than the Li cation. The negative surface charge together with the presence of ions orient water molecules with hydrogens towards the graphene surfaces, which in turn weakens the intermolecular bond network. The one-layer nanochannels have the biggest effect on the water structure and intermolecular bonding as well as on the adsorption of ions with only co-ions entering these nanochannels. The self-diffusivity of confined water is strongly reduced with respect to the bulk water and decreases with diminishing nanochannel heights except for the negatively-charged one-layer nanochannel. The self-diffusivity of ions also decreases with the reducing the nanochannel heights except for the self-diffusivity of cations in the negatively-charged one-layer nanochannel, evidencing cooperative diffusion of confined water and ions. Due to the significant break-up of the intermolecular bond network in the negatively-charged one-layer nanochannel, self-diffusion coefficients of water and cations exceed those for the two- and three-layer nanochannels and become comparable to the bulk values.

Functionalized carbon nanocones performance in water harvesting

In this work, we investigate the water capture process for functionalized carbon nanocones (CNCs) through molecular dynamic simulations in the following three scenarios: a single CNC in contact with a reservoir containing liquid water, a single CNC in contact with a water vapor reservoir, and a combination of more than one CNC in contact with vapor. We found that water flows through the nanocones when in contact with the liquid reservoir if the nanocone tip presents hydrophilic functionalization. In contact with steam, we observed the formation of droplets at the base of the nanocone only when hydrophilic functionalization is present. Then, water flows through in a linear manner, a process that is more efficient than that in the liquid reservoir regime. The scalability of the process is tested by analyzing the water flow through more than one nanocone. The results suggest that the distance between the nanocones is a fundamental ingredient for the efficiency of water harvesting.

NMR Investigation of Water in Salt Crusts: Insights from Experiments and Molecular Simulations

The evaporation of water from bare soil is often accompanied by the formation of a layer of crystallized salt, a process that must be understood in order to address the issue of soil salinization. Here, we use nuclear magnetic relaxation dispersion measurements to better understand the dynamic properties of water within two types of salt crusts: sodium chloride (NaCl) and sodium sulfate (Na₂SO₄). Our experimental results display a stronger dispersion of the relaxation time T₁ with frequency for the case of sodium sulfate as compared to sodium chloride salt crusts. To gain insight into these results, we perform molecular dynamics simulations of salt solutions confined within slit nanopores made of either NaCl or Na₂SO₄. We find a strong dependence of the value of the relaxation time T₁ on pore size and salt concentration. Our simulations reveal the complex interplay between the adsorption of ions at the solid surface, the structure of water near the interface, and the dispersion of T₁ at low frequency, which we attribute to adsorption-desorption events.

Molecular modeling and simulation of aqueous solutions of alkali nitrates

A set of molecular models for the alkali nitrates (LiNO3, NaNO3, KNO3, RbNO3, and CsNO3) in aqueous solutions is presented and used for predicting the thermophysical properties of these solutions with molecular dynamics simulations. The set of models is obtained from a combination of a model for the nitrate anion from the literature with a set of models for the alkali cations developed in previous works of our group. The water model is SPC/E and the Lorentz–Berthelot combining rules are used for describing the unlike interactions. This combination is shown to yield fair predictions of thermophysical and structural properties of the studied aqueous solutions, namely the density, the water activity and the mean ionic activity coefficient, the self-diffusion coefficients of the ions, and radial distribution functions, which were studied at 298 K and 1 bar; except for the density of the solutions of all five nitrates and the activity properties of solutions of NaNO3, which were also studied at 333 K. For calculating the water the activity and the mean ionic activity coefficient, the OPAS ( osmotic pressure for the activity of selvents) method was applied. The new models extend an ion model family for the alkali halides developed in previous works of our group in a consistent way.

Size and Quality of Quantum Mechanical Data Set for Training Neural Network Force Fields for Liquid Water

Molecular dynamics simulations have been used in different scientific fields to investigate a broad range of physical systems. However, the accuracy of calculation is based on the model considered to describe the atomic interactions. In particular, ab initio molecular dynamics (AIMD) has the accuracy of density functional theory (DFT) and thus is limited to small systems and a relatively short simulation time. In this scenario, Neural Network Force Fields (NNFFs) have an important role, since they provide a way to circumvent these caveats. In this work, we investigate NNFFs designed at the level of DFT to describe liquid water, focusing on the size and quality of the training data set considered. We show that structural properties are less dependent on the size of the training data set compared to dynamical ones (such as the diffusion coefficient), and a good sampling (selecting data reference for the training process) can lead to a small sample with good precision.

Dynamics of Aqueous Electrolyte Solutions: Challenges for Simulations

This Perspective article focuses on recent simulation work on the dynamics of aqueous electrolytes. It is well-established that full-charge, nonpolarizable models for water and ions generally predict solution dynamics that are too slow in comparison to experiments. Models with reduced (scaled) charges do better for solution diffusivities and viscosities but encounter issues describing other dynamic phenomena such as nucleation rates of crystals from solution. Polarizable models show promise, especially when appropriately parametrized, but may still miss important physical effects such as charge transfer. First-principles calculations are starting to emerge for these properties that are in principle able to capture polarization, charge transfer, and chemical transformations in solution. While direct ab initio simulations are still too slow for simulations of large systems over long time scales, machine-learning models trained on appropriate first-principles data show significant promise for accurate and transferable modeling of electrolyte solution dynamics.

Atmospheric water harvesting using functionalized carbon nanocones

In this work, we propose a method to harvest liquid water from water vapor using carbon nanocones. The condensation occurs due to the presence of hydrophilic sites at the nanocone entrance. The functionalization, together with the high mobility of water inside nanostructures, leads to a fast water flow through the nanostructure. We show using molecular dynamics simulations that this device is able to collect water if the surface functionalization is properly selected.

Three-Dimensional Confinement of Water: H2O Exhibits Long-Range (>50 nm) Structure while D2O Does Not

Water is the liquid of life thanks to its three-dimensional adaptive hydrogen (H)-bond network. Confinement of this network may lead to dramatic structural changes influencing chemical and physical transformations. Although confinement effects occur on a <1 nm length scale, the upper length scale limit is unknown. Here, we investigate 3D-confinement over lengths scales ranging from 58-140 nm. By confining water in zwitterionic liposomes of different sizes and measuring the change in H-bond network conformation using second harmonic scattering (SHS), we determined long-range confinement effects in light and heavy water. D₂O displays no detectable 3D-confinement effects <58 nm (<3 × 10⁶ D₂O molecules). H₂O is distinctly different. The vesicle enclosed inner H-bond network has a different conformation compared to the outside network and the SHS response scales with the volume of the confining space. H₂O displays confinement effects over distances >100 nm (>2 × 10⁷ H₂O molecules).

Comprehensive Review on the Degradation Chemistry and Toxicity Studies of Functional Materials

In recent decades there has been growing interest of material chemists in the successful development of functional materials for drug delivery, tissue engineering, imaging, diagnosis, theranostic, and other biomedical applications with advanced nanotechnology tools. The efficacy and safety of functional materials are determined by their pharmacological, toxicological, and immunogenic effects. It is essential to consider all degradation pathways of functional materials and to assess plausible intermediates and final products for quality control. This review provides a brief insight into chemical degradation mechanisms of functional materials like oxidation, photodegradation, and physical and enzymatic degradation. The intermediates and products of degradation were confirmed with analytical methods such as proton nuclear magnetic resonance (¹H NMR), gel permeation chromatography (GPC), UV-vis spectroscopy (UV-vis), infrared spectroscopy (IR), differential scanning calorimetry (DSC), mass spectroscopy, and other sophisticated analytical methods. These analytical methods are also used for regulatory, quality control, and stability purposes in industry. The assessment of degradation is important to predetermine the behavior of functional materials in specific storage conditions and can be relevant to their behavior during in vivo applications. Another important aspect is the evaluation of the toxicity of functional materials. Toxicity can be accessed with various methods using in vitro, in vivo, ex vivo, and in silico models. In vitro cell culture methods are used to determine mitochondrial damage, reactive oxygen species, stress responses, and cellular toxicity. In vitro cellular toxicity can be measured by MTT assay, LDH leakage assay, and hemolysis. In vivo studies are performed using various animal models involving zebrafish, rodents (mice and rats), and nonhuman primates. Ex vivo studies are also used for efficacy and toxicity determinations of functional materials like ex vivo potency assay and precision-cut liver slice (PCLS) models. The in silico tools with computational simulations like quantitative structure-activity relationships (QSAR), pharmacokinetics (PK) and pharmacodynamics (PD), dose and time response, and quantitative cationic-activity relationships ((Q)CARs) are used for prediction of the toxicity of functional materials. In this review, we studied the principle methods used for degradation studies, different degradation pathways, and mechanisms of functional material degradation with prototype examples. We discuss toxicity assessments with different toxicity approaches used for estimation of the safety and efficacy of functional materials.

Usefulness of conventional glass ionomer cements in an environment of insufficient moisture exclusion

PURPOSE

Moisture exclusion while treating dental caries can be challenging, and the glass ionomer cements (GICs) used for these procedures are susceptible to water. Few studies have examined the effects of the powder/liquid ratio (PLR) on the physical properties of GICs exposed to water. In this study, the hardness and thickness of the water-susceptible surface layer of three GICs were evaluated.

METHODS

Three conventional GICs were mixed in increasing PLRs, and hardness over time was measured under conditions of no water exposure, distilled water exposure, and saliva exposure. Furthermore, the thickness of the water-susceptible layer for each GIC was determined.

RESULTS

A water-susceptible layer of approximately 250 μm was evident for all GICs, and the thickness decreased with increasing PLR. GIC hardness increased with increasing PLR in conditions without water for all GIC types. Furthermore, the removal of the water-susceptible layer restored the physical properties of each GIC.

CONCLUSION

Overall, the results indicate that conventional GIC restoration with the removal of the water-susceptible surface layer is a feasible strategy for treating dental caries in individuals for whom exclusion of moisture can be difficult.

Connection between water's dynamical and structural properties: Insights from ab initio simulations

SignificanceFirst-principles calculations, which explicitly account for the electronic structure of matter, can shed light on the molecular structure and dynamics of water in its supercooled state. In this work, we use density functional theory, which relies on a functional to describe electronic exchange and correlations, to evaluate which functional best describes the temperature evolution of bulk water transport coefficients. We also assess the validity of the Stokes-Einstein relation for all the functionals in the temperature range studied, and explore the link between structure and dynamics. Based on these results, we show how transport coefficients can be computed from structural descriptors, which require shorter simulation times to converge, and we point toward strategies to develop better functionals.

Adsorption Free Energy of Cellulose Nanocrystal on Water-Oil Interface

To investigate the amphiphilicity of cellulose, a series of molecular dynamics simulations were performed with a cellulose nanocrystal and a water-octane interfacial system. Assuming that the axis of cellulose is parallel to the water-octane interface, the freedoms of motion of the nanocrystal were restricted to two, the distance from the interface and the orientation around the axis. The mean force and the mean torque on the nanocrystal were evaluated with sufficiently long simulation at each crystal configuration, and their numerical integration gave a smooth free energy surface as the potential of mean force. The cellulose sample used here was found to be much more hydrophilic than oleophilic with the free energy difference ΔFw→o=318 kcal/mol. Three adsorption states with local minimum of adsorption free energy are distinguished in the free energy surface-the direct contact type which is similar to previously reported one, the hydrophilic-surface/water/octane type where a thin water layer is sandwiched between the surface and the octane phase, and the oleophilic/water/octane type where a thin water layer also exists. Water molecules in these water layers contribute to stabilize the adsorption states by taking a special orientational order and slow self-diffusion.

Diffusion characteristics of water molecules in a lamellar structure formed by triblock copolymers

The distribution and diffusion of water molecules are playing important roles in determining self-assembly and transport properties of polymeric systems. Small-angle neutron scattering (SANS) experiments and molecular dynamics (MD) simulation have been applied to understand the distribution of water molecules and their dynamics in the lamellar membrane formed by Pluronic L62 block copolymers. Penetration of water molecules into the polyethylene oxide (PEO) layers of the membranes has been estimated using scattering length density (SLD) profiles obtained from SANS measurements, which agree well with the molecular distribution observed from MD simulations. The water diffusion coefficient at different regions of the lamellar membrane was further investigated using MD simulation. The diffusion characteristic shows a transition from normal to anomalous diffusion as the position of the water molecule changes from the bulk to PEO and to the polypropylene oxide (PPO) layer. We find that water molecules within the PEO or PPO layers follow subdiffusive dynamics, which can be interpreted by the model of fractional Brownian motion.

Structure and dynamics of a water/methanol mixture confined in zeolitic imidazolate framework ZIF-8 from atomistic simulations

A classical atomistic simulation study is reported for the microscopic structure and dynamics of a water/methanol mixture confined in flexible nanoporous zeolitic imidazolate framework ZIF-8. Both the radial density distribution and vivid two-dimensional density profile demonstrate that methanol molecules can roughly be viewed as "embedded" between two layers of water molecules to form a "sandwich" structure. The reason for the formation of such a specific structure is explained based on the hydrogen-bonding state and the strength of various hydrogen bonds. The investigation of guest molecular diffusion shows that the self-diffusion coefficient of confined water is generally one to two orders of magnitude smaller than that of bulk water. In addition, the dependence of the self-diffusion coefficient on loading is non-monotonic: the self-diffusion coefficient firstly shows a significant increase and then decreases at higher loading. Moreover, both the structure and dynamics of the hydrogen bond (HB) network of confined water molecules are investigated in a spatially resolved manner. The results indicate that both the HB structure and dynamics of water molecules near the ZIF-8 surface deviate significantly from those of bulk water. However, while water molecules located at the pore center are relatively similar to bulk water molecules with respect to the HB structure, they exhibit strong slowdown in HB dynamics when compared with bulk water. This simulation study elucidates in detail the structural and dynamical properties of a water/methanol mixture in nanoscopic ZIF-8 confinement, which is expected to provide a deep insight into the role of porous fillers, such as ZIF-8, in improving the performance of the dehydration of alcohols via pervaporation and other related processes.

Using Computationally-Determined Properties for Machine Learning Prediction of Self-Diffusion Coefficients in Pure Liquids

The ability to predict transport properties of liquids quickly and accurately will greatly improve our understanding of fluid properties both in bulk and complex mixtures, as well as in confined environments. Such information could then be used in the design of materials and processes for applications ranging from energy production and storage to manufacturing processes. As a first step, we consider the use of machine learning (ML) methods to predict the diffusion properties of pure liquids. Recent results have shown that Artificial Neural Networks (ANNs) can effectively predict the diffusion of pure compounds based on the use of experimental properties as the model inputs. In the current study, a similar ANN approach is applied to modeling diffusion of pure liquids using fluid properties obtained exclusively from molecular simulations. A diverse set of 102 pure liquids is considered, ranging from small polar molecules (e.g., water) to large nonpolar molecules (e.g., octane). Self-diffusion coefficients were obtained from classical molecular dynamics (MD) simulations. Since nearly all the molecules are organic compounds, a general set of force field parameters for organic molecules was used. The MD methods are validated by comparing physical and thermodynamic properties with experiment. Computational input features for the ANN include physical properties obtained from the MD simulations as well as molecular properties from quantum calculations of individual molecules. Fluid properties describing the local liquid structure were obtained from center of mass radial distribution functions (COM-RDFs). Feature sensitivity analysis revealed that isothermal compressibility, heat of vaporization, and the thermal expansion coefficient were the most impactful properties used as input for the ANN model to predict the MD simulated self-diffusion coefficients. The MD-based ANN successfully predicts the MD self-diffusion coefficients with only a subset (2 to 3) of the available computationally determined input features required. A separate ANN model was developed using literature experimental self-diffusion coefficients as model targets. Although this second ML model was not as successful due to a limited number of data points, a good correlation is still observed between experimental and ML predicted self-diffusion coefficients.

Bayesian estimation of the hydroxyl radical diffusion coefficient at low temperature and high pressure from atomistic molecular dynamics

The hydroxyl radical is the primary reactive oxygen species produced by the radiolysis of water and is a significant source of radiation damage to living organisms. Mobility of the hydroxyl radical at low temperatures and/or high pressures is hence a potentially important factor in determining the challenges facing psychrophilic and/or barophilic organisms in high-radiation environments (e.g., ice-interface or undersea environments in which radiative heating is a potential heat and energy source). Here, we estimate the diffusion coefficient for the hydroxyl radical in aqueous solution using a hierarchical Bayesian model based on atomistic molecular dynamics trajectories in TIP4P/2005 water over a range of temperatures and pressures.

Structure and dynamics of nanoconfined water and aqueous solutions

This review is devoted to discussing recent progress on the structure, thermodynamic, reactivity, and dynamics of water and aqueous systems confined within different types of nanopores, synthetic and biological. Currently, this is a branch of water science that has attracted enormous attention of researchers from different fields interested to extend the understanding of the anomalous properties of bulk water to the nanoscopic domain. From a fundamental perspective, the interactions of water and solutes with a confining surface dramatically modify the liquid's structure and, consequently, both its thermodynamical and dynamical behaviors, breaking the validity of the classical thermodynamic and phenomenological description of the transport properties of aqueous systems. Additionally, man-made nanopores and porous materials have emerged as promising solutions to challenging problems such as water purification, biosensing, nanofluidic logic and gating, and energy storage and conversion, while aquaporin, ion channels, and nuclear pore complex nanopores regulate many biological functions such as the conduction of water, the generation of action potentials, and the storage of genetic material. In this work, the more recent experimental and molecular simulations advances in this exciting and rapidly evolving field will be reported and critically discussed.

Anisotropic Electrostatic Interactions in Coarse-Grained Water Models to Enhance the Accuracy and Speed-Up Factor of Mesoscopic Simulations

Water models with realistic physical–chemical properties are essential to study a variety of biomedical processes or engineering technologies involving molecules or nanomaterials. Atomistic models of water are constrained by the feasible computational capacity, but calibrated coarse-grained (CG) ones can go beyond these limits. Here, we compare three popular atomistic water models with their corresponding CG model built using finite-size particles such as ellipsoids. Differently from previous approaches, short-range interactions are accounted for with the generalized Gay–Berne potential, while electrostatic and long-range interactions are computed from virtual charges inside the ellipsoids. Such an approach leads to a quantitative agreement between the original atomistic models and their CG counterparts. Results show that a timestep of up to 10 fs can be achieved to integrate the equations of motion without significant degradation of the physical observables extracted from the computed trajectories, thus unlocking a significant acceleration of water-based mesoscopic simulations at a given accuracy.

Understanding the Stabilization of a Bulk Nanobubble: A Molecular Dynamics Analysis

Bulk nanobubbles (NBs) have received considerable attention because of their extensive potential applications, such as in ultrasound imaging and water management. Although multiple types of experimental evidence have supported the existence and stabilization of bulk NBs, the underlying mechanism remains unclear. This study numerically investigates the bulk NB stabilization with molecular dynamics (MD) methods: the all-atom (AA) MD simulation is used for NBs of several nanometers diameter; the coarse-grained (CG) MD simulation is for the NBs of about 100 nm. The NB properties are statistically obtained and analyzed, including the inner density, inner pressure, surface charge, interfacial hydrogen bond (HB), and gaseous diffusion. The results show that the gas inside an NB has ultrahigh density (tens of kilograms per cubic meter). A double-layer surface charge exists on the NB. The inner/outer layer is positively/negatively charged, and the electrostatic stress can counteract part of the surface tension. In addition, the interfacial HB is weakened by the interaction between gas and water molecules, causing less surface tension. The above features are beneficial to NB stabilization. The NB equilibrium radii solved by the interfacial mechanical equilibrium equation agree with the MD results, indicating that this equation can describe the force balance of an NB as small as several nanometers. Besides, supersaturation appears to be necessary for the NB thermodynamic equilibrium. Based on Henry's law and the ideal gas law, the theoretical analysis suggests that the stability of the NB thermodynamic equilibrium is conditional: the number of gas molecules in NBs should be more than half that dissolved in liquid. This study unravels a stabilized bulk NB's properties and discusses the NB equilibrium and stabilization mechanism, which will advance the understanding and application of bulk NBs.

Systematic Comparison of the Structural and Dynamic Properties of Commonly Used Water Models for Molecular Dynamics Simulations

Water is a unique solvent that is ubiquitous in biology and present in a variety of solutions, mixtures, and materials settings. It therefore forms the basis for all molecular dynamics simulations of biological phenomena, as well as for many chemical, industrial, and materials investigations. Over the years, many water models have been developed, and it remains a challenge to find a single water model that accurately reproduces all experimental properties of water simultaneously. Here, we report a comprehensive comparison of structural and dynamic properties of 30 commonly used 3-point, 4-point, 5-point, and polarizable water models simulated using consistent settings and analysis methods. For the properties of density, coordination number, surface tension, dielectric constant, self-diffusion coefficient, and solvation free energy of methane, models published within the past two decades consistently show better agreement with experimental values compared to models published earlier, albeit with some notable exceptions. However, no single model reproduced all experimental values exactly, highlighting the need to carefully choose a water model for a particular study, depending on the phenomena of interest. Finally, machine learning algorithms quantified the relationship between the water model force field parameters and the resulting bulk properties, providing insight into the parameter-property relationship and illustrating the challenges of developing a water model that can accurately reproduce all properties of water simultaneously.

Heterogeneous Microscopic Dynamics of Intruded Water in a Superhydrophobic Nanoconfinement: Neutron Scattering and Molecular Modeling

With their strong confining porosity and versatile surface chemistry, zeolitic imidazolate frameworks-including the prototypical ZIF-8-display exceptional properties for various applications. In particular, the forced intrusion of water at high pressure (∼25 MPa) into ZIF-8 nanopores is of interest for energy storage. Such a system reveals also ideal to study experimentally water dynamics and thermodynamics in an ultrahydrophobic confinement. Here, we report on neutron scattering experiments to probe the molecular dynamics of water within ZIF-8 nanopores under high pressure up to 38 MPa. In addition to an overall confinement-induced slowing down, we provide evidence for strong dynamical heterogeneities with different underlying molecular dynamics. Using complementary molecular simulations, these heterogeneities are found to correspond to different microscopic mechanisms inherent to vicinal molecules located in strongly adsorbing sites (ligands) and other molecules nanoconfined in the cavity center. These findings unveil a complex microscopic dynamics, which results from the combination of surface residence times and exchanges between the cavity surface and center.

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

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