Model Of Electrolyte Solutions Research Articles

Differentiable modeling and optimization of non-aqueous Li-based battery electrolyte solutions using geometric deep learning

Electrolytes play a critical role in designing next-generation battery systems, by allowing efficient ion transfer, preventing charge transfer, and stabilizing electrode-electrolyte interfaces. In this work, we develop a differentiable geometric deep learning (GDL) model for chemical mixtures, DiffMix, which is applied in guiding robotic experimentation and optimization towards fast-charging battery electrolytes. In particular, we extend mixture thermodynamic and transport laws by creating GDL-learnable physical coefficients. We evaluate our model with mixture thermodynamics and ion transport properties, where we show improved prediction accuracy and model robustness of DiffMix than its purely data-driven variants. Furthermore, with a robotic experimentation setup, Clio, we improve ionic conductivity of electrolytes by over 18.8% within 10 experimental steps, via differentiable optimization built on DiffMix gradients. By combining GDL, mixture physics laws, and robotic experimentation, DiffMix expands the predictive modeling methods for chemical mixtures and enables efficient optimization in large chemical spaces.

Predictive potentialities of the Quasi-Random Lattice model for electrolyte solutions, discussion and improvement strategies

This article focuses on the predictive potentialities of the Quasi-Random Lattice (QRL) model, developed for describing the activity behaviour of electrolytic solutions, and elaborates strategies for their improvement.First, the study critically discusses the computational-experimental procedure (previously published) for determining the QRL parameterization, whose convergence within few iterations is counterbalanced by known experimental issues concerning, in particular, the mean activity coefficient. An alternative procedure is proposed, that makes use of osmotic data at medium-high concentrations, so as to make QRL more interesting from a practical point of view.Second, the study explores the applicability of the model beyond the concentration ranges earlier considered. To this purpose, the solution density is evaluated in detail. Its thermodynamic relationship with the mean activity coefficient yields a parametric Abel Equation of the Second Kind valid in the medium-high range of concentrations. A further density equation is formulated, useful in the low-medium range, based on a classical power-series combined with appropriate analytical constraints to improve estimation and prediction methods.QRL theory, methods and procedures are applied to binary aqueous solutions at 25°C.

Molecular modeling and simulation of organic electrolyte solutions for lithium ion batteries.

Multi-criteria optimization is used for developing molecular models for ethylene carbonate (EC) and propylene carbonate (PC), organic solvents commonly used in Li-ion batteries. The molecular geometry and partial charges of the solvents are obtained from quantum mechanical calculations. Using a novel optimization strategy that combines systematic variations of the Lennard-Jones parameters with a reduced units approach, the models are fitted to experimental data on the liquid density, vapor pressure, relative permittivity, and self-diffusion coefficient. Since no experimental data for the self-diffusion coefficient of pure EC were available in the literature, they are measured in this work using a gradient-based nuclear magnetic resonance technique. For all pure component properties, excellent agreement between experiment and simulation is obtained. Moreover, the predictive capabilities of the new solvent models are assessed by comparison to experimental data for the liquid density and relative permittivity of mixtures of EC and PC. In addition, molecular models for the anions PF6-, BF4-, and ClO4- in solutions of their lithium electrolytes in PC are developed using experimental data on the solution densities. Finally, the self-diffusion coefficients of LiPF6 in PC and in aqueous solution are predicted and compared, showing that diffusion is much slower in the organic solution due to the formation of larger solvent shells around the ions. Furthermore, an analysis of the radial distribution functions in these solutions suggests that the ions have much less impact on the structure of the solvent PC than on water.

Cluster Formation Induced by Local Dielectric Saturation in Restricted Primitive Model Electrolytes.

Experiments using the Surface Force Apparatus (SFA) have found anomalously long-ranged charge-charge underscreening in concentrated salt solutions. Meanwhile, theory and simulations have suggested ion clustering to be a possible origin of this behavior. The popular Restricted Primitive Model of electrolyte solutions, in which the solvent is represented by a uniform relative dielectric constant, εr, is unable to resolve the anomalous underscreening seen in experiments. In this work, we modify the Restricted Primitive Model to account for local dielectric saturation within the ion hydration shell. The dielectric "constant" in our model locally decreases from the bulk value to a lower saturated value at the ionic surface. The parameters for the model are deduced so that typical salt solubilities are obtained. Our simulations for both bulk and slit geometries show that our model displays strong cluster formation and these give rise to long-ranged density correlations between charged surfaces, at distances similar to what has been observed in SFA measurements. An electrolyte model wherein the dielectric constant remains uniform does not display similar clusters, even with εr equal to the low saturated value at ion contact. Hence, the observed behaviors are not simply due to an enhanced Coulomb interaction. In the latter case, cluster growth is counteracted by long-ranged repulsions between like-charged ions within clusters; this is an effect that is considerably reduced when the dielectric response drop is local. Our results imply that long-ranged interactions in these systems are mainly due to cluster-cluster correlations, rather than large electrostatic screening lengths.

Minimal Coarse-Grained Models of Polar Solvent for Electrolytes: Stockmayer Versus Dumbbell.

This study explores the potential of the dumbbell solvent as a minimal model for understanding electrolyte solutions in polar solvents. Our investigation involves a comparative analysis of the dumbbell model and the Stockmayer model, focusing on ion solvation and ion-ion correlations. We examine electrolytes containing symmetric monovalent salts dissolved in polar solvents while varying the ion density and solvent polarity. Both models predict an augmented solvent coordination number around ions as the solvent polarity increases, with the dumbbell solvent displaying a more pronounced effect. Notably, radial distribution functions (RDFs) between solvent and ions yield differing trends; Stockmayer models exhibit a nonmonotonic relationship due to strong dipole-dipole interactions at higher polarity, while RDFs for ions and dumbbell solvents consistently rise. In response to increased solvent polarity, Stockmayer solvents within the ion's solvation shell undergo continuous dipole orientation shifts, whereas the dumbbell solvent predominantly adopts pointing-away dipole orientations, diminishing pointing-to orientations. This underscores the significance of the interplay between the solvent molecular orientation and dipole rotation. Both models qualitatively predict ion pairing and clustering behaviors across varying solvent dipole strengths and salt concentrations. The Stockmayer solvent generally provides stronger electrostatic screening than the dumbbell solvent due to its neglect of the coupling between molecular orientation and dipole rotation. What's more, at a high dipole moment regime, ion-ion correlations in Stockmayer solvent can become stronger with increasing dipole moment due to stronger solvent-solvent correlations. This study underscores the effectiveness of the dumbbell solvent model in systematically elucidating the fundamental principles governing electrolytes and offers potential applications in the rational design of electrolyte systems.

The Behavior of Phenolic Compounds from Apples during Simulated Gastrointestinal Digestion with Focus on Chlorogenic Acid.

The fate of phenolic compounds during digestion is important for their bioactive effects in the digestive tract. The aim was to study the various phenolic compounds occurring in the peel and flesh of apples in in vitro simulated gastrointestinal digestion, focusing on the behavior of chlorogenic acids. Additionally, the behavior of individual chlorogenic acids (chlorogenic, neochlorogenic, and cryptochlorogenic) was studied in models of simulated salivary, gastric, and intestinal fluid electrolyte solutions (SSF, SGF, SIF). At the end of the intestinal phase of the digestion of peel and flesh, the amount of recovered dihydrochalcones and flavonols increased or was similar to the amount in the gastric phase, which showed their stability. Anthocyanins and flavan-3-ols decreased, which suggests their biotransformation. Chlorogenic acid isomerized into neochlorogenic and cryptochlorogenic acid: chlorogenic acid from the peel into 22% and 41% of the isomers in the salivary and intestinal phases, respectively; chlorogenic acid from the flesh into 12% of the isomers in the intestinal phase. Similarly, chlorogenic acid isomerized in model solutions (20% and 26% of the isomers in SSF and SIF, respectively). Neochlorogenic and cryptochlorogenic acid isomerized in SSF and SIF into other two forms. They were all stable in SGF. For bioactive effects in the digestive tract, the biotransformation of chlorogenic acids should be considered.

Electrochemical Investigations of Ag and Bi in Choline Chloride-Ethylene Glycol DES Electrolyte

Electrodeposition for silver and bismuth is currently carried out in alkaline solutions, e.g., by use of cyanide, and by electroplating these metals, by themselves or together. The electroplated products have important uses, e.g., in semiconductors [1].Choline Chloride (ChCl)-Ethylene Glycol (EG) DES mixtures, often referred to as ethaline, have been shown to have superior electrochemical properties compared to many other DES systems [2]. This system is considered a green solvent [3]. In this work, the electrochemical behaviour of Ag and Bi in ethaline electrolyte has been investigated to obtain the necessary parameters to extract them by electrochemical methods, either separately or together, when both are present in the DES electrolyte. The presence of Cu and Sb in the electrolyte, has also been studied, and its effect in the metal obtained has been evaluated. Ethaline solutions were fabricated by mixing together ChCl and EG at 1:2 ChCl:EG molar ratio by stirring at 60 °C until a clear liquid was formed. Model electrolyte solutions were then produced by dissolving AgCl and BiCl3, as well as SbCl3 and CuCl2, in the DES. Electrochemical investigations were carried out at 60 °C by cyclic voltammetry (CV), chronoamperometry (CA) and potentiostatic electrolysis using a 3-electrode setup.The CVs obtained using Pt-wire or GC-rod as working electrodes in the DES with 10 mM Ag(I) and Bi(III), showed two distinguished peaks in the cathodic scan. The CV and CA results showed that the Bi deposition starts at approximately 0.15-0.20 V more cathodic than the Ag deposition. Two or more electrochemical signals were observed in the reverse anodic scan, correlating to the dissolution of the metals, alloys and possible electrolyte reactions. Example of CV curve obtained on a Pt wire at a scan rate of 200 mV/s is included.The results indicated that it could be possible to electrochemically extract only Ag or both Ag and Bi simultaneously, when present at identical concentrations in the DES electrolyte, by carefully choosing the deposition potential. This was confirmed after analysis of the cathodic deposits on Pt and stainless steel (316L) substrates by Scanning Electron Microscopy-Energy Dispersive Spectroscopy (SEM-EDS).Experiments with Sb(III) and Cu(II), in addition to Ag(I) and Bi(III) present in the DES electrolyte showed that the cathodic deposition of the different metals appears in the order Ag<Sb<Bi<Cu. Significant co-deposition might occur, enhanced by favourable alloy formation, when metallic elements may deposit at activities lower than 1. Still, at 10 mM of each of the four metal salts present in the DES electrolyte, it was possible to obtain deposits with one, two, three or four metals present, by choosing the proper cathodic deposition potential.AcknowledgementsThis project has received funding from the EU’s Horizon 2020 research and innovation program under Grant Agreement 815748. The content in this presentation reflects only the views of the authors. The European Commission is not responsible for any use that may be made of the information it contains.

Simulation Study of Li-Ion Batteries Considering the Porosity and Tortuosity of Separator

Lithium-ion batteries (Li-ion batteries) offer high energy and power densities, making them the most widely used battery technology for energy storage in various applications such as grid-scale, automotive, and electronic devices. One of the critical components of a Li-ion battery is the porous separator which can impair performance at high charge/discharge rates. Separator has a considerable influence on the transport of lithium ions. The structural properties of the separator, such as porosity and tortuosity can have a significant impact on heat generation and polarization of lithium concentration as well as the current density distribution inside the separator. The porosity of a porous separator is a well-defined feature that may be easily determined. In contrast, the tortuosity of separators, is more difficult to assess.To model and calculate the separator properties, in this study, the simulated structural separator was constructed by numerical analysis1 based on actual separator structure from Cryo-FIB-SEM. The numerical simulation of the ion-transport model for concentrated electrolyte solutions using the model developed by Newman et al2. Different structures of separators provided different behaviors at different charge/discharge rates. To evaluate overall battery performance, using the previously reported structural information3,4, lithium nickel manganese cobalt oxides (NCM), 1.0 M LiPF6 solution in EC-DEC solvent, and graphite were used for the cathode, electrolyte, and anode, respectively.This work simulated and compared three different separator structures: foam, non-woven fabric, and stretched structure with three different constant charging rate (C-rate) conditions (1 C, 5 C and 8 C). The calculation of porosity and tortuosity has been done for through-plane model. The higher C-rate will increase the heat generation significantly and affect the battery`s thermal behavior. The tortuosity and porosity have correlation on the effective ionic conductivity σeff = (ε/τ)*σ and effective diffusion coefficient Deff = (ε/τ)*D. Higher separator porosity can effectively increase the effective diffusion coefficient, hence improving mass transfer and reducing resistance. The separator with uniform porosity and smaller tortuosity showed smaller diffusion polarization because Li+ can be transported easily and uniformly in it, leading to lower heat generation even in high C-rate condition. The model developed in this study is intended to be valuable in understanding behavior of porous separators and optimizing the battery design.Acknowledgement: This research was carried out under the project (Grant Number JPMJMI21G4) supported by the JST-Mirai Program, Japan.

New Electrical Conductivity Model for Electrolyte Solutions Based on the Debye-Hückel-Onsager Theory.

A new electrical conductivity model is developed for unassociated electrolyte solutions based on the Debye-Hückel-Onsager theory. In this model, we assume that a single cation and a single anion with their crystallographic ionic radii are in a continuum medium of the solvent(s). We compare the predictions of the developed model with the experimental measurements of binary 1:1, 2:1, 1:2, 2:2, 1:3, 3:1, 2:3, 3:2, 3:3, 1:4, and 2:4 aqueous solutions in the temperature range 273.15-373.15 K. Our results are in good agreement with the experimental data. An extension of the model was formulated to incorporate ion pairing, and its effectiveness was evaluated across three essential systems: 2:2 aqueous sulfate solutions, ionic liquid-co-solvent systems, and NaCl-water-1,4-dioxane solutions. This adaptation demonstrated a strong correlation with experimental data, highlighting the broad applicability.

Application of the symmetric Poisson-Boltzmann theory to equilibrium thermodynamic properties of primitive model electrolyte mixtures

A symmetric Poisson-Boltzmann theory is applied to a primitive model electrolyte solution containing 7 different ion species. Only 7 coupled equations need to be solved for the mean electrostatic potential around the ions once the uncharged hard sphere radial distribution function is specified. Comparison is made with the individual activity and osmotic coefficients of a simulation study of a sea water mixture. Good overall agreement is found with the simulation results.

Mean ionic activity coefficient of associative electrolyte solutions: A comparison study

The performance of four implicit solvent models for associative and two models for non-associative electrolyte solutions has been compared and analyzed for the mean ionic activity coefficient (MIAC) of electrolytes in the solution. Two of these models for associative electrolyte solutions are based on a chemical approach (Fisher-Levin-Guillot-Guissani (FLGG) and Ebeling-Grigo (EG)), and one of them is based on the reference cavity approximation (Zhou-Yeh-Stell (ZYS)). The last one is based on the thermodynamic perturbation theory (Binding mean spherical approximation, BiMSA). Models without ion-pairing also consist of hard sphere (HS) contribution in addition to the electrostatic contribution from the Debye-Hückel (HS + DH) and the mean spherical approximation (HS + MSA) theories. To this aim, the models’ predictions are compared with the numerical solution of the Poisson-Boltzmann equation, the Monte Carlo simulations, and the experimental data. We have shown that considering the ion pairing results in a better agreement of the predicted MIAC against both simulations and experimental data of 2:2 electrolytes. We have also adjusted the ionic diameter and the distance between ion pairs to the MIAC experimental data and validated the estimated fractions of free ions with the electrical conductivity measurements. We have shown that the FLGG model captures the physics of the system more accurately compared to other models.

Thermodynamic modeling of aqueous lithium salt solutions with association electrolyte nonrandom two-liquid activity coefficient model

The high charge density of lithium ion and the resulting strong association phenomena make thermodynamic modeling of aqueous lithium electrolyte solutions extremely challenging. In this study, the association electrolyte nonrandom two-liquid activity coefficient model of Lin et al. (AIChE J. 2022, 68(2), e17422) is utilized to correlate and predict thermodynamic properties and solubility behavior of aqueous single electrolyte solutions of LiCl, LiBr, LiI, and LiNO3, and their mixed electrolyte solutions. Capturing self-association of water, cross-association of ion and water for hydration, and cross-association of cation and anion for ion-pairing, the association model accurately represents the literature experimental data up to saturation concentrations and at the temperature ranging from 263 K to 523 K. This study further investigated the effect of anions of the lithium salts, and re-confirmed that the order of solution non-ideality as LiI > LiBr > LiCl > LiNO3 because the anions with stronger association strengths are more likely to form ion pairs and thus lower the mean ionic activity coefficients.

The Contribution of the Ion-Ion and Ion-Solvent Interactions in a Molecular Thermodynamic Treatment of Electrolyte Solutions.

Developing molecular equations of state to treat electrolyte solutions is challenging due to the long-range nature of the Coulombic interactions. Seminal approaches commonly used are the mean spherical approximation (MSA) and the Debye-Hückel (DH) theory to account for ion-ion interactions and, often, the Born theory of solvation for ion-solvent interactions. We investigate the accuracy of the MSA and DH approaches using each to calculate the contribution of the ion-ion interactions to the chemical potential of NaCl in water, comparing these with newly computer-generated simulation data; the ion-ion contribution is isolated by selecting an appropriate primitive model with a Lennard-Jones force field to describe the solvent. A study of mixtures with different concentrations and ionic strengths reveals that the calculations from both MSA and DH theories are of similar accuracy, with the MSA approach resulting in marginally better agreement with the simulation data. We also demonstrate that the Born theory provides a good qualitative description of the contribution of the ion-solvent interactions; we employ an explicitly polar water model in these simulations. Quantitative agreement up to moderate salt concentrations and across the relevant range of temperature is achieved by adjusting the Born radius using simulation data of the free energy of solvation. We compute the radial and orientational distribution functions of the systems, thereby providing further insight on the differences observed between the theory and simulation. We thus provide rigorous benchmarks for use of the MSA, DH, and Born theories as perturbation approaches, which will be of value for improving existing models of electrolyte solutions, especially in the context of equations of state.

Current Trends in Predictive Methods and Electrolyte Equations of State.

Over the past 20–30 years, the development of thermodynamic models for electrolyte solutions has experienced remarkable progress. While in the first half of the 20th century, the thermodynamic models were essentially based on the continuum electrostatic approach, nowadays equations of state and predictive methods have been adapted to deal with electrolyte solutions. Given this panorama, in this mini-review, the recent advances in predictive methods and electrolyte equations of state are examined, as well as their performance in predicting activity coefficients and solid–liquid phase equilibrium data. Although this mini-review aims to shed light on the current progress in predictive methods and electrolyte equations of state, it also provides valuable references and information to the several models and theories that form the backbone of the thermodynamics of electrolyte solutions.

Proposing an Ultrapure Water Unit Coupled to an Existing Reverse Osmosis Desalination Plant and its Exergy Analysis

In this study, three desalination exergy analysis models including the Cerci et al. model (Model A), Drioli et al. model (Model B) and electrolyte solution model (Model C), were developed on an existing reverse osmosis (RO) desalination plant in Oman (Plant ALG). A modified ultrapure water (UPW) unit fed by Plant ALG has also been proposed (Plant A) based on the technology used in a UPW unit operated under the climate of Europe and fed by European river water (Plant B). The most suitable exergy model for characterizing the proposed UPW production plant was used. Model C was found to be the most proper model among its counterparts. It reflected the electrolytic behavior of the relevant streams and considered as the appropriate model. The major exergy destruction sites were also identified, and the exergy efficiency was calculated. The electro-de-ionization (EDI) and the RO unit were the highest exergy destructive components in Plant A.

Accounting for Ionic Strength in the Laliberte–Cooper Density Model for Electrolyte Solutions

Accounting for Ionic Strength in the Laliberte–Cooper Density Model for Electrolyte Solutions

Bridging atomistic simulations and thermodynamic hydration models of aqueous electrolyte solutions.

Chemical thermodynamic models of solvent and solute activities predict the equilibrium behavior of aqueous solutions. However, these models are semi-empirical. They represent micro-scale ion and solvent behaviors controlling the macroscopic properties using small numbers of parameters whose values are obtained by fitting to activities and other partial derivatives of the Gibbs energy measured for the bulk solutions. We have conducted atomistic simulations of aqueous electrolyte solutions (MgCl2 and CaCl2) to determine the parameters of thermodynamic hydration models. We have implemented a cooperative hydration model to categorize the water molecules in electrolyte solutions into different subpopulations. The value of the electrolyte-specific parameter, k, was determined from the ion-affected subpopulation with the lowest absolute value of the free energy of removing the water molecule. The other equilibrium constant parameter, K1, associated with the first degree of hydration, was computed from the free energy of hydration of hydrated clusters. The hydration number, h, was determined from a reorientation dynamic analysis of the water subpopulations compared to bulk-like behavior. The reparameterized models [R. H. Stokes and R. H. Robinson, J. Solution Chem. 2, 173 (1973) and Balomenos et al., Fluid Phase Equilib. 243, 29 (2006)] using the computed values of the parameters lead to the osmotic coefficients of MgCl2 solutions that are consistent with measurements. Such an approach removes the dependence on the availability of experimental data and could lead to aqueous thermodynamic models capable of estimating the values of solute and solvent activities as well as thermal and volumetric properties for a wide range of compositions and concentrations.

Effects of model tear proteins and topical ophthalmic formulations on evaporation inhibition and biophysical property of model tear lipid nanofilm in vitro

Biophysical property and water evaporation retardation through a lipid nanofilm can be altered by model tear protein and topical ophthalmic formulation. Evaporation rate and dynamic surface pressure were measured using a sessile drop technique. Water evaporations from 5 individual protein solutions, their mixture, and 6 ophthalmic formulations were quantified. Biophysical property and evaporation through model lipid nanofilms spread on model electrolyte solutions, tear protein solutions, and ophthalmic formulations were assessed. Model lipid nanofilms spread on electrolyte solution reduced evaporative fluxes by 43–60%. Evaporative fluxes from individual protein solutions without lipids were 3–19% lower than from electrolytes solution. Evaporative fluxes through lipid nanofilms were decreased by the presence of albumin or lactoferrin in solutions but increased by lysozyme and mucin. Evaporative fluxes from ophthalmic formulations were 10–43% lower than from electrolyte solution. Evaporations through lipid nanofilms spread on formulations were higher than through lipids on electrolyte solution. Model lipid nanofilms spread on Diquas appeared more rigid than on electrolyte solution but showed softening when spread on Refresh Mega-3. Some proteins and ophthalmic formulations altered model lipid nanofilms evaporative barriers. Ophthalmic formulation induced changes in biophysical property of model lipid nanofilms in vitro may suggest possible tear film destabilization in vivo.

Association‐based activity coefficient model for electrolyte solutions

AbstractThis work presents an association‐based activity coefficient model that explicitly considers the solution nonideality due to associations among ions and solvent species. Built upon the electrolyte nonrandom two‐liquid (eNRTL) model, the model greatly improves the accuracy of eNRTL model for strongly associating electrolyte solutions due to presence of ionic species with high surface charge density. The model successfully correlates mean ionic activity coefficients of 46 aqueous single‐salt systems from 10 cations and 5 anions at 298.15 K up to their solubility limits. With the ion‐specific association parameters identified, the model accurately predicts activity and osmotic coefficients for aqueous mixed‐salt systems at 298.15 K. The temperature dependence of the model results has also been examined at 273–373 K. With superior accuracy over a wide range of concentration and temperature, the model represents a major advancement over eNRTL model and has a great potential to be a next‐generation model for electrolyte solutions.

Toward a First-Principles Framework for Predicting Collective Properties of Electrolytes

Given the universal importance of electrolyte solutions, it is natural to expect that we have a nearly complete understanding of the fundamental properties of these solutions (e.g., the chemical potential) and that we can therefore explain, predict, and control the phenomena occurring in them. In fact, reality falls short of these expectations. But, recent advances in the simulation and modeling of electrolyte solutions indicate that it should soon be possible to make progress toward these goals. In this Account, we will discuss the use of first-principles interaction potentials based in quantum mechanics (QM) to enhance our understanding of electrolyte solutions. Specifically, we will focus on the use of quantum density functional theory (DFT) combined with molecular dynamics simulation (DFT-MD) as the foundation for our approach. The overarching concept is to understand and accurately reproduce the balance between local or short-ranged (SR) structural details and long-range (LR) correlations, allowing the prediction of the thermodynamics of both single ions in solution as well as the collective interactions characterized by activity/osmotic coefficients. In doing so, relevant collective motions and driving forces characterized by chemical potentials can be determined.In this Account, we will make the case that understanding electrolyte solutions requires a faithful QM representation of the SR nature of the ion-ion, ion-water, and water-water interactions. However, the number of molecules that is required for collective behavior makes the direct application of high-level QM methods that contain the best SR physics untenable, making methods that balance accuracy and efficiency a practical goal. Alternatives such as continuum solvent models (CSMs) and empirically based classical molecular dynamics have been extensively employed to resolve this problem but without yet overcoming the fundamental issue of SR accuracy. We will demonstrate that accurately describing the SR interaction is imperative for predicting both intrinsic properties, namely, at infinite dilution, and collective properties of electrolyte solutions.DFT has played an important role in our understanding of condensed phase systems, e.g., bulk liquid water, the air-water interface, ions in bulk, and at the air-water interface. This approach holds huge promise to provide benchmark calculations of electrolyte solution properties that will allow for the development and improvement of more efficient methods, as well as an enhanced understanding of fundamental phenomena. However, the standard protocol using the generalized gradient approximation with van der Waals (vdW) correction requires improvement in order to achieve a high level of quantitative accuracy. Simply simulating with higher level DFT functionals may not be the best route considering the significant computational cost. Alternative methods of incorporating information from higher levels of QM should be explored; e.g., using force matching techniques on small clusters, where high level benchmark calculations are possible, to develop ideal correction terms to the DFT functional is a promising possibility. We argue that DFT with statistical mechanics is becoming an increasingly useful framework enabling the prediction of collective electrolyte properties.