Deep Eutectic Solvents: Molecular Simulations with a First-Principles Polarizable Force Field

Force Fields for Deep Eutectic Mixtures: Application to Structure, Thermodynamics and 2D-Infrared Spectroscopy

Parametrizing energy functions for ionic systems can be challenging. Here, the total energy function for an eutectic system consisting of water, SCN-, K+ and acetamide is improved vis-a-vis experimentally measured properties. Given the importance of electrostatic interactions, two different types of models are considered: the first (model M0) uses atom-centered multipole whereas the other two (models M1 and M2) are based on fluctuating minimal distributed charges (fMDCM) that respond to geometrical changes of SCN-. The Lennard-Jones parameters of the anion are adjusted to best reproduce experimentally known hydration free energies and densities, which are matched to within a few percent for the final models irrespective of the electrostatic model. Molecular dynamics simulations of the eutectic mixtures with varying water content (between 0 and 100%) yield radial distribution functions and frequency correlation functions for the CN-stretch vibration. Comparison with experiments indicates that models based on fMDCM are considerably more consistent than those using multipoles. Computed viscosities from models M1 and M2 are within 30% of measured values and their change with increasing water content is consistent with experiments. This is not the case for model M0.

Efficient Molecular Dynamics Simulations of Deep Eutectic Solvents with First-Principles Accuracy Using Machine Learning Interatomic Potentials

In recent years, deep eutectic solvents emerged as highly tunable and ecofriendly alternatives to common organic solvents and liquid electrolytes. In the present work, the ability of machine learning (ML) interatomic potentials for molecular dynamics (MD) simulations of these liquids is explored, showcasing a trained neural network potential for a 1:2 ratio mixture of choline chloride and urea (reline). Using the ML potentials trained on density functional theory data, MD simulations for large systems of thousands of atoms and nanosecond-long time scales are feasible at a fraction of the computational cost of the target first-principles simulations. The obtained structural and dynamical properties of reline from MD simulations using our machine learning models are in good agreement with the first-principles MD simulations and experimental results. Running a single MD simulation is highlighted as a general shortcoming of typical first-principles studies if the dynamic properties are investigated. Furthermore, velocity cross-correlation functions are employed to study the collective dynamics of the molecular components in reline.

Long-Lived Weak Ion Pairs in Ionic Liquids: An Insight from All-Atom Molecular Dynamics Simulations

The microstructure and local dynamics of ions in room-temperature ionic liquids (RTILs) have drawn a lot of attention due to their extensive potential applications in numerous fields. It is well-known that the widely used definitions of ion pairs (IPs) cannot reflect the full picture of RTILs. In this study, we find a universal residence time (τ_MR), which is regardless of the number of counterions in the first solvation shell in RTILs. Inspired by this, we propose a weak IP (WIP) model from a spatiotemporal perspective and demonstrate that the WIPs are long-lived and that their lifetimes obey a log-normal distribution, which is different from the literature. In addition, the electrostatic interactions are the main factors in the formation of WIPs, and the reorientations of ions are vital to the ruptures of WIPs. This research provides a new perspective for understanding the microstructural and dynamical properties of RTILs.

Molecular Dynamics Simulation Study of the Far-Infrared Spectrum of a Deep Eutectic Solvent

Deep eutectic solvents (DESs) are similar to ionic liquids (IL) in terms of physicochemical properties and technical uses. In ILs, far-infrared (FIR) spectroscopy has been utilized to reveal ionic interactions and even to produce a signature of the strengthening of the cation-anion hydrogen bond. However, for the situation of the DES, where the mixing of a salt and a molecular species makes the interplay between multiple intermolecular interactions even more complex, a full investigation of FIR spectra is still absent. In this work, the FIR spectrum of the DES, often referred to as ethaline, which is a 1:2 mixture of choline chloride and ethylene glycol, is calculated using classical molecular dynamics (MD) simulations and compared to experimental data. To explore the induced dipole effect on the computed FIR spectrum, MD simulations were run with both nonpolarizable and polarizable models. The calculation satisfactorily reproduces the position of the peak at ∼110 cm^-1 and the bandwidth seen in the experimental FIR spectrum of ethaline. The MD simulations show that the charge current is the most important contributor to the FIR spectrum, but the cross-correlation between the charge current and dipole reorientation also plays a role in the polarizable model. The dynamics of the chloride-ethylene glycol correlation span a wide frequency range, with a maximum at ∼150 cm^-1, but it participates as a direct mechanism only in the charge current-dipole reorientation cross-term. Anion correlations, whose dynamics are regulated via correlation with both ethylene glycol and choline, make the most significant contribution to the charge current mechanism. The MD simulations were also utilized to investigate the effect on the FIR spectrum of adding water to the DES and switching to a 1:1 composition.

Ion Correlation in Choline Chloride-Urea Deep Eutectic Solvent (Reline) from Polarizable Molecular Dynamics Simulations

In recent years, deep eutectic solvents (DESs) emerged as highly tunable and environmentally friendly alternatives to common ionic liquids and organic solvents. In this work, a polarizable model based on the CHARMM Drude polarizable force field is developed for a 1:2 ratio mixture of choline chloride/urea (reline) DES. To successfully reproduce the structure of the liquid as compared to first-principles molecular dynamics simulations, a damping factor was introduced to correct the observed over-binding between the chloride and the hydrogen bonding site of choline. Investigated radial distributions reveal the formation of hydrogen bonds between all the constituents of reline and similar interactions for chloride and urea's oxygen atoms, which could contribute to the melting point depression of the mixture. Predicted dynamic properties from our polarizable force field are in good agreement with experiments, showing significant improvements over nonpolarizable models. Similar to some ionic liquids, an oscillatory behavior in the velocity autocorrelation function of the anion is visible, which can be interpreted as a rattling motion of the lighter anion surrounded by the heavier cations. The obtained results for ionic conductivity of reline show some degree of correlated ion motion in this DES. However, a joint diffusion of ion pairs cannot be observed during the simulations.

Computer Simulations of Deep Eutectic Solvents: Challenges, Solutions, and Perspectives

Deep eutectic solvents (DESs) are one of the most rapidly evolving types of solvents, appearing in a broad range of applications, such as nanotechnology, electrochemistry, biomass transformation, pharmaceuticals, membrane technology, biocomposite development, modern 3D-printing, and many others. The range of their applicability continues to expand, which demands the development of new DESs with improved properties. To do so requires an understanding of the fundamental relationship between the structure and properties of DESs. Computer simulation and machine learning techniques provide a fruitful approach as they can predict and reveal physical mechanisms and readily be linked to experiments. This review is devoted to the computational research of DESs and describes technical features of DES simulations and the corresponding perspectives on various DES applications. The aim is to demonstrate the current frontiers of computational research of DESs and discuss future perspectives.

Bulk and interfacial nanostructure and properties in deep eutectic solvents: Current perspectives and future directions

Deep eutectic solvents (DESs) are a tailorable class of solvents that are rapidly gaining scientific and industrial interest. This is because they are distinct from conventional molecular solvents, inherently tuneable via careful selection of constituents, and possess many attractive properties for applications, including catalysis, chemical extraction, reaction media, novel lubricants, materials chemistry, and electrochemistry. DESs are a class of solvents composed solely of hydrogen bond donors and acceptors with a melting point lower than the individual components and are often fluidic at room temperature. A unique feature of DESs is that they possess distinct bulk liquid and interfacial nanostructure, which results from intra- and inter-molecular interactions, including coulomb forces, hydrogen bonding, van der Waals interactions, electrostatics, dispersion forces, and apolar-polar segregation. This nanostructure manifests as preferential spatial arrangements of the different species, and exists over several length scales, from molecular- to nano- and meso-scales. The physicochemical properties of DESs are dictated by structure-property relationships; however, there is a significant gap in our understanding of the underlying factors which govern their solvent properties. This is a major limitation of DES-based technologies, as nanostructure can significantly influence physical properties and thus potential applications. This perspective provides an overview of the current state of knowledge of DES nanostructure, both in the bulk liquid and at solid interfaces. We provide definitions which clearly distinguish DESs as a unique solvent class, rather than a subset of ILs. An appraisal of recent work provides hints towards trends in structure-property relationships, while also highlighting inconsistencies within the literature suggesting new research directions for the field. It is hoped that this review will provide insight into DES nanostructure, their potential applications, and development of a robust framework for systematic investigation moving forward.