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At least 19 records

Assessing the Effect of Explicit Polarizability on Models of Carbon Dioxide Solvation in Ionic Liquids

Ionic liquids are an important possible carbon capture material because of their anomalously high sorption selectivity for carbon dioxide over other gases common in air. Many research groups have investigated the molecular origins of this property and provided important insights, including using 1D and 2D-IR spectroscopy. Molecular dynamics simulations have been indispensable to the interpretation of these experiments. In prior molecular dynamics simulation work, charge-scaled force fields have typically been used to provide a mean-field treatment of effects vital to ionic liquid systems such as charge transfer and polarization. Here, we compare models of carbon dioxide solvated in ionic liquids with explicit polarization to models of the same with implicit polarizability through charge-scaling. We calculate structural, dynamical, and spectroscopic properties, and make comparisons to the same items measured in experiment. In this study, we focus on two ionic liquids: 1-butyl-3- methylimidazolium (BMIM + ) paired with bis(trifluoromethane sulfonyl imide) (Tf 2 N − ) and 1-butyl-3-methylimidazolium (BMIM+) paired with hexafluorophosphate (PF 6 − ). We find that many structural, dynamical, and spectroscopic properties are changed when polarization is modeled explicitly. We also find that explicit polarizability softens local ion cages around the carbon dioxide and that the long-time diffusion of the carbon dioxide is gated by the reorganization of the ionic liquid molecules. Comparisons to experiment show modest improvement of many observables compared with experiment for the explicitly polarizable model over the charge-scaled model. Overall, our results show that charge-scaled force fields are likely sufficient to compute spectroscopic properties of carbon dioxide in ionic liquids and suggest some interpretive rules for understanding their structural and dynamical properties. Those using charge-scaled force fields should generally assume that the ion cages around solutes such as carbon dioxide are too stiff and cation-rich in their models and adjust their interpretations and predictions accordingly.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Tethered from the Head and from the Tail: The Structure of Hydroxyl-Functionalized Ionic Liquids

Ionic liquids with special functionalities are synthesized with the specific purpose of creating new patterns of interaction in the condensed phase. This Letter discusses the case of alcohol-functionalized ILs, the so-called HFILs, which are part of the larger cohort of task-specific ionic liquids. We find that this small chemical modification can cause massive changes in the liquid landscape when the cationic tails are longer. For prototypical ionic liquids, larger alkyl tails act as separators of charge networks, but in the case of HFILs these become physical charge network linkers. The OH functionality adds a large repertoire of interactions and correlations that were mostly unavailable to traditional ILs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Molecular dynamics simulations of uranyl and plutonyl cations in a task-specific ionic liquid

Ionic liquids (ILs) are a unique class of solvents with potential applications in advanced separation technologies relevant to the nuclear industry. ILs are salts with low melting points and a wide range of tunable physical properties, such as viscosity, hydrophobiciy, conductivity, and liquidus range. ILs have negligible vapor pressure, are often non-flammable, and can have high thermal stability and a wide electrochemical window, making them attractive for use in separations processes relevant to the nuclear industry. Metal salts generally have a low solubility in ILs; however, by incorporating new functional groups into the IL cation or anion that promote complexation with the metal, the solubility can be greatly increased. One such task-specific ionic liquid (TSIL) is 1-carboxy-N, N, N-trimethylglycine bis(trifluoromethylsulfonyl)imide ([Hbet][Tf 2 N]). Water, which is detrimental for electrochemical separations, is a common impurity in ILs and can coordinate with actinyl cations, particularly in ILs containing only weakly coordinating components. Understanding the behavior of actinides in TSIL/water mixtures on a molecular level is vital for designing improved separations processes. Classical molecular dynamics simulations of uranyl(VI) and plutonyl(VI) in 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([EMIM][Tf 2 N]) with deprotonated Hbet (betaine) and water have been performed to understand the coordination and dynamics of the actinyl cations. We find that betaine is a much stronger ligand than water and prefers to coordinate the metal in a bidentate manner. Potential of mean force simulations yield a relative free energy for betaine coordination of approximately -120 to -90 kJ/mol in mixtures with water. As the amount of betaine coordinated to the actinide increases, the diffusion coefficient of the actinyl cation decreases. Moreover, the betaine ligand is able to bridge between two metal centers, resulting in dimeric complexes with actinide–actinide distances of ~5 Å. Potential of mean force simulations show that these structures are stable, with relative free energies of up to -40 kJ/mol. The crystal structure for [(UO 2 ) 2 (bet) 6 (H 2 O) 2 ][Tf 2 N] 4 shows that the betaine bridges between two uranium atoms to form dimeric complexes similar to those found in our simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Electrons and Their Multiple Kinetic Fates in an Ionic Liquid

Ionic liquids (ILs) for electrochemical, nuclear, and solar energy applications operate under harsh conditions, where electrons and transient radical species can form. This communication discusses why anions such as bis(trifluoromethylsulfonyl)imide (Tf 2 N − ) are reduced at the electron-rich electrode whereas in laser photoionization or pulse radiolysis studies, where electrons are ejected from species in the bulk, we often detect long-lived electrons in cavities that interact with IL cations instead. This work argues that bulk excess electrons generated photolytically or radiolytically follow kinetically favored pathways. As such, cavity electrons may not be the most energetically favorable states, but when they form, and they do form, they are kinetically stable. Reduction reactions of anions or electron localization in cavities and subsequent reactions are all expected outcomes. Here we focus on a pyrrolidinium-based IL of the dicyanamide (N(CN) 2 − ) anion because of its large electrochemical window and very low viscosity, which are ideal for energy applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Deep Learning Approaches for Predicting the Surface Tension of Ionic Liquids

Ionic liquids (ILs) are a novel class of solvents that have attracted significant attention due to their unique and tunable properties. Among their physiochemical characteristics, surface tension plays a critical role in various industrial applications including electrolytes, heat transfer fluids, and separation processes. However, because of the exploratory nature of IL design and the vast combinatorial space of possible anion–cation pairs, the experimental determination of these properties is often impractical, being both time-consuming and costly. To overcome these challenges, computational approaches are increasingly employed to develop accurate predictive models that can accelerate IL discovery and design. In this study, we present two deep learning (DL) models for predicting the surface tension of ILs across a broad temperature range at a constant pressure. The models use simplified molecular input line entry system, SMILES, representations of ILs to extract molecular features as inputs. Both DL models demonstrate excellent agreement with experimental data, achieving an R 2 value of 0.990 and a root-mean-square error of 0.792 mN/m. In conclusion, these results offer valuable insights for the rapid screening and rational design of ILs with tailored surface tension values.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Influence of Ether-Functionalized Pyrrolidinium Ionic Liquids on Properties and Li + Cation Solvation in Solvate Ionic Liquids

Ionic liquids are tunable solvents composed entirely of ions that have properties desirable as electrolytes for lithium batteries such as non-flammability and a large electrochemical stability window. Solvate ionic liquids are a subclass of ionic liquids that consist of a glyme-based solvent and lithium salt in an equimolar ratio, where Li + cation-glyme solvation interactions result in ionic liquid-like properties. LiG4TFSi is a well-studied solvate ionic liquid consisting of equimolar amounts of lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) and tetraglyme (G4). In this work, pyrrolidinium ionic liquids with ether-functionalized side chains were synthesized containing either one ether (EO1) moiety or three ether (EO3) moieties and mixed with LiG4TFSI to form a new class of electrolyte mixtures. Their physical and transport properties, as well as ion solvation structures, were characterized by electrochemical, thermal, rheological, and spectroscopic measurements. The conductivity of the electrolyte mixture composed of EO1:LiTFSI:G4 in a 1:1:1 molar ratio is 2.54 mS/cm at 30 °C, compared to 1.53 mS/cm for LiG4TFSI, an increase of 67%. A significant decrease in the conductivity to 0.279 mS/cm is observed for the EO3:LiTFSI:G4 mixture in a 1:1:0.4 molar ratio. Pulsed-field gradient nuclear magnetic resonance (PFG-NMR) measurements revealed that the EO1 cation diffuses significantly faster than the EO3 cation in their respective mixtures. Liquid-state 13 C NMR experiments indicate that Li + cations preferentially coordinate with tetraglyme. Li + cations do not coordinate with the EO1 cation and only coordinate with EO3 ether side chains at lower concentrations of tetraglyme. We hypothesize that the oligoether EO3 cation competes with G4 and TFSI - for lithium cation solvation in G4 deficient compositions, leading to a largely adverse effect on the mass transport properties of the electrolyte.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Disentangling cation effects on ion mobility and structure in ionic liquid electrolytes

Ionic liquids (ILs) are low-temperature molten salts, where ion transport is primarily governed by ion–ion interactions. Yet, the impact of organic IL cations on critical electrolyte properties such as ion dissociation and overall transport behavior in lithium-salt-doped ILs remains poorly understood. Moreover, despite their critical role in designing IL-based electrolytes for energy storage applications, ion–ion interactions and ion-specific transport under an applied electrical potential are seldom quantified, largely due to the unique experimental and computational challenges involved. Herein, we compare transport properties obtained using 1 H, 7 Li, and 19 F pulsed-field gradient nuclear magnetic resonance (NMR) and electrophoretic NMR (eNMR) with those measured by electrochemical impedance spectroscopy. Non-equilibrium molecular dynamics (MD) simulations and eNMR confirm the presence of negatively charged [Li(TFSI) n ] (1−n) aggregates that migrate towards the positive electrode, resulting in negative lithium transference numbers. Equilibrium MD simulations reveal a vehicular Li ion transport mechanism facilitated by long-lived aggregates with Li + cations strongly bound to multiple TFSI − anions. Finally, we observe an inverse relationship between the apparent charge of the TFSI − anion in the neat IL, which is dictated by the IL cation, and Li + transport in the salt-doped systems. This highlights the opportunity to tune electrolyte performance by tailoring cation chemistry.

Li-ion batteries

Machine learning-enabled discovery of ionic liquid–solvent electrolytes exhibiting high ionic conductivity

Ionic liquids (ILs), which are a class of materials with versatile nature and growing popularity, are facing impediments toward widespread usage as electrolytes due to various factors such as low ionic conductivity, high viscosity, high market price etc. One of the ways these limitations can be addressed is by mixing ILs with a molecular solvent. In a combinatorial sense, there exists an immense number of specific IL–solvent combinations. An exhaustive experimental or even simulation-based investigation of the chemical space spanned by such combinations can be extremely time-consuming, expensive, and nearly impossible. An alternative approach is to employ machine learning-based models developed from available databases. Although there exists prior literature that integrates machine learning to investigate mixtures of specific solvents with ILs, these models lack generalization necessitating development of a large number of ML models to handle various solvents. To remedy this shortcoming, as a part of designing green electrolytes with high ionic conductivity that can have potential applications in next-generation batteries and solar cells, this work aims to develop a unified machine learning model to predict ionic conductivity of any IL–solvent mixture system. In this regard, three models, namely, Random Forest, extreme gradient boosting (XGBoost), and artificial neural network (ANN) were formulated using the NIST ILThermo database. The dataset contained 549 unique ionic liquids from 16 cation families and 81 unique solvents, representing a total of 23 712 datapoints. SHAPLEY additive explanation (SHAP) method was used to assess the impact of various features on model prediction and their significance was compared with literature to gain physical insight about the model behavior. Finally, using the developed models, approximately 2.5 million IL–solvent mixtures at five different compositions were screened at room temperature. The high-throughput screening yielded nearly 19 000 IL–solvent mixtures for which ionic conductivity was found to exceed the ionic conductivity of conventional Li-ion battery electrolyte.

25 ENERGY STORAGE

Isopentane Disproportionation in Lewis Acidic Chloroaluminate Ionic Liquid

Lewis acidic chloroaluminate ionic liquid diluted in dichloromethane catalyzes the disproportionation of alkanes, such as isopentane, via carbenium ions in a reaction readily initiated by carbenium ion precursors such as tert-butyl chloride (TBC). The carbenium ion-AlCl 4 – ion-pairs stabilized by the ionic liquid-dichloromethane solution are the key intermediates in two distinctive kinetic regimes, i.e., a transient regime (0–5 min) and a steady-state regime (after 5 min). The transient regime constitutes the majority of isopentane conversion and is governed by the initial carbenium ion concentration. In the steady-state regime, disproportionation occurs at a considerably lower rate, affected by the carbenium ion concentration, the concentration of the ionic liquid, and the reaction temperature. The formation of alkenes observed in the 1 H NMR spectra of the reacting substrates, along with the DFT calculations, suggests that deprotonation of carbenium ion-pairs reduces their concentration, decreasing, in turn, the reaction rate. Kinetic modeling indicates that the transient regime is significantly controlled by the hydride transfer (k HT ) and the deprotonation rate constants (k DP ), while the steady-state regime is additionally influenced by the alkene protonation rate constant (k –DP ). The overall activation energy of the reaction at the steady state, expressed as E a,steady-state regime = E a,HT – E a,DP + E a,–DP , was 54 kJ/mol. The reaction mechanism and the kinetics highlight the potential of Lewis acid-catalyzed conversions of hydrocarbons under remarkably mild conditions.

Deprotonation

Identifying High Ionic Conductivity Compositions of Ionic Liquid Electrolytes Using Features of the Solvation Environment

Binary mixtures of ionic liquids with molecular solvents are gaining interest in electrochemical applications due to the improvement in their performance over neat ionic liquids. Dilution with suitable molecular solvents can reduce the viscosity and facilitate faster diffusion of ions, thereby yielding substantially higher ionic conductivity than that for a pure ionic liquid. Although viscosity and diffusion coefficients typically behave as monotonic functions of concentration, ionic conductivity often passes through a peak value at an optimum molar ratio of the molecular solvent to the ionic liquid. The ionic conductivity maximum is generally explained in terms of a balance between the ease of charge transport and the concentration of the charge carriers. In this work, fluctuation in the local environment surrounding an ion is invoked as a plausible explanation for the ionic conductivity mechanism with a binary mixture of 1-ethyl-3-methylimidazolium tetrafluoroborate and ethylene glycol as an example. The magnitude of the dynamism in the local environment is captured by measuring the spatial and temporal features of the solvation environment. Standard deviation in the number of ions in the solvation environment serves as a spatial feature, while the cage correlation lifetimes for oppositely charged ions within the first solvation shell serve as a temporal feature. Large standard deviations in the cluster ion population and short cage correlation lifetimes are indicators of highly dynamic ionic environment at the molecular level and consequently yield high ionic conductivity. Such compositions were found to be in good agreement with the optimum ionic liquid mole fractions obtained through experimental measurement. Short cage correlation lifetimes enable the identification of optimum mixture compositions using simulation trajectories significantly shorter than those required to implement the Nernst–Einstein or Einstein formalisms for calculating ionic conductivity. We validated the applicability of this approach across force fields and in six ionic liquid-molecular solvent electrolytes formed with combination of cations, anions, and solvents. We offer a computationally efficient approach of screening ionic liquid-molecular solvent binary mixture electrolytes to identify molar ratios that yield high ionic conductivity.

25 ENERGY STORAGE

Elucidating the Microscale Behavior and Phase Separation Kinetics of Thermally Responsive Ionic Liquid–Water Mixtures

Thermally responsive ionic liquids (ILs) exhibit liquid-liquid phase separation into a water-rich (WR) and ionic-liquid-rich (ILR) phase when heated above a lower critical solution temperature (LCST). This phase behavior has been leveraged for applications ranging from forward osmosis (FO) desalination, where the IL acts as a draw solute, to refrigeration and dehumidification cycles, where the IL acts as a liquid desiccant. While significant effort has been devoted to characterizing the thermodynamic and thermophysical properties of LCST ILs, their phase separation kinetics have not been investigated. In this work, we describe the macroscale phase separation kinetics (phase separation time) by gleaning insight into the microscale colloidal behavior of aqueous mixtures of four different materials, P 4444 TFA (tetrabutylphosphonium-2,4-trifluoroacetate), P 4444 DMBS (tetrabutylphosphonium-2,4-dimethyl-benzenesulfonate), N 4444 Sal (tetrabutylammonium salicylate), and P 4444 Sal (tetrabutylphosphonium salicylate) as a function of IL concentration at a separation temperature of 70 °C. We report the discontinuous microscale size distributions for each material and correlate their theoretical settling velocities to experimental phase separation times. The results indicate that a simple Stokes' law model can predict the phase separation time within reasonable accuracy. Overall, this work lays the foundation for understanding the micro- to macroscale phase separation behavior and kinetics of LCST ILs for various water-energy applications.

LCST

Secondary electron emission measurements from imidazolium-based ionic liquids

The electron-induced secondary electron emission (SEE) yields of imidazolium-based ionic liquids are presented for primary electron beam energies between 30 and 1000 eV. These results are important for understanding plasma synthesis of nanoparticles in plasma discharges with an ionic liquid electrode. Due to their low vapor pressure and high conductivity, ionic liquids can produce metal nanoparticles in low-pressure plasmas through reduction of dissolved metal salts. In this work, the low vapor pressure of ionic liquids is exploited to directly measure SEE yields by bombarding the liquid with electrons and measuring the resulting currents. The ionic liquids studied are [BMIM][Ac], [EMIM][Ac], and [BMIM][BF 4 ]. The SEE yields vary significantly over the energy range, with maximum yields of around 2 at 200 eV for [BMIM][Ac] and [EMIM][Ac], and 1.8 at 250 eV for [BMIM][BF 4 ]. Molecular orbital calculations indicate that the acetate anion is the likely electron donor for [BMIM][Ac] and [EMIM][Ac], while in [BMIM][BF 4 ], the electrons likely originate from the [BMIM] + cation. The differences in SEE yields are attributed to varying ionization potentials and molecular structures of the ionic liquids. These findings are essential for accurate modeling of plasma discharges and understanding SEE mechanisms in ionic liquids.

ionic liquids

Liquid state theory of the structure of model polymerized ionic liquids

We employ polymer integral equation theory to study a simplified model of semiflexible polymerized ionic liquids (PolyILs) that interact via hard core repulsions and short range screened Coulomb interactions. The multi-scale structure in real and Fourier space of PolyILs (ions chosen to mimic Li, Na, K, Br, PF 6 , and TFSI) are determined as a function of melt density, Coulomb interaction strength, and ion size. Comparisons with a homopolymer melt, a neutral polymer–solvent-like athermal mixture, and an atomic ionic liquid are carried out to elucidate the distinct manner that ions mediate changes of polymer packing, the role of excluded volume effects, and the influence of chain connectivity, respectively. The effect of Coulomb strength depends in a rich manner on ion size and density, reflecting the interplay of steric packing, ion adsorption, and charge layering. Ion-mediated bridging of monomers is found, which intensifies for larger ions. Intermediate range charge layering correlations are characterized by a many-body screening length that grows with PolyIL density, cooling, and Coulomb strength, in disagreement with Debye–Hückel theory, but in accord with experiments. Qualitative differences in the collective structure, including an ion-size-dependent bifurcation of the polymer structure factor peak and pair correlation function, are predicted. The monomer cage order parameter increases significantly, but its collective ion counterpart decreases, as ions become smaller. Such behaviors allow one to categorize PolyILs into two broad classes of small and large ions. Furthermore, dynamical implications of the predicted structural results are qualitatively discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

CO 2 in Ionene–Ionic Liquid Composite Membranes

Abstract Ionene – ionic liquid (IL) composites are promising materials for CO 2 separation, yet a molecular‐level understanding of their structure and its impact on CO 2 speciation, solubility, rotation, and diffusivity remains unclear. Herein, using multimodal nuclear magnetic resonance (NMR), time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS), atomic force microscopy (AFM), and molecular dynamics (MD) simulations, we reveal that the composites contain IL‐rich domains extending across hundreds of nanometres within the ionene matrix, and these bicontinuous domains span the entire membrane depth. CO 2 also absorbs into the ionene matrix, with the distribution between two CO 2 species varying with temperature and time. The rotational correlation times of these two species are on the timescale of 0.1 and 1 ns, respectively. As IL content increases, the ionic domains expand, resulting in higher CO 2 solubility due to enhanced molecular dynamics and increased free volume in both ionene backbones and IL‐rich regions. Although CO 2 diffusion in the membranes is an order of magnitude slower than in bulk IL, the activation energy for CO 2 diffusion remains comparable. Ionene‐IL composites represent a promising platform for designing CO 2 separation membranes, offering enhanced CO 2 diffusion and selectivity through IL‐rich domains, and increased CO 2 solubility and mechanical integrity from the ionene matrix.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH