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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Frontiers of Ionic Liquids in Carbon Dioxide Separation and Valorization

Ionic liquids (ILs) have emerged as highly tunable sorbents and membranes for gas separation, especially in the purification of CO 2 -containing gas streams such as air, natural gas, biogas, and syngas. Their negligible volatility, high thermal stability, and chemical versatility position them as promising alternatives to conventional amine and alkaline metal derivative-based systems, effectively addressing key challenges such as volatility, stability, and high regeneration energy. Here, this Review explores IL-derived systems for CO 2 -related gas separation across dense, porous, and supported categories. At the dense liquid level, we discuss strategies for tailoring IL properties to optimize CO 2 sorption, focusing on the correlation between IL-CO 2 interaction strength, uptake capacity, and regeneration energy. Key advancements in carbon capture, including amino-functionalized (AILs) and superbase-derived ILs (SILs), are highlighted, along with strategies such as chemical structure engineering, multiple binding site integration, alternative driving force exploration, and stability enhancement. Then, the porous liquids (PLs) scale focuses on the emerging field integrating IL properties with permanent porosity engineering, spanning ultramicropores (<5 Å) to macropores (around 100 nm). These innovations improve gas uptake capacity, accelerate transport kinetics, introduce the gating effect, and enable the coexistence of active sites with antagonistic properties within a single IL medium. At the supported IL scale, the discussion shifts to IL- and ionic pair-modified sorbents and membranes, emphasizing the modulation of cations and anions, confinement effects from porous supports, and the IL–interface interaction to enhance CO 2 separation performance, particularly in diluted gas streams. Beyond separation, this Review highlights IL-based integrated processes for CO 2 capture and conversion into value-added chemicals via thermocatalytic, electrocatalytic, and photocatalytic pathways. At each scale, advanced computational and experimental tools for IL design are also discussed, providing insights into stability enhancement, sorption efficiency, and process integration. The Review concludes by addressing existing challenges and outlining future directions for IL-driven innovations in gas separation technologies.

Qiu, Liqi [Univ. of Tennessee, Knoxville, TN (Unit↗
DOE OSTI2025

Field-Driven Simulations to Probe the Impact of Ionic Correlations on Solution Transport Coefficients in Binary, Ternary, and Reciprocal Quaternary Aqueous Electrolytes

Ionic correlations play a critical role in governing transport properties of mixed-salt aqueous electrolyte solutions, yet their quantitative characterization remains challenging, particularly for multicomponent aqueous systems. Here, we develop a general nonequilibrium molecular dynamics framework to efficiently compute Onsager transport coefficients and ionic correlations in mixed-salt aqueous solutions. Using field-driven simulations, we obtain accurate Onsager matrices for LiCl/ KCl, KCl/KBr, and LiBr/KCl electrolyte solutions with significantly reduced computational cost relative to equilibrium Green−Kubo methods. The framework enables direct assessment of how attractive cation−anion and repulsive like-ion interactions contribute to conductivity and salt diffusivity across compositions. While static ion pairing exhibits strong composition dependence, dynamic ion correlations remain nearly invariant, leading to constant deviations from Nernst−Einstein predictions. These results highlight the disconnect between static ion association and dynamic transport correlations, and they establish a transferable approach for analyzing ion transport in complex electrolyte environments relevant to separation processes and electrochemical systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Predicting Partial Atomic Charges in Metal–Organic Frameworks: An Extension to Ionic MOFs

Molecular simulation is an invaluable tool to predict and understand the usage of metal–organic frameworks (MOFs) for gas storage and separation applications. Accurate partial atomic charges, commonly obtained from density functional theory (DFT) calculations, are often required to model the electrostatic interactions between the MOF and adsorbates, especially when the adsorbates have dipole or quadrupole moments, such as water and CO 2 . Machine learning (ML) models have been previously employed to predict partial charges and avoid the computational cost associated with DFT calculations. However, previous ML models suffer from small training data sets, which limit their scope of application. In this work, we introduce two novel machine learning models, PACMOF2-neutral and PACMOF2-ionic, aimed at predicting the density-derived electrostatic and chemical (DDEC6) partial atomic charges for both neutral and ionic MOFs. These models not only yield DFT-level accuracy at a fraction of the computational cost but also demonstrate a remarkable improvement in prediction of adsorption, as validated with grand canonical Monte Carlo simulations. Furthermore, the robustness and fast computational time of the PACMOF2 models, along with their transferability to other porous materials such as covalent organic frameworks and zeolites, underscores their potential in high-throughput screening of MOFs for diverse applications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Tuning Anion Composition and Mobility to Balance Ionic Conductivity and Cation Selectivity in Solid Polymer Electrolytes

Solid polymer electrolytes (SPEs) offer a promising route toward safe and high-performance electrochemical energy storage, yet a fundamental challenge in SPEs involves improving ionic conductivity while maintaining selective cation transport. The hurdle exists because ion transport is typically coupled closely to polymer segmental dynamics. Herein, a glassy single-ion-conducting polymer, poly[lithium sulfonyl(trifluoromethane sulfonyl)imide methacrylate] (PLiMTFSI), in which the anions were tethered to the polymer, was blended with a flexible polymer, poly(oligo-oxyethylene methyl ether methacrylate) (POEM), and a series of small-molecule lithium salts, in which the anions were untethered [lithium bis(trifluoromethane­sulfonyl)imide (LiTFSI), lithium bis(fluorosulfonyl)imide (LiFSI), lithium trifluoromethanesulfonate (LiTf), or lithium perchlorate (LiClO 4 )]. The impact of salt anion volume and tethered-to-untethered anion ratio on the ion conduction behavior and thermal properties of blend electrolytes was investigated. In some cases, conductivity could be enhanced through this ternary blend approach. For example, a POEM-based polymer blend containing a bulky salt anion (TFSI⁻) and an equimolar mixture of PLiMTFSI and LiTFSI exhibited a Li + conductivity (4.8×10 -4 S/cm) an order of magnitude higher than that of a comparable POEM / LiTFSI system (6.3×10 -5 S/cm) at 100 °C. This enhancement was attributed to a more than ninefold increase in lithium transference number (0.66 in the ternary blend vs. 0.07 in POEM / LiTFSI). Overall, this study highlights the potential for tuning anion composition and mobility to achieve relatively high ionic conductivities and maintain selective cation transport in SPEs, offering a pathway to enable batteries that tolerate elevated temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Ionic Associations and Hydration in the Electrical Double Layer of Water-in-Salt Electrolytes

Water-in-Salt-Electrolytes (WiSEs) are an exciting class of concentrated electrolytes finding applications in energy storage devices because of their expanded electrochemical stability window, good conductivity and cation transference number, and fire-extinguishing properties. These distinct properties are thought to originate from the presence of an anion-dominated ionic network and interpenetrating water channels for cation transport, which indicates that associations in WiSEs are crucial to understanding their properties. Currently, associations have mainly been investigated in the bulk, while little attention has been given to the electrolyte structure near electrified interfaces. Here, we develop a theory for the electrical double layer (EDL) of WiSEs, where we consistently account for the thermoreversible associations of species into Cayley tree aggregates. The theory predicts an asymmetric structure of the EDL. At negative voltages, hydrated Li + dominates, and cluster aggregation is initially slightly enhanced before disintegration at larger voltages. At positive voltages, when compared to the bulk, clusters are strictly diminished. Performing atomistic molecular dynamics (MD) simulations of the EDL of WiSE provides EDL data for validation and bulk data for parametrization of our theory. Validating the predictions of our theory against MD showed good qualitative agreement. Furthermore, we performed electrochemical impedance measurements to determine the differential capacitance of the studied LiTFSI WiSE and also found reasonable agreement with our theory. Overall, the developed approach can be used to investigate ionic aggregation and solvation effects in the EDL, which, among other properties, can be used to understand the precursors for solid-electrolyte interphase formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

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↗
DOE OSTI2024

Influence of Water Sorption on Ionic Conductivity in Polyether Electrolytes at Low Hydration

Ion-containing polymers are subject to a wide range of hydration conditions across electrochemical and water treatment applications. Significant work on dry polymer electrolytes for batteries and highly swollen membranes for water purification has informed our understanding of ion transport under extreme conditions. However, knowledge of intermediate conditions (i.e., low hydration) is essential to emerging applications (e.g., electrolyzers, fuel cells, and lithium extraction). Ion transport under low levels of hydration is distinct from the extreme conditions typically investigated, and the relevant physics cannot be extrapolated from existing knowledge, stifling materials design. In this study, we conducted ion transport measurements in LiTFSI-doped polyethers that were systematically hydrated from dry conditions. A semiautomated apparatus that performs parallel measurements of water uptake and ionic conductivity in thin-film polymers under controlled humidity was developed. For the materials and swelling range considered in this study (i.e., <0.07 g water/g dry polymer electrolyte), ionic conductivity depends nonlinearly on water uptake, with the initial sorbed water weakly affecting conductivity. With additional increases in swelling, more significant increases in conductivity were observed. Remarkably, changes in conductivity induced by water sorption were correlated with the number of water molecules per lithium ion, with the normalized molar conductivity of different samples effectively collapsing onto one another until this unit of hydration exceeded the solvation number of lithium ions under aqueous conditions. Furthermore, these results provide important knowledge regarding the effects of trace water contamination on conductivity measurements in polymer electrolytes and demonstrate that the lithium-ion solvation number marks a key transition point regarding the influence of water on ion transport in ion-containing polymers.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Critical Role of Framework Flexibility and Disorder in Driving High Ionic Conductivity in LiNbOCl 4

Understanding Li-ion transport is key for the rational design of superionic solid electrolytes with exceptional ionic conductivities. LiNbOCl 4 is reported to be one of the most highly conducting materials in the recently realized new class of soft oxyhalide solid electrolytes, exhibiting an ionic conductivity of ~11 mS·cm -1 . Here, we apply X-ray/neutron diffraction and pair distribution function analysis - coupled with density functional theory/ab-initio molecular dynamics - to determine a structural model that provides a rationale for the high conductivity that we observe experimentally in this nanocrystalline solid. We show that it arises from unusually high framework flexibility at room temperature. This owes to isolated 1-D [NbOCl 4 ] - anionic chains which exhibit energetically favorable orientational disorder that is - in turn - correlated to multiple, disordered and equi-energetic Li + sites in the lattice. As the Li-ions sample the 3-D energy landscape with a fast predicted diffusion coefficient of 5.1 x 10 -7 cm 2 /s at room temperature (σ i calc = 17.4 mS·cm -1 ), the inorganic polymer chains can reorient or vice versa. The activation energy barrier for Li migration through the frustrated energy landscape is especially reduced by the elastic nature of the NbO 2 Cl 4 octahedra evident from very widely dispersed Cl-Nb-Cl bond angles in AIMD snapshots at 300 K. The phonon spectra are predominantly influenced by Cl vibrations in the low energy range, and there is strong overlap between the framework (Cl, Nb) and Li partial pDOS in the region between 1.2 - 4.0 THz. The framework flexibility is also reflected in a relatively low bulk modulus of 22 GPa. In conclusion, our findings pave the way for investigation of future “flex-ion” inorganic solids and open up a new direction for the design of high conductivity, soft solid electrolytes for all-solid-state batteries.

AIMD↗
DOE OSTI2025

Anodized Aluminum Oxide Membrane Ionic Memristors

Memory effect in ion transport (IT) at the solid–solution interface is uniquely attractive in that the conductance depends on or “memorizes” the previous states. Hysteretic and rectified transport properties offer exciting potential to developing advanced iontronics and neuromorphic functions, improving the efficiency of energy conversion and electrochemical processes, and overcoming the selectivity-throughput bottleneck in the enrichment of low abundant species for environment- and energy-friendly separations, among others. Herein, memory effects are discovered in the rectified electrokinetic IT through anodized aluminum oxide (AAO) membranes containing densely packed highly ordered nanochannels (10 10 per cm 2 ). Characteristic memristor responses of pinched current–potential loops are resolved in voltammetric experiments and successfully reproduced through finite element simulation. Excitatory and inhibitory conductance states are shown to arise from the enrichment and depletion of mobile charge carriers. Structurewise, the transport symmetry is broken by the barrier oxide layer (BOL) on the one end of the cylindrical nanochannels across the AAO membranes. Charge selectivity is attributed to the gradient(s) of the space charge density across the BOL characterized by depth profiling via X-ray photoelectron spectroscopy analysis. The space charge gradient(s) overcomes the fundamental limitation of widely exploited surface charge effects to enable intense rectification and hysteresis prevailing at very high ionic concentrations up to 1–2 M. A new strategy is developed for controlling the preferential IT direction and selectivity via counterion intercalation and extraction/exchange. Mechanistic understanding is further confirmed through parameter variations such as potential scan rate and ionic strength, which also demonstrates convenient controls of the related functions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Neural network potentials with effective charge separation for non-equilibrium dynamics of ionic solids: a ZnO case study

Developing neural network potentials (NNPs) accurate under non-equilibrium dynamics is challenging, as such systems require extensive sampling beyond equilibrium phases. Here we construct high-fidelity NNPs for zinc oxide (ZnO), a polymorphic ionic solid, using density functional theory (DFT) reference data. To efficiently capture transitional configurations, we combine enhanced-sampling molecular dynamics with empirical potentials, data distillation, and pretraining on short-range atomic energies (A-Train), followed by transfer learning with DFT-relabeled datasets. This hierarchical approach improves transferability across polymorphs and stress states. We further introduce effective charge separation, treating long-range Coulombic terms analytically while short-range residual interactions are learned by the NNP. The optimal effective charges fall in the range 0.5–1.0 q e , consistent with dielectric-screened values derived from formal charges but distinct from Bader estimates. Motivated by this observation, we propose a simple data-driven protocol in which effective charges are optimized by comparing DFT reference energies with explicit Coulomb calculations, without additional NNP training. This strategy improves accuracy and transferability in DFT-level predictions of energies, forces, and stress. Together, these results provide a practical charge-selection framework for robust NNP development in ionic solids, enabling reliable simulation of polymorphic phase transformations and non-equilibrium dynamics.

Chemistry↗
DOE OSTI2026

Solid-state thermometry via ionic–electronic coupling in two-dimensional heterostructures

The coupling of ionic and electronic transport in solid-state systems offers new opportunities for realizing compact, energy-efficient sensing technologies, yet practical implementations remain limited. In this article, we introduce a two-dimensional iontronic platform based on field-effect transistors that integrate monolayer MoS 2 channels with van der Waals bimetallic thiophosphates ( AB P 2 X 6 , A = Li, Cu, Ag and so on; B = In, Sc and so on; and X = S and Se) as ionic gate dielectrics to realize on-chip thermometry. Specifically, we exploit thermally activated ion migration within the gate dielectric leading to conductance modulation in the MoS 2 channel for temperature sensing. We achieve ~1–2 °C resolution, fast electronic readout and subpicojoule energy consumption in an ultracompact footprint (~1 µm 2 ). Beyond thermometry, these results establish bimetallic thiophosphates as a versatile platform for solid-state iontronics and broaden the functional design space of van der Waals heterostructures for sensing, actuation and adaptive electronics.

42 ENGINEERING↗
DOE OSTI2025

Balancing solvation: stabilizing lithium metal batteries via optimized cosolvents for ionic-liquid electrolytes

In this study, we examined three cosolvents with distinct solvation capabilities for ionic-liquid electrolytes based on 1-methyl-1-propyl pyrrolidinium bis(fluorosulfonyl)imide (Py13FSI). We demonstrate that 1,1,1-trifluoro-2-(2-(2-(2,2,2-trifluoroethoxy)ethoxy)ethoxy)ethane (FDG) notably enhances the cycle life of Py13FSI-based electrolytes, outperforming 1,1,2,2-tetrafluoroethyl 2,2,3,3-tetrafluoropropylether (TTE) and diglyme (DG). Electrochemical and surface analyses showed that this improvement could be attributed to the formation of a favorable cathode interphase, promoting efficient Li+ transport with reduced overpotential. Spectroscopic techniques (FTIR, Raman, and NMR spectroscopy) and molecular dynamics simulations revealed that cosolvents with varying solvation abilities can influence the solvation structures in Py13FSI-based electrolytes. The mild solvating strength and lithium stability of FDG are key contributors to its effectiveness. Conversely, DG, a strong solvating solvent, destabilized the Py13FSI-DG electrolyte at the lithium metal anode, while TTE, a non-solvating solvent, failed to enhance lithium transport or form a stable cathode interphase. Our findings highlight that balanced solvation exerted by the cosolvents is critical for forming a stable electrolyte–cathode interface, potentially through FSI decomposition. This study offers valuable insights into the development of durable ionic-liquid electrolytes, emphasizing the importance of selecting cosolvents with optimal solvation properties.

Li, Xinlin [Argonne National Laboratory (ANL), Arg↗
DOE OSTI2025

Molecular property prediction for very large databases with natural language processing: a case study in ionic liquid design

The prospect of using artificial intelligence (AI) to accurately screen very large databases of compounds for multiple properties has yet to be realized. Here, we explore this possibility using ionic liquids (ILs) which offer unique physicochemical properties and excellent tunability, making them highly versatile solvents for various research applications. Screening millions of potential ILs for the best perfomance for use in specific tasks with experimental methods alone however, is impractical. Further, traditional’ physics-based computational chemistry is hindered by high computational cost. To address this challenge, we leverage a natural language processing (NLP)-based molecular embedding technique with advanced machine learning (ML) models to predict seven key IL properties: viscosity, density, ionic conductivity, surface tension, melting temperature, toxicity, and water solubility. Comprehensive datasets for these properties are obtained, then NLP featurization with Mol2vec is compared with other featurization techniques such as 2D Morgan fingerprints, and 3D quantum chemistry-derived sigma profiles. NLP-based featurization exhibited the best predictive performance, achieving the highest R 2 and lowest RMSE values for all the studied IL properties. Further, we present case studies of how ILs might be screened using combined property criteria for practical cases – lignocellulosic biomass processing, CO 2 capture, and optimal electrolytes for batteries – screening a novel database of ∼10.6 million generated feasible ILs. The results introduce NLP as a powerful tool for engineering many designer solvents with desirable properties for task specific applications.

Mohan, Mood [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2026

Ionic liquid-enhanced recycling of lithium-ion battery black mass via heavy liquid centrifugal separation

Direct recycling of lithium-ion batteries (LIBs) is of great significance to supply chain security and environmental protection by restoring spent battery materials to their original purpose without destroying their chemical structure. One of the key processes for direct recycling is to separate valuable anode and cathode active materials from black mass. This study evaluates ionic liquid-enhanced Heavy Liquid Centrifugal Separation (HLCS) as an efficient method for separating LIB black mass into its constituent anode and cathode materials. The optimized HLCS process achieved a separation efficiency of over 95%, yielding a graphite-rich upper layer and an NMC-rich lower layer. Characterization by thermogravimetric analysis (TGA), X-ray diffraction (XRD), and inductively coupled plasma-optical emission spectroscopy (ICP-OES) confirmed the purity and structural integrity of the recovered fractions. The addition of N-methyl-2-pyrrolidone and ionic liquid 1-ethyl-3-methylimidazolium bromide decoupled entangled particles, while subsequent treatment of the anode layer with 1-(2,3-dihydroxypropyl)-3-methylimidazolium chloride further enhanced separation purity. The recycled graphite exhibited comparable battery performance to pristine graphite. These results demonstrate HLCS as a promising LIB recycling strategy, advancing sustainable battery manufacturing.

Adigun, Babafemi [Univ. of Tennessee, Knoxville, T↗
DOE OSTI2024

Voltage-induced modulation of interfacial ionic liquids measured using surface plasmon resonant grating nanostructures

We have used surface plasmon resonant metal gratings to induce and probe the dielectric response (i.e., electro-optic modulation) of ionic liquids (ILs) at electrode interfaces. Here, the cross-plane electric field at the electrode surface modulates the refractive index of the IL due to the Pockels effect. This is observed as a shift in the resonant angle of the grating (i.e., Δϕ), which can be related to the change in the local index of refraction of the electrolyte (i.e., Δnlocal). The reflection modulation of the IL is compared against a polar (D2O) and a non-polar solvent (benzene) to confirm the electro-optic origin of resonance shift. The electrostatic accumulation of ions from the IL induces local index changes to the gratings over the extent of electrical double layer (EDL) thickness. Finite difference time domain simulations are used to relate the observed shifts in the plasmon resonance and change in reflection to the change in the local index of refraction of the electrolyte and the thickness of the EDL. Simultaneously using the wavelength and intensity shift of the resonance enables us to determine both the effective thickness and Δn of the double layer. We believe that this technique can be used more broadly, allowing the dynamics associated with the potential-induced ordering and rearrangement of ionic species in electrode–solution interfaces.

Chemistry↗
DOE OSTI2024

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↗
DOE OSTI2024

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↗