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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.
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.
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.
Quantum Chemistry-Driven Machine Learning Approach for the Prediction of the Surface Tension and Speed of Sound in Ionic Liquids
Ionic liquids (ILs) have unique solvent properties and have thus garnered significant interest. However, exhaustive experimental determination of the physicochemical properties of ILs is unrealistic due to the large structural diversity of anions and cations, their high cost, the requirements of elevated temperature and pressure, and the time required. To circumvent these experimental costs, computational approaches to accurately calculate these properties have emerged. Here in the present study, we present a demonstration of two machine learning (ML) models for the prediction of two critical IL physical properties, the surface tension and the speed of sound, across a wide range of temperatures and pressures. The models make use of molecular descriptors derived from the COSMO-RS, a quantum chemical-based model. The ML models show excellent agreement with experimental observations, with an R2 value of 0.96–0.99 and RMSE of 1.71 mN/m and 16.12 m/s for the surface tension and speed of sound, respectively. This work paves the way for the development of COSMO-RS-informed ML models for the prediction of IL properties which can help to further optimize and accelerate technology development for ILs.
Atomic Level Interactions and Suprastructural Configuration of Plant Cell Wall Polymers in Dialkylimidazolium Ionic Liquids
Ionic liquids (ILs) have been widely investigated for the pretreatment and deconstruction of lignocellulosic feedstocks. However, the modes of interaction between IL-anions and cations, and plant cell wall polymers, namely, cellulose, hemicellulose, and lignin, as well as the resulting ultrastructural changes are still unclear. In this study, we investigated the atomic level and suprastructural interactions of microcrystalline cellulose, birch wood xylan, and organosolv lignin with 1,3-dialkylimidazolium ILs having varying sizes of carboxylate anions. Analysis by 13 C NMR spectroscopy indicated that cellulose and lignin exhibited stronger hydrogen bonding with acetate ions than with formate ions, as evidenced by greater chemical shift changes. Small-angle X-ray scattering analysis showed that while both cellulose and xylan adopted a single-stranded conformation in acetate-ILs, twice as many acetate ions were bound to one anhydroglucose unit than to an anhydroxylose unit. Further, we also determined that a minimum of seven representative carbohydrate units must interact with an anion for that IL to effectively dissolve cellulose or xylan. Lignin is associated as groups of four polymer molecules in formate-ILs and dispersed as single molecules in acetate-ILs, which indicates that it is highly soluble in the latter. In summary, our study demonstrated that 1,3-dialkylimidazolium acetates displayed stronger binding interactions with cellulose and lignin, as compared to formates, and thus have superior potential to fractionate these polymers from lignocellulosic feedstocks.
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.
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.
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.
CO2 Sorption in Ionic Liquid Crystals
Ionic liquid crystals (ILCs) have an affinity for certain polarizable gases such as CO2, due to their similarity to ionic liquids. We investigated three ILCs in the [1-alkyl-3-methylimidazolium+] family: n=12,14 with [BF4-] and [PF6-]: liquid crystalline analogues to ionic liquids with moderate (e.g., 1-2 mol%) CO2 solubility at atmospheric conditions: [1-butyl-3-methylimidazolium+] with [BF4-] and [PF6-]. While ionic liquids show high CO2 solubility, regenerating the CO2 is a high-energy process. Liquid crystals show low CO2 solubility but have a much lower regeneration energy requirement. Will ionic liquid crystals uptake CO2? What are the energy requirements of regenerating CO2? Conclusions: 1. C12mim BF4- shows the highest sorption at 0.12 wt% CO2 in the isotropic phase vs. C14mim BF4- with 0.097 wt% in the smectic phase. We hypothesize that the increase in chain length affects the free volume of the smectic vs. isotropic phase of C14mim BF4-, increasing the latter. 2. The change in anion from BF4- to PF6- decreased the sorption to an insignificant level more analogous to a physical adsorption onto the material in all phases. We hypothesize that the change in anion to the larger, less charge dense PF6- decreased the attractive forces between CO2 and the anion. 3. 0.12 wt% of CO2 in C12mim BF4- is small but significant. This in combination with the room temperature release of CO2 after only requiring refrigeration temperatures to occlude the CO2, making ionic liquid crystals promising materials for future.
Proton Conducting Sulfonated Poly(Ionic Liquid) Block Copolymers
Herein, we report the synthesis of proton-conducting sulfonated poly(ionic liquid) block copolymers (S-PILBCPs) containing one block with sulfonic acid (sulfonated styrene, SS) and the other with an IL moiety (vinylbenzylmethylimidazolium bis(trifluoromethylsulfonyl)imide, VBMIm-TFSI) using reversible addition–fragmentation chain-transfer (RAFT) polymerization and post-polymerization modifications (i.e., functionalization, anion exchange reactions, and sulfonation). The S-PILBCPs uniquely conjoin the SS block with mobile protons (H + ) and the PIL block with mobile anions (TFSI – ), where multiple highly desired properties, including high proton conductivity (from the SS block), and high IL-philicity and oxygen solubility (from the PIL block) can exist compartmentally within a microphase separated morphology (evidenced by differential scanning calorimetry (DSC) and small-angle X-ray scattering (SAXS)). High ion conductivity of 79.7 mS/cm at a PIL block composition of 21.6 mol % was observed at 80 °C and 90% relative humidity (RH) (comparable to the benchmark Nafion ionomer). This work successfully demonstrates the design of S-PILBCPs as a new material platform and showcases its promise as an ionomer for proton exchange membrane fuel cells (PEMFCs) as they simultaneously and compartmentally combine proton conductivity and oxygen solubility. Furthermore, these benefits have recently been leveraged to achieve substantial improvement in oxygen reduction reaction (ORR) activity and subsequently fuel cell performance.
Nanodomains and Their Temperature Dependence in a Phosphonium-Based Ionic Liquid: A Single-Molecule Tracking Study
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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.
Theory-Enabled High-Throughput Screening of Ion Dissociation Explains Conductivity Enhancements in Diluted Ionic Liquid Mixtures
The growing demand for room-temperature ionic liquids (RTILs) for energy applications necessitates the development of an efficient screening platform. Here, in this study, we successfully developed a fully automated high-throughput RTIL screening platform specifically designed for assessing ionic conductivity. By utilizing the 96 wells of a microtiter plate as individual electrolysis cells, we measured the ionic conductivity of 22 different RTILs, encompassing various combinations of cations and anions, and benchmarked the values with existing literature. We also employed the screening platform to investigate the conductivities of RTIL mixtures with a nonaqueous solvent, ethylene glycol (EG). Specific combinations of RTILs with EG result in approximately 200% enhancement in the conductivity values compared to the pure RTILs. To understand the underlying mechanisms responsible for this enhancement, we developed a theoretical framework for ionic conductivity that considers factors such as the degree of dissociation, viscous forces, and molal volume of the RTIL-EG mixtures. The optimized electrolyte mixture was then employed in the migration-assisted moisture gradient (MAMG) CO 2 capture process to study the effects of improved ionic conductivity on the energy efficiency of the process. Notably, the enhanced conductivity of the RTIL-EG mixture led to a nearly 50% reduction in energy consumption for capturing CO 2 . These outcomes highlight the effectiveness of our strategy in screening RTILs and improving existing processes. Moreover, this fully automated high-throughput setup, combined with the developed theoretical framework, provides a comprehensive platform for screening and studying RTIL mixtures with different solvents, enabling their application in various fields.
Ionic Thermoelectric Generators in Vertical and Planar Topologies Based on Fluorinated Polymer Hybrid Materials with Ionic Liquids
Abstract Ionic thermoelectrics (TEs), in which voltage generation is based on ion migration, are suitable for applications based on their low cost, high flexibility, high ionic conductivity, and wide range of Seebeck coefficients. This work reports on the development of ionic TE materials based on the poly(vinylidene fluoride‐trifluoroethylene), Poly(VDF‐co‐TrFE), as host polymer blended with different contents of the ionic liquid, IL, 1‐ethyl‐3‐methylimidazolium bis(trifluoromethylsulfonyl)imide, [EMIM][TFSI]. The morphology, physico‐chemical, thermal, mechanical, and electrical properties of the samples are evaluated together with the TE response. It is demonstrated that the IL acts as a nucleating agent for polymer crystallization. The mechanical properties and ionic conductivity values are dependent on the IL content. A high room temperature ionic conductivity of 0.008 S cm −1 is obtained for the sample with 60 wt% of [EMIM][TFSI] IL. The TE properties depend on both IL content and device topology‐vertical or planar‐the largest generated voltage range being obtained for the planar topology and the sample with 10 wt% of IL content, characterized by a Seebeck coefficient of 1.2 mV K −1 . Based on the obtained maximum power density of 4.9 µW m −2 , these materials are suitable for a new generation of TE devices.
Factors that influence the activity of biomass-degrading enzymes in the presence of ionic liquids—a review
Ionic liquids (ILs) are seen as a more sustainable alternative to volatile organic solvents that are accelerating innovations in many industries such as energy storage, separations, and bioprocessing. The ability to effectively deconstruct lignocellulosic biomass is a significant hurdle in the biorefining/bioprocessing industry and presents limitations towards the commercial production of bioproducts (such as biofuels, biomaterials, etc. ). Certain ILs have been shown to promote effective lignin removal, cellulose recovery, and sugar yields from various biomass feedstocks such as corn stover, wheat straw, sugarcane bagasse, sorghum, switchgrass, miscanthus, poplar, pine, eucalyptus, and certain mixtures of municipal solid waste. However, these improvements are often counteracted by the limited biocompatibility of ILs, which results in an IL-induced reduction in enzyme activity and stability—an important downstream step in the conversion of biomass to biofuels/bioproducts. As a result, significant efforts have been made to discover and engineer compatible enzyme-IL systems and to improve our understanding on the effect that these ILs have on these systems. This review seeks to examine the impact of ionic liquids on enzymes involved in lignocellulosic biomass deconstruction, with a specific focus on their relevance in the context of pretreatment. Beyond presenting an overview of the ionic liquid pretreatment landscape, we outline the main factors that influence enzyme activity and stability in the presence of ILs This data is consolidated and analyzed to apply this body of knowledge towards new innovations that could lead to improvements in the processing of biomass to biofuels and bioproducts.
Non-Isochronal Behavior of Charge Transport at Liquid–Liquid and Liquid–Glass Transition in Aprotic Ionic Liquids
A reversible, first-order transition separating two liquid phases of a single-component material is a fascinating yet poorly understood phenomenon. Here, we investigate the liquid–liquid transition (LLT) ability of two tetraalkylphosphonium ionic liquids (ILs), [P 666,14 ]Cl and [P 666,14 ][1,2,4-triazolide], using differential scanning calorimetry and dielectric spectroscopy. The latter technique also allowed us to study the LLT at elevated pressure. We found that cooling below 205 K transforms [P 666,14 ]Cl and [P 666,14 ][Trz] from one liquid state (liquid 1) to another (the self-assembled liquid 2), while the latter facilitates the charge transport decoupled from structural dynamics. In contrast to temperature, pressure was found to play an essential role in the self-organization of a liquid 2 phase, resulting in different time scales of charge transport for rapidly and slowly compressed samples. Furthermore, τ σ (P LL ) was found to be much shorter than τ σ (T LL , P=atm), which constitutes the first example of non-isochronal behavior of charge transport at LLT. In turn, dielectric studies through the liquid–glass transition revealed the non-monotonic behavior of τ σ at elevated pressure for [P 666,14 ]Cl, while for [P 666,14 ][Trz] τ σ (P g ) was almost constant. These results highlight the diversity of liquid–liquid transition features within the class of phosphonium ionic liquids.
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.