Effects of Acid Dissociation and Ionic Solutions on the Aggregation of 2-Pyrone-4,6-dicarboxylic Acid
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The ability of functionalized ionic liquids (ILs) to provide an environment of increased stability for biomolecules has been studied. Serum albumin is an inexpensive, widely available protein that contributes to the overall colloid osmotic blood pressure within the vascular system. Albumin is used in the present study as a marker of biomolecular stability in the presence of various ILs in a range of concentrations. The incorporation of hydroxyl functionality into the methylimidazolium-based cation leads to increased protein stability detected by fluorescence spectroscopy and circular dichroic (CD) spectrometry.
Physical networks formed by ionizable polymers with ionic clusters as crosslinks are controlled by coupled dynamics that transcend from ionic clusters through chain motion to macroscopic response. Here, the coupled dynamics, across length scales, from the ionic clusters to the networks in toluene swollen polystyrene sulfonate networks, were directly correlated, as the electrostatic environment of the physical crosslinks was altered. The multiscale insight is attained by coupling neutron spin echo measurements with molecular dynamics simulations, carried out to times typical of relaxation of polymers in solutions. The experimental dynamic structure factor is in outstanding agreement with the one calculated from computer simulations, as the networks are perturbed by elevating the temperature and changing the electrostatic environment. In toluene, the long-lived clusters remain stable over hundreds of ns across a broad temperature range, while the polymer network remains dynamic. In conclusion, though the size of the clusters changes as the dielectric constant of the solvent is modified through the addition of ethanol, they remain stable but morph, enhancing the polymer chain dynamics.
Renewable energy is increasingly relying on optimized electrolytes and interfaces. In this work, Tween 20 and sodium chloride are selected as a model system to reveal the effects of surfactants on salt crystallization in the context of ionic conductivity and interface optimization. At a varied crystallization speed and mix ratio, it is demonstrated that the resultant solution-grown ionic crystalline complexes can achieve a highly tunable ion transport with a controllable crystalline interface. X-ray diffraction results rule out the possibility of polymorphism in the NaCl/Tween 20 systems, which further supports the importance of an optimized crystalline network for optimizing permittivity or ionic conductivity. Raman mapping and machine learning techniques are used to perform semantic segmentation on highly heterogeneous NaCl/Tween 20 complexes. Furthermore, FTIR measurements demonstrate that inter- and intra-molecular interactions play critical roles in the formation of these crystals. This work lays a foundation toward future optimization of such complex ion systems for a specific salt or crystallization modifier in energy storage or ion transport applications.
The electrochemical stability window (ESW) defines the voltage range within which an electrolyte remains stable against oxidation and reduction, serving as a key descriptor for ionic liquid (IL)-based systems. The ESWs of 15 ILs with diverse cation-anion combinations were systematically investigated, both in their neat forms and as binary mixtures with three representative solvents, i.e., propylene carbonate (PC), ethylene glycol (EG), and tetrahydrofuran (THF). Cyclic voltammetry on a glassy carbon electrode determined anodic and cathodic stability limits, revealing that ESW protection in IL-solvent mixtures strongly depends on solvent polarity, proticity, and IL compatibility. PC, with a high dielectric constant and aprotic character, broadened anodic limits and moderately stabilized cathodic limits. THF maintained compact interfacial structure, offering additional cathodic protection, whereas EG, being protic, reduced ESWs via proton-coupled electron transfer and hydrogen evolution. The solvent protection trend followed by PC > THF > EG, with bulky, hydrophobic cations ([HMIM] + , [BMPYRR] + ) and weakly coordinating anions ([NTF 2 ] - , [DCA] - , [DEP] - ) showing the highest ESW protection for 50 mol% IL in these solvents. Among the neat ILs, [EMIM][DEP], [HMIM][PF 6 ], and [BMPYRR][DCA] showed wide ESWs of ∼5.5 V. These results provide valuable insight into solvent-modulated electrochemical stability, enabling rational design of IL-based electrolytes for energy storage and electrosynthesis.
Rotating magnetic fields (RMF) have found applications in modern metallurgy. Examples are casting and semiconductor crystal growth technology. Rotating convective flows can also be induced in ionic fluids. Due to optical transparency, these fluids offer a great opportunity to visualize convection. In this work, we investigate the dynamics of convection induced by a high frequency (100 kHz range) RMF. A dye injected into a cylindrical column of salty water serves as an indicator of the flow. The developed technique has been used to study mixing phenomena induced by a RMF both when the direc'tion of the field rotation is constant and when it is alternated. Optical recording has been used to analyze this process. A numerical model describing RMF mixing in the laminar regime will also be presented.
An electrochemical technique for deionizing water, now under development, is intended to overcome a major limitation of prior electrically-based water-purification techniques. The limitation in question is caused by the desired decrease in the concentration of ions during purification: As the concentration of ions decreases, the electrical resistivity of the water increases, posing an electrical barrier to the removal of the remaining ions. In the present technique, this limitation is overcome by use of electrodes, a flowfield structure, and solid electrolytes configured to provide conductive paths for the removal of ions from the water to be deionized, even when the water has already been purified to a high degree. The technique involves the use of a bipolar membrane unit (BMU), which includes a cation-exchange membrane and an anion-exchange membrane separated by a nonconductive mesh that has been coated by an ionically conductive material (see figure). The mesh ensures the desired microseparation between the ion-exchange membranes: The interstices bounded by the inner surfaces of the membranes and the outer surfaces of the coated mesh constitute a flow-field structure that allows the water that one seeks to deionize (hereafter called "process water" for short) to flow through the BMU with a low pressure drop. The flow-field structure is such that the distance between any point in the flow field and an ionically conductive material is small; thus, the flow-field structure facilitates the diffusion of molecules and ions to and from the ion-exchange membranes. The BMU is placed between an anode and a cathode, but not in direct contact with these electrodes. Instead, the space between the anion-exchange membrane and the anode is denoted the anode compartment and is filled with an ionic solution. Similarly, the space between the cation-exchange membrane and the cathode is denoted the cathode compartment and is filled with a different ionic solution. The electrodes are made of titanium coated with platinum.
Widely known as “green solvents,” ionic liquids (ILs) and deep eutectic solvents (DESs) have been used as substitutes for traditional organic solvents in separation science. To achieve better separations using ILs and DESs, this work aimed to predict the infinite dilution activity coefficients (IDACs) of molecular solutes in these solvents with the state-of-the-art factorization-machine-based neural network (DeepFM). DeepFM combines the benefits of factorization machines and deep neural networks to learn both low-order and high-order interactions among features. The IDAC prediction model was established with 52,372 experimental IDAC datapoints including 260 solvents (252 ILs and 8 DESs) and 112 molecular solutes collected at various temperatures from 288.15 to 428.15 K. Chemical information describing the ILs, DESs, and molecular solutes was included in the IDAC prediction model, including chemical functional groups, molecular weights, and Abraham solvation parameters. The IDAC prediction model showed an improved accuracy compared with alternative models; additionally, DESs were included in the IDAC prediction model for the first time. Here, the model will reduce the energy and resources needed to optimize the selection of ILs and DESs for specific separations, which will promote the development of these green solvents for sustainable chemical processes.
Highly selective ion separations are vital for producing pure salts, and membrane-based separations are promising alternatives to conventional ion-separation techniques. Our previous work demonstrated that simple pressure-driven flow through negatively charged isoporous membranes can separate Li+ and K+ with selectivities as high as 70 in dilute solutions. The separation mechanism relies on spontaneously arising streaming potentials that induce electromigration, which opposes advection and separates cations based on differences in their electrophoretic mobilities. Although the separation technique is simple, this work shows that high selectivities are possible only with careful consideration of experimental conditions including transmembrane pressure, solution ionic strength, the K+/Li+ ratio in the feed, and the extent of concentration polarization. Separations conducted with a rotating membrane show Li+/K+ selectivities as high as 150 with a 1000 rpm membrane rotation rate, but the selectivity decreases to 1.3 at 95 rpm. These results demonstrate the benefits and necessity of quantitative control of concentration polarization in highly selective separations. Increases in solution ionic strength or the K+/Li+ feed ratio can also decrease selectivities more than an order of magnitude.
This paper describes a practical approach using a general purpose lumped-parameter computer program, GFSSP (Generalized Fluid System Simulation Program) for calculating flow distribution in a network of micro-channels including electro-viscous effects due to the existence of electrical double layer (EDL). In this study, an empirical formulation for calculating an effective viscosity of ionic solutions based on dimensional analysis is described to account for surface charge and bulk fluid conductivity, which give rise to electro-viscous effect in microfluidics network. Two dimensional slit micro flow data was used to determine the model coefficients. Geometry effect is then included through a Poiseuille number correlation in GFSSP. The bi-power model was used to calculate flow distribution of isotropically etched straight channel and T-junction microflows involving ionic solutions. Performance of the proposed model is assessed against experimental test data.
We characterize a concentrated 7.3 m CaCl 2 solution, combining neutron diffraction with chloride isotopic substitution (Cl-NDIS) in null water and molecular dynamics (MD) simulations. We elucidate the solution structure, thermodynamic properties, and extent of ion pairing previously suggested as concentration-dependent and often not observed at lower concentrations. Our Cl-NDIS measurements designate the solvent-shared ion pairing as dominant and the contact ion pairing (CIP) as insignificant even under conditions close to the solubility limit. The MD models parameterized against neutron diffraction with calcium isotopic substitution (Ca-NDIS) overestimate CIP despite successfully reproducing most of the Cl-NDIS signal. This drawback originates from the fact that Ca 2+ –Cl - interactions were primarily “hidden” in the Ca-NDIS signal due to overlapping with Ca 2+ –O w and Ca 2+ –H w contributions to the total scattering. Contrary, MD models with moderate CIP and possessing generally good performance at high concentrations fail to reproduce the NDIS measurements accurately. Therefore, the electronic polarization, introduced in most of the recent MD models via scaling ionic charges, resolves some but not all parameterization drawbacks. We conclude that despite improving the quality of MD models “on average,” the question “which model is the best” has not been answered but replaced by the question “which model is better for a given research.” An overall “good” model can still be inappropriate or, in some instances, “bad” and, unfortunately, produce erroneous results. Additionally, the accurate interpretation of several NDIS datasets, complemented by MD simulations, can prevent such mistakes and help identify the strengths, weaknesses, and convenient applications for corresponding computational models.
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Abstract The ionic liquid 1-ethyl-3-methylimidazolium methanesulfonate ([EMIM][MeSO 3 ]) has been considered as a promising alternative desiccant to triethylene glycol and lithium bromide commonly used in the industry. In this paper, the water activity coefficient of this binary system was measured from 303 K to 363 K with water concentration from 18% to 92%. The interaction energies between the ionic liquid molecules ( $${g}_{22}$$ g 22 ) and between the ionic liquid and water molecules ( $${g}_{12}$$ g 12 ) for the [EMIM][MeSO 3 ]/water binary system were determined from the water activity coefficient data using the Non-Random Two-Liquid (NRTL) model. The magnitude of the interaction energy between the [EMIM][MeSO 3 ] and water molecules ( $${g}_{12}$$ g 12 ) was found to be in the range of 45~49 kJ/mol, which was about 20% larger than that between the water molecules ( $${g}_{11}$$ g 11 ) in the [EMIM][MeSO 3 ]/water system. The large ( $${g}_{12}$$ g 12 ) can explain many observed macroscopic thermodynamic properties such as strong hygroscopicity in the ionic liquid [EMIM][MeSO 3 ]. These interaction energies were used to determine the heat of desorption of the [EMIM][MeSO 3 ]/water system, and the obtained heat of desorption was in good agreement with that calculated from the conventional Clausius-Clapeyron Equation.
Photoelectron spectroscopy experiments in ionic solutions reveal important electronic structure information, in which the interaction between hydrated ions and water solvent can be inferred. Based on many-body perturbation theory with GW approximation, we theoretically compute the quasiparticle electronic structure of chloride anion solution, which is modeled by path-integral abinitio molecular dynamics simulation by taking account the nuclear quantum effects (NQEs). The electronic levels of hydrated anion as well as water are determined and compared with the recent experimental photoelectron spectra. It is found that NQEs improve the agreement between theoretical prediction and experiment because NQEs effectively weaken the hybridization of the between the Cl – anion and water. Furthermore, our study indicates that NQEs plays a small but non-negligible role in predicting the electronic structure of the aqueous solvation of ions of the Hofmeister series.
Rejection characteristics of organic and inorganic compounds were examined for six reverse osmosis (RO) membranes and two nanofiltration (NF) membranes that are commercially available. A batch stirred-cell was employed to determine the membrane flux and the solute rejection for solutions at various concentrations and different pH conditions. The results show that for ionic solutes the degree of separation is influenced mainly by electrostatic exclusion, while for organic solutes the removal depends mainly upon the solute radius and molecular structure. In order to provide a better understanding of rejection mechanisms for the RO and NF membranes, the ratio of solute radius (r(i,s)) to effective membrane pore radius (r(p)) was employed to compare rejections. An empirical relation for the dependence of the rejection of organic compounds on the ratio r(i,s)/r(p) is presented. The rejection for organic compounds is over 75% when r(i,s)/r(p) is greater than 0.8. In addition, the rejection of organic compounds is examined using the extended Nernst-Planck equation coupled with a steric hindrance model. The transport of organic solutes is controlled mainly by diffusion for the compounds that have a high r(i,s)/r(p) ratio, while convection is dominant for compounds that have a small r(i,s)/r(p) ratio. c2005 Elsevier B.V. All rights reserved.
Two mechanisms have been proposed to account for solute permeation of lipid bilayers. Partitioning into the hydrophobic phase of the bilayer, followed by diffusion, is accepted by many for the permeation of water and other small neutral solutes, but transient pores have also been proposed to account for both water and ionic solute permeation. These two mechanisms make distinctively different predictions about the permeability coefficient as a function of bilayer thickness. Whereas the solubility-diffusion mechanism predicts only a modest variation related to bilayer thickness, the pore model predicts an exponential relationship. To test these models, we measured the permeability of phospholipid bilayers to protons, potassium ions, water, urea, and glycerol. Bilayers were prepared as liposomes, and thickness was varied systematically by using unsaturated lipids with chain lengths ranging from 14 to 24 carbon atoms. The permeability coefficient of water and neutral polar solutes displayed a modest dependence on bilayer thickness, with an approximately linear fivefold decrease as the carbon number varied from 14 to 24 atoms. In contrast, the permeability to protons and potassium ions decreased sharply by two orders of magnitude between 14 and 18 carbon atoms, and leveled off, when the chain length was further extended to 24 carbon atoms. The results for water and the neutral permeating solutes are best explained by the solubility-diffusion mechanism. The results for protons and potassium ions in shorter-chain lipids are consistent with the transient pore model, but better fit the theoretical line predicted by the solubility-diffusion model at longer chain lengths.
Electrolytes featuring negatively charged polymers, such as nonaqueous polyelectrolyte solutions and polymerized ionic liquids, are currently under investigation as potential high cation transference number (t+) electrolytes for lithium-ion batteries. Herein, we use coarse-grained molecular dynamics simulations to characterize the Onsager transport coefficients of polyelectrolyte solutions as a function of chain length and concentration. For all the systems studied, we find that the rigorously computed transference number is substantially lower than that approximated by the ideal solution (Nernst-Einstein) equations typically used to characterize these systems due to the presence of strong anion-anion and cation-anion correlations. None of the polyelectrolyte solutions achieve t+ greater than that of the conventional binary salt electrolyte, with some solutions having negative t+. Overall, this work demonstrates that the Nernst-Einstein assumption does not provide a physically meaningful estimate of the transference number in these solutions and calls into question the expectation of polyelectrolytes to exhibit a high cation transference number.