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Osmotic and mean activity coefficients of uni-univalent electrolytes in aqueous solutions at 25 deg C
This work explores the use of thermodynamics-informed Gaussian processes (GPs) and active learning (AL) to model activity coefficients and construct phase diagrams. Relying on synthetic data generated from an excess Gibbs energy model, GPs were found to accurately describe the activity coefficients of several binary mixtures across large composition and temperature ranges. Moreover, GPs could estimate their own uncertainty and identify composition/temperature regions where activity coefficient data provide the most information to the models. This was leveraged to build AL algorithms targeted at modeling phase equilibria. In many cases, a single active-learning-acquired data point was sufficient to describe the phase diagrams studied. Lastly, the ability of AL to greatly reduce the amount of data needed to obtain accurate models was further verified on experimental case studies, namely individual ion activity coefficients, the solid–liquid and vapor–liquid equilibrium of deep eutectic solvents, and phase equilibria in ternary mixtures.
The partitioning of trace elements between metal and silicate melts serves as the foundation for understanding the differentiation of a planetary body into a metallic core and silicate mantle. Element activity influences metal-silicate partitioning behavior. Activity coefficients are directly dependent on composition and temperature, and can be indirectly dependent on oxygen fugacity and pressure. Distinguishing the effect of pressure from other variables on the activity coefficients and partitioning is important for understanding the chemical evolution of different planetary bodies during differentiation. In this study, we investigated the influence of pressure on the activity coefficients of Cu, Mo, Pd, Pt, As, Sb, and Bi in Fe-Si metallic liquids. All of these elements exhibit moderate to high activity coefficients in Fe-Si liquids at low pressure, which significantly controls their metal-silicate partitioning behavior. Identifying whether this strong dependence persists at higher pressures is critical to modeling and understanding the chemical consequences of core formation. New experiments at 10 GPa were used to derive activity coefficients for these metals which can be compared to activity coefficients determined at 1 GPa. Experiments were conducted at 10 GPa and 2373K using a 10/5 assembly in the 880-ton multi-anvil press at NASA Johnson Space Center. The standard 10/5 COMPRES assembly was slightly modified to accommodate a sample capsule machined from single-crystal MgO that minimizes melt percolation out of the sample volume during the experiment. Experiment starting materials were comprised of 70 wt.% Knippa basalt and 30 wt.% metal. The metal mixture (~85 wt.% Fe) was created by adding the elements of interest (Cu, Mo, Pd, Pt, As, Sb, Bi) to Fe metal powder. Varied amounts of Si metal (0-10 wt.% Si) were added to the metal-silicate mixtures to generate a systematic series of starting materials. For each element, an epsilon interaction parameter in Fe-Si liquid was derived from the results of our 0-10 wt.% Si metal series. To investigate whether pressure influences the trace element activity coefficients in the 1-10 GPa pressure range, we compared our results at 10 GPa to those at 1-4 GPa [1-3]. Our results can also be directly compared to interaction parameters for Au, P, V, Mn, Ga, Zn, Cd, Sn, W, Pb, and Nb previously determined at 10 GPa and 2373K following the same methods [4]. Combined, this suite of interaction parameters will directly inform metal-silicate partitioning between 1 and 10 GPa, and assess whether these values can be extrapolated to modeling differentiation processes at pressures >10 GPa.
The treatment of Hanford tank waste is one of the most technically challenging environmental cleanup activities for the U.S. Department of Energy to date. To expedite the processing of liquid waste stored in underground tanks in southeastern Washington state, it is necessary to remove the significant dose contributor, 137 Cs. Toward this effort, ion exchange with crystalline silicotitanate (CST) has been employed as part of the Tank Side Cesium Removal system. The model used to predict Cs exchange onto CST was developed using activity coefficients calculated from the Bromley equation. A series of batch contact tests that varied in [Na] were conducted to look at the impact of Na concentration on Cs distribution. Experimental distribution ratios ( K d ) were compared to the distribution ratios predicted using three different activity coefficient models: (1) commercially available HSC software, (2) the Bromley equation, and (3) a simplified approach adapted from Marcos-Arroyo et al. Ultimately, the Bromley method underpredicted the effect of ionic strength on the Na activity coefficient ( γ Na+ ), HSC overestimated the impact of ionic strength on the expected performance due to the Cs activity coefficient ( γ Cs+ ), but the simplified approach predicted the experimental K d values quite well in a binary matrix. In conclusion, expansion of this approach in complex matrices is necessary for application to Hanford tank waste.
Light elements can alloy into the iron cores of terrestrial planetary bodies. It is estimated that the Earth’s core contains ~10% of a light element, most likely a combination of S, C, Si, and O with Si probably being the most abundant. Si dissolved into Fe metal liquids can have a significant influence on the activity coefficients of siderophile elements, and thus the partitioning behavior of those elements between the core and mantle. Many of these elements have been investigated extensively at ambient pressure, and studies up to 1 GPa are becoming more common, but few have been studied at pressures above this. The formation of the Earth’s core has been estimated to have formed at pressures between 40-60 GPa, so investigating the effect pressure has on Si’s influence on siderophile element partitioning is important for modeling core formation in the Earth and smaller planets. Pressure is well known to influence volumetric properties of metallic and silicate liquids, and oxygen fugacity (e.g., [10,11]), but less is known about its effect on activity coefficients (e.g., [12]). Some activity coefficients depend strongly upon the Si content of Fe liquids, and the concentration of siderophile elements such as P, Sb, and As in the terrestrial mantle is easily influenced by dissolved Si in the core. Thus, isolating the effect of pressure on activity coefficients in general is critical in quantitative analysis of core formation models. In this work, we investigate the effect variable Si content has on the partitioning of Au between Fe metal and silicate melt at 10 GPa and 2373 K, with the intention of comparing the behavior to that already investigated at lower pressures. In addition, P, V, Mn, Ga, Zn, Cd, Sn, W, Pb, and Nb were also measured and could thus be included in the assessment of potential pressure effects.
Abstract This work presents an association‐based activity coefficient model that explicitly considers the solution nonideality due to associations among ions and solvent species. Built upon the electrolyte nonrandom two‐liquid (eNRTL) model, the model greatly improves the accuracy of eNRTL model for strongly associating electrolyte solutions due to presence of ionic species with high surface charge density. The model successfully correlates mean ionic activity coefficients of 46 aqueous single‐salt systems from 10 cations and 5 anions at 298.15 K up to their solubility limits. With the ion‐specific association parameters identified, the model accurately predicts activity and osmotic coefficients for aqueous mixed‐salt systems at 298.15 K. The temperature dependence of the model results has also been examined at 273–373 K. With superior accuracy over a wide range of concentration and temperature, the model represents a major advancement over eNRTL model and has a great potential to be a next‐generation model for electrolyte solutions.
Metallic core formation in differentiated bodies in the inner solar system can take place between low pressures (near 1 bar) to much higher pressures (up to 100 GPa). Most thermodynamic models of metal-silicate equilibria utilise activity coefficients for metallic tracers in Fe liquids, nearly all of which have been carried out at low pressures. This study focuses on the effect of pressure on activity coefficients for Au, P, V, Mn, Ga, Zn, Cd, Sn, W, Pb, and Nb in liquid Fe-Si alloys. From a series of experiments at 10 GPa, 2373 K containing variable Si content in a metallic liquid we have derived epsilon interaction parameters in Fe-Si liquids ($ε^{Si}_{M}$). Comparison of 1 GPa and 10 GPa data shows no difference except for Nb. Epsilon parameters derived from low pressure experiments can thus be used to calculate activity coefficients for application to higher pressure processes (at least to 10 GPa).
The high charge density of lithium ion and the resulting strong association phenomena make thermodynamic modeling of aqueous lithium electrolyte solutions extremely challenging. In this study, the association electrolyte nonrandom two-liquid activity coefficient model of Lin et al. (AIChE J. 2022, 68(2), e17422) is utilized to correlate and predict thermodynamic properties and solubility behavior of aqueous single electrolyte solutions of LiCl, LiBr, LiI, and LiNO 3 , and their mixed electrolyte solutions. Capturing self-association of water, cross-association of ion and water for hydration, and cross-association of cation and anion for ion-pairing, the association model accurately represents the literature experimental data up to saturation concentrations and at the temperature ranging from 263 K to 523 K. Here, this study further investigated the effect of anions of the lithium salts, and re-confirmed that the order of solution non-ideality as LiI > LiBr > LiCl > LiNO 3 because the anions with stronger association strengths are more likely to form ion pairs and thus lower the mean ionic activity coefficients.
Metallic core formation in differentiated bodies in the inner solar system can takeplace between low pressures (near 1 bar) to much higher pressures (up to 100 GPa). Mostthermodynamic models of metal-silicate equilibria utilize activity coefficients for metallic tracersin Fe liquids, nearly all of which have been carried out at low pressures. This study focuses onthe effect of pressure on activity coefficients for Au, P, V, Mn, Ga, Zn, Cd, Sn, W, Pb, and Nb inliquid Fe-Si alloys. From a series of experiments at 10 GPa, 2373 K containing variable Sicontent in a metallic liquid we have derived epsilon interaction parametersin FeSi liquids (εMSi). Comparison of 1 GPa and 10 GPa data shows no difference except for Nb. Epsilonparameters derived from low pressure experiments can thus be used to calculate activitycoefficients for application to higher pressure processes (at least to 10 GPa).
A test bed was constructed to measure the absorption and desorption isotherms for palladium hydride using H 2 , D 2 , and various H 2 /D 2 mixtures for temperatures in the range 20 °C ≤ T ≤ 120 °C. The pressure–composition–temperature isotherms were measured. The pressures obtained with mixtures between each pure isotope were monotonic, yet nonlinear. This nonlinear dependence of total pressure with feed gas protium concentration reveals the mixed isotope hydride system behaves nonideally. A thermodynamic model was adapted from the literature, which accounts for the nonideal nature of the mixed-isotope system. The measured data were used as constraints in this model in order to calculate the protium mole fractions in the hydride phase and the protium activity coefficients for palladium hydride at various temperatures and protium concentrations in the system. Knowing the protium mole fraction and activity coefficients allows for a priori calculation of the isotopologue distribution in the gas phase and the isotope distribution in the hydride phase, given a palladium temperature and equilibrium pressure.
Tabulated activity coefficients of electrolytes in aqueous solutions from freezing point to boiling point of solvent
Molar heat and entropy of adsorption and activity coefficient of adsorbed phase for methane-ethane- silica gel system
We introduce HANNA, the first hybrid neural network model that strictly complies with all thermodynamic consistency criteria for predicting activity coefficients and outperforms current benchmark methods in terms of accuracy and applicability.
Nonideal molecular interactions in aerosol particles influence the partitioning of semivolatile organic compounds (SVOCs). However, few direct measurements exist that determine activity coefficients (γ), which quantify nonideality, for individual organic compounds in different atmospheric mixtures. By measuring the isothermal evaporation of SOA formed from multifunctional SVOCs in an environmental chamber, this study determines the mole-fraction-based γ of the bulk SOA in a variety of pre-existing chemically complex particles, approximated as if the bulk SOA behaved like a single SVOC. These multicomponent mixtures contain molecular structures commonly found in the atmosphere. When treated as a single liquid phase, γ of the bulk SOA tends to increase from ~1 to ~5 as the organic seeds and the SOA have more differing polarities. A high computed γ value of 74 for a wet ammonium sulfate-SOA system indicates phase separation. The γ for some individual species was also quantified based on gas-phase measurements and AIOMFAC model predictions. However, the bulk SOA γ cannot be explained by the simplified speciated SVOC–seed interactions, suggesting incomplete compositional understanding of the bulk SOA. In this work, these results demonstrate a method to quantify nonideal behavior and show that it can occur in multicomponent mixtures and therefore influence OA formation, evolution, and lifetimes.
Earth's core contains approximately 10% of a light element that is likely a combination of S, C, Si, and O, with Si possibly being the most abundant light element. Si dissolved into Fe liquids can have a large effect on the magnitude of the activity coefficient of siderophile elements (SE) in Fe liquids, and thus the partitioning behavior of those elements between core and mantle. The effect of Si can be small such as for Ni and Co, or large such as for Mo, Ge, Sb, As. The effect of Si on many siderophile elements is unknown yet could be an important, and as yet unquantified, influence on the core-mantle partitioning of SE. Here we report new experiments designed to quantify the effect of Si on the partitioning of Pt (with Re and Ru in progress or planned) between metal and silicate melt. The results will be applied to Earth, for which we have excellent constraints on the mantle Pt concentrations.
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.
Earth's core contains approximately 10 percent light elements that are likely a combination of S, C, Si, and O, with Si possibly being the most abundant. Si dissolved into Fe liquids can have a large effect on the magnitude of the activity coefficient of siderophile elements (SE) in Fe liquids, and thus the partitioning behavior of those elements between core and mantle. The effect of Si can be small such as for Ni and Co, or large such as for Mo, Ge, Sb, As. The effect of Si on many siderophile elements is unknown yet could be an important, and as yet unquantified, influence on the core-mantle partitioning of SE. Here we report new experiments designed to quantify the effect of Si on the partitioning of P, Au, Pd, and many other SE between metal and silicate melt. The results will be applied to Earth, for which we have excellent constraints on the mantle siderophile element concentrations.
Metallic cores contain light alloying elements that can be a combination of S, C, Si, and O, all of which have important chemical and physical influences. For Earth, Si may be the most abundant light element in the core. Si dissolved into Fe liquids can have a large effect on the magnitude of the activity coefficient of siderophile elements (SE), and thus the partitioning behavior of those elements between core and mantle. The effect of Si on the highly siderophile elements is only beginning to be studied and the effects on Au, Pd and Pt are significant. Here we report new experiments designed to quantify the effect of Si on the partitioning of Re between metal and silicate melt. A solid understanding of Re partitioning is required for a complete understanding of the Re-Os isotopic systems. The results will be applied to understanding the HSEs and Os isotopic data for planetary mantles, and especially Earth.