Liquids, Volume 2, Issue 3 (September 2022) – 10 articles

Hydrated zinc(II) cations, due to their importance in biological systems, are the subject of ongoing research concerning their hydration shell structure and dynamics. Here, ab initio molecular dynamics (AIMD) simulations are used to study solvent exchange events around aqueous Zn²+, for which observation in detail is possible owing to the considerable length of the generated trajectory. While the hexacoordinated Zn(H₂O)₆²+ is the dominant form of Zn(II) in an aqueous solution, there is a non-negligible contribution of the pentacoordinated Zn(H₂O)₅²+ complex which presence is linked to the dissociative solvent exchange events around Zn²+. The pentacoordinated Zn(II) has a much tighter hydration sphere and is characterized by a trigonal bipyramidal structure, in contrast to the usual octahedral symmetry of the hexacoordinated complex. In total, two full exchange events are registered in the analyzed trajectory. AIMD simulations on an adequate length scale thus provide a direct way of studying such solvent exchange events around ions in molecular detail. Full article

This review article summarizes the reported crystallographically determined structures of compounds containing a hydrated metal ion and the reported structures of hydrated metal ions in aqueous solution. A short overview of the methods available to study structures of metal complexes in solution is given. Full article

In this article, the stability of sols of detonated nanodiamonds, DND, with positively charged colloidal particles, is studied in different salt solutions in water–dimethyl sulfoxide (DMSO) binary systems containing 95 vol.% organic solvent. Additionally, several CCC values are determined in 95 vol.% acetonitrile for comparison. The critical coagulation concentrations (CCC) are determined using the dynamic light scattering technique and the Fuchs function. As coagulators, NaCl, NaBr, NaNO₃, NaClO₄, Nan-C₈H₁₇SO₃, and Nan-C₁₂H₂₅OSO₃ are used. Comparison of the CCC values in DMSO–H₂O and CH₃CN–H₂O with those obtained in water allows us to make some conclusions. The variations of these values in different solvents are explained in terms of good and poor interfacial solvation of colloidal particles, “structural” contribution to the interparticle interaction energy, lyotropic series for anions, and more or less pronounced adsorption of surfactants. The study of the stability of DND hydrosol in solutions of anionic surfactants with different hydrocarbon tail length demonstrated the crucial role of adsorption in the coagulation process. Full article

Globally, multiple efforts are being made to develop active atmospheric water generation (AWG) or atmospheric water extraction (AWE) systems, particularly using direct air-cooling technology to produce water from ambient air. However, this legacy technique is highly energy-intensive; it can only be operated when the local dew point is above the freezing point of water, and does not scale to create enough water to offer solutions for most industries, services, or agriculture. Liquid-desiccant-based AWG methods show promising performance advantages, and offer a versatile approach to help address the thermodynamics, health risks, and geographic constraints currently encountered by conventional active AWG systems. In this study, we performed a techno-economic analysis of a liquid-desiccant-based AWG system with a continuous operating style. An energy balance was performed on a single design point of the AWG system configuration while using a LiCl liquid desiccant loaded with multiwalled carbon nanotubes (MWCNTs). We showed that the MWCNTs can be doped in LiCl for effective heat transfer during water desorption, resulting in lowering of the sensible heat load by ≈49% on the AWG system. We demonstrated that the specific energy consumption (SEC) can currently be obtained as low as 0.67 kWh per US gallon, while changing the inlet desiccant stream concentration of MWCNT-doped LiCl under the given conditions. While the production cost of water (COW) showed a significant regional dependency, economic analysis revealed that water can be produced at a minimum selling price of USD 0.085 per US gallon, based on the 2021 annual average wholesale electricity cost of USD 0.125 per kWh in the U.S.A., thereby providing a strong foundation for future research to meet desirable and competitive water costs by 2026, but before 2031. Full article

Meloxicam is widely prescribed as an analgesic and anti-inflammatory drug in human therapeutics. Owing the very low aqueous solubility of meloxicam, this property has been studied in dimethyl sulfoxide (DMSO)-aqueous solvent systems at several temperatures from 273.15 to 313.15 K to expand the solubility database about analgesic drugs in mixed solvents. The flask shake method followed by ultraviolet-visible (UV-vis) spectrophotometry analysis were used for meloxicam solubility determinations. A number of cosolvency models, including the Jouyban–Acree model, were challenged for solubility correlation/prediction of this drug in these mixtures. The van’t Hoff and Gibbs equations were employed to calculate the apparent standard thermodynamic quantities relative to dissolution and mixing processes. The inverse Kirkwood–Buff integral method was employed for calculating the preferential solvation parameters of meloxicam by DMSO in the mixtures. Meloxicam solubility increases with increasing temperature and maximum solubilities are observed in neat DMSO at all temperatures studied. Dissolution processes were endothermic in all cases and entropy-driven in the composition interval of 0.40 ≤ x₁ ≤ 1.00. A nonlinear enthalpy–entropy relationship was observed in the plot of enthalpy vs. Gibbs energy for drug transfer processes. Meloxicam is preferentially solvated by water in water-rich mixtures but preferentially solvated by DMSO in the composition interval of 0.21 < x₁ < 1.00. Full article

Data-driven flow forecasting models, such as Artificial Neural Networks (ANNs), are increasingly used for operational flood warning systems. In this research, we systematically evaluate different machine learning techniques (random forest and decision tree) and compare them with classical methods of the NAM rainfall run-off model for the Vésubie River, Nice, France. The modeled network is trained and tested using discharge, precipitation, temperature, and evapotranspiration data for about four years (2011–2014). A comparative investigation is executed to assess the performance of the model by using Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and a correlation coefficient (R). According to the result, Feed Forward Neural Network (FFNN) (a type of ANN) models are less efficient than NAM models. The precision parameters correlation coefficient of ANN is 0.58 and for the NAM model is 0.76 for the validation dataset. In all machine learning models, the decision tree which performed best had a correlation coefficient of 0.99. ANN validation data prediction is good compared to the training, which is the opposite in the NAM model. ANN can be improved by fitting more input variables in the training dataset for a long period. Full article

Published solubility data for 4,5-dihydroxyanthraquinone-2-carboxylic acid dissolved in several organic solvents of varying polarity and hydrogen-bonding character are used to calculate the Abraham model solute descriptors. Calculated descriptor values suggest that 4,5-dihydroxyanthraquinone-2-carboxylic acid engages in intramolecular hydrogen formation between the two phenolic hydrogens and the proton acceptor sites (the lone electron pairs) on the neighboring quinone oxygen atom. Our study further shows that existing group contribution and machine learning methods provide rather poor estimates of the experimental-based solute descriptors of 4,5-dihydroxyanthraquinone-2-carboxylic acid, in part because the estimation methods to not account for the likely intramolecular hydrogen-bonds. The predictive aspect of the Abraham model is illustrated by predicting the solubility of 4,5-dihydroxyanthraquinone-2-carboxylic acid in 28 additional organic mono-solvents for which experimental data does not exist. Full article

In this article, we raise awareness about the misuses of frequently invoked criteria for structure making/breaking phenomena, resulting from the absence of any explicit cause–effect relationship between the proposed markers and the microstructural perturbation of the solvent induced by the solute. First, we support our assessment with rigorous molecular-based foundations to determine, directly and quantitatively, the solute-induced perturbation of the solvent structure leading to an unambiguous definition of a structure making/breaking event. Then, we highlight and discuss the sources of concealed ambiguities in two of the most frequently invoked structure making/breaking criteria, i.e., Hepler’s thermal expansivity-based and Jones–Dole’s $B$ coefficient-based markers. Finally, we illustrate how the implementation of rigorous molecular-based arguments, in conjunction with the available experimental evidence on a variety of aqueous species at infinite dilution, rule out the validity of these two criteria as structure making/breaking markers and suggest their discontinuation to avoid the perpetuation of myths. Full article

Abraham model L solute descriptors have been determined for 149 additional C₁₁ to C₄₂ monomethylated and polymethylated alkanes based on published Kovat’s retention indices based upon gas–liquid chromatographic measurements. The calculated solute descriptors, in combination with previously published Abraham model correlations, can be used to predict a number of very important chemical and thermodynamic properties including partition coefficients, molar solubility ratios, gas–liquid chromatographic and HPLC retention data, infinite dilution activity coefficients, molar enthalpies of solvation, standard molar vaporization and sublimation at 298 K, vapor pressures, and limiting diffusion coefficients. The predictive computations are illustrated by estimating both the standard molar enthalpies of sublimation and the enthalpies of solvation in benzene for the monomethylated and polymethylated alkanes considered in the current study. Full article

Residence time of water flow is an important factor in subsurface media to determine the fate of environmental toxins and the metabolic rates in the ecotone between the surface stream and groundwater. Both numerical and lab-based experimentation can be used to estimate the residence time. However, due to high variability in material composition in subsurface media, a pragmatic model set up in the laboratory to trace particles is strenuous. Nevertheless, the selection and inclusion of input parameters, execution of the simulation, and generation of results as well as post-processing of the outcomes of a simulation take a considerable amount of time. To address these challenges, an automated particle tracing method is developed where the numerical model, i.e., flow and reactive transport code, MIN3P, and MATLAB code for tracing particles in saturated porous media, is used. A rectangular model domain is set up considering a fully saturated subsurface media under steady-state conditions in MIN3P. Streamlines and residence times of the particles are computed with a variety of seeding locations covering the whole model surface. Sensitivity analysis for residence time is performed over the varying spatial discretization and computational time steps. Moreover, a comparative study of the outcomes with Paraview is undertaken to validate the automated model (R² = 0.997). The outcome of the automated process illustrates that the computed residence times are highly dependent on the accuracy of the integration method, the value of the computational time step, ∆t, spatial discretization, stopping criterion for the integration process of streamlines, location, and amount of seed points. The automated process can be highly beneficial in obtaining insights into subsurface flow dynamics with high variability in the model setup instead of laboratory-based experimentation in a computationally efficient manner. Full article