Liquids, Volume 5, Issue 2 (June 2025) – 9 articles

Solvent association and solute–solvent complexation are known to influence the relationship between the thermodynamic functions of solvation, known as the compensation relationship. Here, we accomplish a series of works devoted to the analysis of Gibbs energy–enthalpy relations in the systems with different capabilities of hydrogen bonding. The data on proton acceptors solvated in alcohols were collected, and the quantitative regularities in their solvation thermodynamics were established, depending on the binding degree in solution. The equations connecting the Gibbs energies and enthalpies of solvation in the systems with competition for hydrogen bonding sites were derived from the previously found correlation between the thermodynamic functions of complexation and solvation in simpler solutions. These equations enabled the successful prediction of the solvation enthalpies of 56 proton acceptors in alcohols (RMSD = 1.8 kJ·mol⁻¹). Together with the results of the previous works, the general linear equation connecting the Gibbs energies and enthalpies of solvation in various solute–solvent systems has been obtained. This finding led us to reshaping common understanding of the compensation relationship phenomenon. Full article

Ionic liquids (ILs) and deep eutectic solvents (DESs) have been extensively studied as absorbents for CO₂ capture, demonstrating high efficiency in this role. To optimize the search for compounds with superior absorption properties, theoretical approaches, including machine learning methods, are highly relevant. In this study, machine learning models were developed and applied to predict Henry’s law constants for CO₂ in ILs and DESs, aiming to identify systems with the best absorption performance. The accuracy of the models was assessed in interpolation tasks within the training set and extrapolation beyond its domain. The optimal predictive models were built using the CatBoost algorithm, leveraging CDK molecular descriptors for ILs and RDKit descriptors for DESs. To define the applicability domain of the models, the SHAP-based leverage method was employed, providing a quantitative characterization of the descriptor space where predictions remain reliable. The developed models have been integrated into the web platform chem-predictor, where they can be utilized for predicting absorption properties. Full article

Carbon dioxide, the primary greenhouse gas responsible for global warming, represents today a critical environmental challenge for humans. Mitigating CO₂ emissions and other greenhouse gases is a pressing global concern. The primary goal of this study is to investigate the potential of particular ionic liquids (ILs) in capturing CO₂ for the sweetening of natural and other gases. The solubility of CO₂ was measured in three distinct ILs, which shared a common anion (triflate, TfO) but differed in their cations. The selected ionic liquids were {1-butyl-3-methylimidazolium triflate [BMIM][TfO], 1-butyl-1-methylpyrrolidinium triflate [BMP][TfO], and 1-butyl-4-methylpyridium triflate [MBPY][TfO]}. The solvents were screened based on results from a molecular computational study that predicted low CO₂ Henry’s Law constants. Solubility measurements were conducted at 303.15 K, 323.15 K, and 343.15 K and pressures up to 1.5 MPa using a gravimetric microbalance (IGA-003). The CO₂ experimental results were modeled using the Peng–Robinson Equation of state with three mixing rules: van der Waals one (vdWI), van der Waals two (vdWII), and the non-random two-liquid (NRTL) Wong–Sandler (WS) mixing rule. For the three ILs, the NRTL-WS mixing rule regressed the data with the lowest average deviation percentage of 1.24%. The three solvents had similar alkyl chains but slightly different polarities. [MBPY][TfO], with the largest size, exhibited the highest CO₂ solubility at all three temperatures. Calculation of its relative polarity descriptor (N) shows it was the least polar of the three ILs. Conversely, [BMP][TfO] showed the highest Henry’s Law constant (lowest solubility) across the studied temperature range. Comparing the results to published data, the study concludes that triflate-based ionic liquids with three fluorine atoms had lower capacity for CO₂ compared to bis(trifluoromethylsulfonyl) imide (Tf2N)-based ionic liquids with six fluorine atoms. Additionally, the study provided data on the enthalpy and entropy of absorption. A final comparison shows that the ILs had a lower CO₂ capacity than Selexol, a solvent widely used in commercial carbon capture operations. Compared to other ILs, the results confirm that the type of anion had a more significant impact on solubility than the cation. Full article

Nuclear technology, while offering significant benefits across various sectors, poses potential health risks due to uranium (U) contamination, particularly through its internalization and subsequent interactions with biological systems. This study investigates the binding of uranyl (UO₂²⁺) and zinc (Zn²⁺) ions to Human Serum Albumin (HSA) that is already bound to fatty acids (FAs), using all-atom molecular dynamics (MD) simulations. The analysis focuses on the structural and dynamic alterations in the protein’s multi-metal binding site (MBS-A) caused by FA binding. Results reveal that FA binding induces a conformational change in HSA, disrupting the pre-formed MBS-A binding site, while still allowing uranyl and zinc ions to interact with residue D249 through strong Coulombic interactions. Secondary binding sites, associated with calcium and zinc binding, remain largely unaffected by FAs, providing alternative coordination for metal ions. This study also explores the binding and unbinding pathways of the metal ions using well-tempered meta-dynamics (WT-MtD), showing that while FA binding disrupts the primary metal binding site, it does not completely inhibit the binding of both uranyl and zinc ions. These findings offer new insights into the nature of uranium’s interactions with blood serum proteins and the role of fatty acids in modulating these interactions, which may help in designing future strategies for managing uranium contamination in biological systems. Full article

Density and viscosity are fundamental properties necessary for processing of red palm oil (RPO). The main fatty acid constituents of RPO were determined to be palmitic acid (C_16:0), oleic acid (C_18:1), and linoleic acid (C_18:2). Rheology measurements confirmed that RPO behaved as a Newtonian fluid. Viscosities and atmospheric densities of RPO were measured at 0.1 MPa and (293 K to 413) K and correlated with the Rodenbush model (0.05% deviation). Dynamic viscosities of RPO were correlated with the Vogel–Fulcher–Tammann model (0.06% deviation) and Doolittle free volume model (0.04% deviation). High-pressure densities of RPO were measured at (10 to 150) MPa and (312 to 352) K. The Tait equation could correlate the high-pressure densities of RPO to within 0.021% deviation and was used to estimate the thermal expansion as 5.1 × 10⁻⁴ K⁻¹ (at 312 K, 150 MPa) to 4.8 × 10⁻⁴ K⁻¹ (at 352 K, 150 MPa) and isothermal compressibility as 7.3 × 10⁻⁴ MPa⁻¹ (at 352 K, 0.1 MPa) to 3.5 × 10⁻⁴ MPa⁻¹ (at 352 K, 150 MPa). Parameters for the perturbed-chain statistical associating fluid theory equation of state were determined and gave an average of 0.143% deviation in density. The data and equations developed should be useful in high-pressure food processing as well as in applications considering vegetable oils as heat transfer fluids or as lubricants. Full article

This work is a continuation of our recent work on the prediction of hydrogen-bonding (HB) interaction enthalpies. In the present work, a simple method is proposed for the prediction of the HB interaction free energies. Quantum chemical (QC) calculations are combined with the Linear Solvation Energy Relationship (LSER) approach for the determination of novel QC-LSER molecular descriptors and the development of the method. Each hydrogen-bonded molecule is characterized by an acidity or proton donor capacity, ${\alpha }_G$, and/or a basicity or proton acceptor capacity, ${\beta }_G$. These descriptors suffice for the prediction of HB interaction free energy when the interacting molecules possess one acidic and or one basic site. In this case of two interacting molecules, 1 and 2, their overall HB interaction free energy is $c\left({\alpha }_{G1}{\beta }_{G2}+{\beta }_{G1}{\alpha }_{G2}\right)$, where c is a universal constant equal to (ln10)RT = 5.71 kJ/mol at 25 °C. This holds true over the full composition range, that is, regardless of which molecule is solute and which solvent. In the case of complex multi-sited molecules possessing more than one distant acidic site and/or more than one type of distant basic sites, two sets of ${\alpha }_G$ and ${\beta }_G$ descriptors are needed, one for the molecule as solute in any solvent and one for the same molecule as the solvent of any solute. Descriptors ${\alpha }_G$ and ${\beta }_G$ are reported for a number of common hydrogen-bonded molecules but they may be obtained for any other hydrogen-bonded molecule of interest from its molecular surface charge distribution already available or easily obtained via relatively cheap DFT/basis-set QC calculations. The new predictive scheme is validated against corresponding estimations of the widely used Abraham’s LSER model. The developments in the present work and the previous one are useful for solvation studies in chemical and biochemical systems and, particularly, for equation-of-state developments in molecular thermodynamics. The strengths and limitations of the new predictive method are critically discussed. Full article

This study investigated the role of synthetic mucus coatings in enhancing the physiological relevance of in vitro nasal spray deposition assessments using 3D-printed nasal cavity models. Synthetic mucus solutions, representing normal (0.25% w/v xanthan gum) and diseased (1% w/v xanthan gum) nasal conditions, were developed to mimic the viscoelastic properties of human nasal mucus. Their physical properties, including viscosity, surface tension, contact angle, and adhesivity on dry and synthetic mucus-coated stereolithography (SLA) surfaces, were systematically characterized. Comparative experiments evaluated the behavior of saline drops and liquid films on dry versus synthetic mucus-coated SLA surfaces at inclinations of 30°, 45°, and 60°. Observational deposition experiments using anatomically accurate nasal models were conducted under a 45° backward-tilted head position with gentle sniff airflow across uncoated, 0.25% w/v mucus-coated, and 1% w/v mucus-coated surfaces. Synthetic mucus coatings significantly influenced saline spray deposition patterns. On uncoated surfaces, deposition consisted of scattered droplets and limited film formation, mainly in the anterior and turbinate regions. In contrast, synthetic mucus coatings facilitated broader and more uniform liquid distribution due to diffusion and lubrication effects. These findings highlight the value of synthetic mucus coatings for better simulating nasal environments, offering insights to optimize nasal spray formulations and delivery devices. Full article

The well-known Poisson–Nernst–Planck model is a classical approach usedto describe ion transport in liquids. Extended versions of this model account for thegeneration–recombination of ions at equilibrium. In this paper, we investigate the influenceof the generation–recombination term on dielectric relaxation in an electrolytic cell shapedlike a slab, bounded by two parallel blocking electrodes. We show that in the adiabaticlimit—which holds when the reaction time is much longer than the dielectric relaxationtime—the electric current in the external circuit does not follow a simple relaxation mechanism.Instead, it is characterized by two distinct relaxation times: a short relaxationtime associated with dielectric relaxation and a longer relaxation time related to the iondissociation–association process. Conversely, this information could be used to assess thepresence and/or significance of the generation–recombination effect in an electrolytic cell. Full article

This work provides a comprehensive picture of the advances that the exponential expansion theory (EET) of autocorrelation functions relevant to liquids dynamics made possible in the last decade up to very recent times. The role of both longitudinal and transverse collective excitations in liquids is investigated by studying the main autocorrelation functions typically obtained either experimentally (when possible) or through molecular dynamics simulations. Examples for some classes of liquids are provided, especially intended for the understanding of dispersion curves, i.e., the collective mode frequencies as a function of the wavevector Q, which is inversely proportional to the length scale at which microscopic processes are probed. The main result of this work is the ubiquitous observation that the EET method works extremely well for all considered autocorrelation functions or spectra, either experimental or simulated. This paper provides also, in its final part, important hints for future research, based on an integration of the EET lineshape description within Bayesian inference analysis. Full article