Journal of Solution Chemistry最新文献

In this investigation, we deployed four advanced statistical physics models within the grand canonical ensemble to scrutinize the adsorption forces and thermodynamics governing the removal of hydroquinone (1,4-benzenediol, HYD) onto the biochar surface, contributing to advancements in water remediation. Our main findings demonstrated the effectiveness of a monolayer model with a single-site energy distribution for describing, at the molecular scale, the binding mechanism within biochar pores. By leveraging this framework, we successfully computed the key steric parameters and derived essential thermodynamic functions (molar entropy, molar internal energy, and Gibbs free energy). Thermodynamic analysis revealed that the microscopic docking of hydroquinone onto the adsorbent’s available sites is a spontaneous, endothermic (heat-consuming), and energetically favorable process. Furthermore, the magnitude of the internal energy confirms physisorption, in which weak physical interactions (van der Waals forces) primarily govern surface occupancy. Analysis of the pore size distribution (PSD) indicated that pine biochar is primarily composed of macropores, while the observed distribution of adhesion energies (AED) provided strong evidence supporting the physisorption mechanism.

It is imperative to state that chromium(VI) effluent is a long-known toxic oxide not only to aquatic spaces but also to the human system. The study aligns with the sustainable development goal 3 that emphasises the physical condition and well-being of man. It investigates the reduction of Cr⁶⁺ ion with bisulphite (({text{HSO}}_{3}^{ - })) and exposes the possibility of electrostatic, hydrophobic, or hydrophilic behaviour of the Cr⁶⁺-bearing effluent in micellar milieu. The studied kinetic parameters reveal a first-order reaction with respect to the concentration of Cr⁶⁺ and ({text{HSO}}_{3}^{ - }) and a one-to-one stoichiometric mole ratio. The population of electrolyte and acid concentration leads to neutral and acceleratory effects on the reduction rate, respectively, whereas the aggregation of surfactant monomers (sodium dodecyl sulphate) aids the reduction rate efficiently. The binding affinity of the substrate with the micelles is strengthened by Piszkiewicz’s and Srinivasan-Raghavan’s models. The evidence of free radicals and the intermediate species are positive and transient, respectively. However, total trapping of Cr⁶⁺ in a green reaction system is sustainable and efficient for greater accessibility of a clean environment. The non-spontaneity of the reduction process with unstable transition molecules is supported by the thermodynamic parameters (ΔH^* = +29.69 ± 0.004 kJ·mol⁻¹, ΔG^* = +71.58 ± 0.004 kJ·mol⁻¹, and ΔS^* = −139.65 ± 0.005 K⁻¹·mol⁻¹). Availability of intermediates is underscored, as the Michaelis–Menten type plot (MMTP) suggested.

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Solubility data were experimentally acquired at ambient temperature using alcohols (2-propanol and 2-butanol) + carbohydrates (glucose and sucrose). The tie-lines were also obtained for solvation data. Additionally, the Othmer–Tobias and Bancroft equations were utilized to match tie-line data and to judge the reliability of the computational approach and related tie-line data. Also, experimental results were correlated with the thermodynamic UNIQUAC and NRTL models, and the precision of the NRTL model was higher than that of the UNIQUAC model.

High molecular weight polymers (HMWPs) exhibit exceptional adsorption properties, enabling them to bind cement particles into a cohesive mass, thereby significantly enhancing the washout resistance of concrete mixtures. This study investigates the mechanism of polymer adsorption on the washout resistance of ultra-high-performance concrete (UHPC) using polymers at dosages of 0%, 1.5%, 2.5%, and 3%. Techniques such as mechanical strength testing, mercury intrusion porosimetry (MIP), water absorption analysis, scanning electron microscopy (SEM), X-ray diffraction (XRD), and energy-dispersive spectroscopy (EDS) were employed to explore the underlying mechanisms. The results indicate that while HMWPs do not significantly alter cement hydration, they absorb water from the surrounding slurry, reducing the flowability of UHPC by 16.8%, 24%, and 33.7% at polymer dosages of 1.5%, 2.5%, and 3%, respectively. Porosity increased from 15.87% to 16.92%, 17.34%, and 18.42%, leading to compressive strength reductions of 4.3%, 5.3%, and 20.1%, respectively. Despite these changes, HMWPs effectively adsorb cement particles, enhancing underwater washout resistance with mass losses reduced to 0.0%, 18.6%, 7.7%, and 0.2% at the respective dosages. These findings underscore the potential of HMWP in optimizing underwater UHPC applications.

The growing emphasis on sustainable solvents in modern organic synthesis demands a deeper understanding of structure–property relationships to guide reaction outcomes. While solvent polarity is a critical parameter, it cannot be fully captured using conventional physical constants. The empirical E_T(30) parameter is a reliable benchmark, but its experimental determination is labor-intensive. Although deep learning models have been proposed for prediction, they often sacrifice interpretability. To address this, Inter-Pol, an interpretable machine learning framework, has been developed. Inter-Pol integrates 1618 features from RDKit, Mordred, PyBioMed, and CDK, followed by rigorous feature selection, which eliminates 1191 fingerprint features from Morgan, Avalon, and MACCS. After feature selection, Inter-Pol employs a rule-based RuleFit model within an interpretable framework. The model generates human-readable rules, such as “LogP > threshold, then high E_T(30), such as 42,” that link molecular descriptors to polarity outcomes, enhancing both transparency and usability in solvent selection. These rules not only explain how and why the model produces its predictions but also provide actionable guidance for E_T(30) optimization. For example, removing hydrogen bond donor groups can result in higher LogP values, reflecting increased polarity, which in turn contributes to higher ET(30) values, as guided by the rules extracted from Inter-Pol. Thus, the interpretable rules derived from Inter-Pol serve not only as predictive components but also as a practical tool for rational solvent design and experimental planning. Across both the 2022 and 2023 benchmarks used in the state-of-the-art paper, the Inter-Pol framework consistently delivers competitive predictive performance–achieving test set (text{R}^2) values of 0.965 and 0.929, respectively–surpassing the 2022 Neural Network benchmark ((text{R}^2 = 0.88)) and approaching the 2023 Neural Network performance ((text{R}^2 = 0.952)), while offering enhanced interpretability through its transparent, rule-based architecture. These results confirm Inter-Pol’s effectiveness in balancing interpretability and accuracy, offering a robust framework for solvent selection in cheminformatics and synthesis.

The thermodynamic properties of electrolyte solutions elucidate the mechanisms of ionic interactions in solution. This study investigates the thermodynamic properties of the ternary systems containing cesium bromide (CsBr), water, and either 1,2-butanediol (1,2-BDO) or 1,4-butanediol (1,4-BDO) at 298.2 K utilizing potentiometric techniques. CsBr molalities were in the approximate range of 0.01 to 1 mol·kg⁻¹, and the mass fraction of 1,2-BDO/1,4-BDO in 1,2-BDO/1,4-BDO+H₂O binary mixed solvents were 0, 0.10, 0.20, and 0.30. The Debye-Hückel model, the Pitzer model, along with the Nernst equation were explored to determine the thermodynamic parameters, which included the mean ionic activity coefficients (γ_±), osmotic coefficients (φ), excess Gibbs free energy (G^E), standard Gibbs free energy of transference (ΔG ⁰_t ), and primary hydration number (n_hydr). The results reveal that the γ_± of CsBr decreases with increasing the molality of CsBr and with increasing the mass fraction of 1,2-BDO and 1,4-BDO in the binary mixture. A positive value for the ΔG ⁰_t signifies that the transfer of CsBr from pure water to the mixed solvent system is thermodynamically unfavorable and thus non-spontaneous. These findings can provide thermodynamic data to support potential industrial processes.

Thermal properties and phase equilibria (vapor–liquid, solid–liquid, and liquid–liquid equilibria) of strong aqueous electrolyte systems are computed by applying the excess Gibbs free energy combined with the non-electrolyte UNIQUAC–NRF model [Mazloumi, S.H. Fluid Phase Equilibria, 2016, 417: 70–76] as the short-range term and the Pitzer–Debye–Hückel equation as the long-range forces at different molalities and temperatures. The two binary interaction temperature-dependent adjustable parameters are computed by correlating the experimental data of thermal properties, solubility of salt, liquid–solid, vapor–liquid, and liquid–liquid equilibrium of binary aqueous electrolyte solutions at different molality and temperatures. Applying this model to the methanol–water solution containing the (NO₃, Cl, HCO₃, K, Na, SO₄, (CO₂)₃, NH ₄) ions and hydrocarbons reveals that the non-electrolyte UNIQUAC–NRF model can be an accurate representation of the vapor–liquid, liquid–liquid, solid–liquid equilibrium, and thermal properties in multi-component mixtures by applying the binary interaction parameters.

This study evaluated the solubility of amlodipine besylate (AMB) in binary solvent mixtures of polyethylene glycol (PEG) 200 and ethanol, as well as PEG 200 and 1-propanol, at five distinct temperatures. The solubility of AMB was assessed via the shake-flask method, and the concentrations of AMB in the solutions were measured using a UV–Vis spectrophotometer. The results demonstrated that the solubility of AMB in both binary solvent combinations increased with greater concentrations of PEG 200 and raised temperatures. The collected data were used in several mathematical models to predict solubility. The mathematical models yielded precise predictions regarding the solubility of AMB in various binary solvent systems, with mean relative deviations (MRDs%) below 11.6. The experimental data acquired for AMB dissolution included several thermodynamic properties, for example, standard Gibbs free energy (ΔG°), enthalpy (ΔH°), and entropy (ΔS°) variations. These features provide significant insights into the energy dimensions of the breakdown process.