The Journal of Physical Chemistry B最新文献

Proton-pumping rhodopsins, which consist of seven transmembrane helices and have a retinal chromophore bound to a lysine side chain through a Schiff base linkage, offer valuable insights for developing unidirectional ion transporters. Despite identical overall structures and membrane topologies of outward and inward proton-pumping rhodopsins, these proteins transport protons in opposing directions, suggesting a rational mechanism that enables protons to move in different directions within similar protein structures. In the present study, we clarified the chromophore structures in early intermediates of inward and outward proton-pumping rhodopsins. Most importantly, common to both pumps, the hydrogen bond of the Schiff base became stronger in the L intermediate than in the unphotolyzed state. Experimental data on the chromophore structures of the L intermediates and proton-pumping activities indicated that the direction of proton release from the Schiff base during the L-to-M transition is determined not by the structure of the retinal chromophore but by the number of negative charges on the extracellular side of the Schiff base. This is in contrast to the idea that the chromophore configuration is a determinant for the direction of proton uptake. The present study, together with our previous studies, clarifies the determining factors of the transport direction in inward and outward proton-pumping rhodopsins.

The oxidation of hydroxylamine was studied by quantum chemical modeling. Hydroxylamine is the product of ammonia oxidation in ammonia monooxygenase. That mechanism has been studied recently by quantum chemical modeling as here. Only two enzymes can oxidize hydroxylamine, hydroxylamine oxidase and cytochrome-P460. Both employ the unusual P460-heme cofactor. In hydroxylamine oxidase, there is a covalently linked tyrosine, while in cytochrome-P460, there is a covalently linked lysine. The calculations give explanations for the experimental findings that NO is the final product in hydroxylamine oxidase, while N₂O is the final product in cytochrome-P460. The effect of the covalent attachments has been investigated, and reasons for their presence have been given. The methodology used, which was proven to give very good agreement with experiments for several redox enzymes, again leads to excellent agreement with experimental findings.

Methods for predicting Henry's law constants H_ij describing the solubility of solutes i in solvents j as a function of temperature are essential in chemical engineering. While isothermal properties of binary mixtures can conveniently be predicted with matrix completion methods (MCMs) from machine learning, we advance their application to the temperature-dependent prediction of H_ij in the present work by combining them with physical equations describing the temperature dependence. For training the methods, experimental H_ij data for 122 solutes and 399 solvents ranging from 173.15 to 573.15 K were taken from the Dortmund Data Bank. Two MCMs are proposed: a data-driven MCM that relies solely on experimental data and a hybrid MCM that incorporates predictions from the established Predictive Soave-Redlich-Kwong (PSRK) equation of state (EoS), effectively combining physical knowledge and machine learning. The performance of these MCMs is assessed via leave-one-out analysis and compared to that of the PSRK-EoS, demonstrating superior prediction accuracy.

¹H and ¹⁹F spin-lattice relaxation experiments have been performed for a series of ionic liquids: [HMIM][TFSI], [OMIM][TFSI], and [DMIM][TFSI] including the same anion and cations with progressively longer alkyl chains. The experiments were performed in a wide frequency range from 10 kHz to 10 MHz (referring to the ¹H resonance frequency) versus temperature. This extensive data set has been analyzed in terms of a theoretical model including all relevant homonuclear (¹H-¹H and ¹⁹F-¹⁹F) and heteronuclear (¹H-¹⁹F) relaxation pathways and linking the relaxation features to the relative translational diffusion between the ion pairs (cation-cation, cation-anion, and anion-anion). In addition to the comprehensive theoretical approach, closed-form expressions have been provided and applied to determine the diffusion coefficients from the slopes of the linear dependences of the relaxation rates on the square root of the resonance frequency. The combined experimental and theoretical studies have led to the determination of the complete set of diffusion coefficients, forming a consistent picture of the dynamical scenario. In addition to revealing the dynamical properties of the liquids and the influence of the subtle changes in the cation structure on the movement of both cations and anions, the theoretical means for exploiting Nuclear Magnetic Resonance relaxometry for ionic liquids have been provided.

In this work, the influence of protonation on the kinetics and thermodynamics of extraction of the Am/Eu pair using N-heterocyclic dicarboxylic acid diamide N,N'-diethyl-N,N'-bis(4-ethylphenyl)-[2,2'-bipyridine]-6,6'-dicarboxamide (L) was investigated. The extraction efficiency of the ligand did not decrease, even at a nitric acid concentration 4 times higher than that of the ligand in the organic phase. X-ray diffraction analysis established that protonation leads to the preorganization of the ligand due to the reversal of bipyridyl rings into the binding conformation when both nitrogen atoms are turned to one side. Also, the effect of protonation on the chemical shifts of the functional binding groups (bipyridyl and amide) in solution was demonstrated by NMR spectroscopy. However, the presaturation of the organic phase with nitric acid did not lead to significant changes in the surface activity of the ligand. For extraction kinetics, a mechanism was proposed in which protonation and preorganization of the ligand was the limiting stage.

As a predictive tool, quantum chemical calculations can be used to design protic ionic liquids (PILs) and predict the result. By adding anionic negative potential sites, two dual-functional PILs diethylenetriamine-barbituric acid [C₄H₁₄N₃]₂[C₄H₂N₂O₃] and diethylenetriamine-ethylenolactonium [C₄H₁₄N₃]₂[C₃H₂N₂O₂] were designed. The simulation results indicated that multisite absorption of anions and cations resulted in an expected absorption ratio exceeding 3:1 (mol CO₂:mol ILs). Furthermore, the Gibbs free energy and enthalpy barrier were calculated. Based on this, the two PILs were synthesized in a controlled manner, and the experimental results demonstrated that 0.25 mol/L [C₄H₁₄N₃]₂[C₄H₂N₂O₃] and [C₄H₁₄N₃]₂[C₃H₂N₂O₂] exhibited a superior CO₂ absorption capacity of 3.152 and 3.466 mol CO₂/mol ILs, respectively. After five adsorption-desorption experiments, the regeneration rates of [C₄H₁₄N₃]₂[C₃H₂N₂O₂] were all higher than 90%. Finally, the reaction mechanism for CO₂ capture in these PILs was revealed that the significant increase in capacity could be attributed to the combined absorption of double negative potential N atoms on anions and primary and secondary amines on cations by using ¹³C NMR.

The glacial phase can be formed from supercooled liquid (SCL) in certain systems, which is called liquid-liquid transition (LLT). Revealing the nature of the glacial phase especially in a single-component system is crucial for understanding the LLT process. Here, by using flash differential scanning calorimetry and cold-field transmission electron microscopy, the structure of the d-mannitol glacial phase and the phase transition kinetics between the glacial phase and SCL were studied. We found that the glacial phase is a fluctuating spinodal-like structure. And the glacial phase displays a first-order melting characteristic when it transforms into the SCL. Furthermore, the LLT diagram in the enthalpy-temperature coordinate system is constructed based on the nucleation-growth and spinodal-decomposition transitions. Our findings provide new insight into the LLT process of the glass forming liquids.

When water is confined in a nanochannel, its thermodynamic and kinetic properties change dramatically compared to the macroscale. To investigate these phenomena, we conducted nonequilibrium molecular dynamics simulations on the heat transfer in copper-water nanochannels with lengths ranging from 12 to 20 nm in the absence and presence of an electric field. The results indicate that in the absence of an electric field (L_z = 12-20 nm), the binding force between water molecules in the 20 nm nanochannel is the weakest, facilitating thermal motion in the liquid phase. When compared to the 12 nm nanochannel, the enhancement rate of the thermal conductivity is 19.53%. In the presence of a uniform electric field in the positive z-direction (L_z = 12-16 nm), water molecules in the 16 nm nanochannel are more readily frozen into ice crystal structures. This change in the mode of heat transfer shifts from the thermal diffusion of water molecules to the vibrations between copper atoms and the ice crystal, resulting in a significant increase in the thermal conductivity of water.

This study addresses a critical gap in the existing literature on carbon dioxide and ionic liquid (IL) mixtures, where fragmented and incomplete data, particularly for flow properties, hinder practical applications. Therefore, this work aimed to establish a robust and efficient method for predicting the density of the CO₂-IL mixtures across diverse operating conditions and IL families using novel validation techniques. Both linear and symbolic regression models provided relevant insights but failed to accurately capture the IL-CO₂ interactions in a mixture that determine the molar volume of CO₂ at infinite dilution when solubilized by a given IL. Therefore, more mathematically flexible artificial neural networks (ANN) were trained based on three different sets of features: (1) IL critical properties, (2) IL structural descriptors, and (3) a selective combination of (1) and (2). While all models showed relative deviations consistently below 3% for the testing data, combining critical and structural data significantly improved accuracy (R² = 0.986, testing data set). A postprocessing outlier-handling method enhanced model performance, removing a minimal fraction (below 0.2%) of unphysical data points. Furthermore, molecular dynamics simulations validated the robust generalization of all ANN models, with the combined model exhibiting remarkable accuracy over operating conditions outside the training ranges for ILs in the training set and even for ILs that are not included in this data set. This computational approach provides a significantly faster and broader alternative to other thermodynamical tools, establishing a solid method for future machine learning (ML)-based property prediction augmented by external validation from cross-comparison tests and statistical thermodynamics models.

Analogous to the aqueous solution where the pH of the solvent affects its multiple behaviors, the optical acidity and basicity of molten salts also greatly influence their thermophysical and thermochemical properties. In the study, we develop ion probes to quantitatively determine the acidity-basicity scale of molten NaCl-xAlCl₃ (x = 1.5-2.1) salt using in situ ultraviolet visible (UV-vis) spectroscopy. With the accumulation of acidity-basicity data of NaCl-AlCl₃ molten salt for a variety of compositions, the correlation between the acidity-basicity of salt and its measured fundamental properties is derived. To understand the physical and chemical features controlling the acidity-basicity variations, the local structures of NaCl-xAlCl₃ molten salts with different chemical compositions are investigated in terms of bonded complexes and coordination numbers. The comprehensive understanding of the correlation between composition, acidity-basicity, fundamental properties, and local structures of molten salt can serve for the full screening and online monitoring of salt melt in extreme environments by simply measuring the salt acidity-basicity as developed in this study.