Water Activity from Equilibrium Molecular Dynamics Simulations and Kirkwood-Buff Theory

Study on the Correlation between the Microstructure and Physical Properties of ZnCl2 Aqueous Solution

This article focuses on the study of the correlation between the microstructure and physical properties of aqueous zinc chloride solutions. Macroscopic physical properties of zinc chloride aqueous solution were determined, and its microstructure was analyzed by Raman spectroscopy, molecular dynamics simulations, and density functional theory (DFT) calculations. The experimental results of macroscopic physical properties show that with the increase of ZnCl2 concentration, the conductivity of aqueous solution first increases and then decreases, and the viscosity gradually increases. Raman spectrum analysis shows that with the increase of solute concentration, double donor-acceptor (DDAA)-type hydrogen bonds are continuously destroyed and the proportion of DA-type hydrogen bonds increases. The results of molecular dynamics simulations show that with the increase of solution concentration, contact ion pairs of Zn2+-Cl- (2.28 Å) gradually appear in ZnCl2 aqueous solution, and the diffusion coefficients of Zn2+ and Cl- gradually decrease. The correlation between the Raman shift and the hydration cluster model of Zn2+ was calculated theoretically by the DFT method. With the increase of the concentration, the cluster structure of Zn2+ in aqueous solution gradually changed from [Zn(H2O)6]2+ to [ZnCl2(H2O)4]. Based on experimental data and molecular dynamics simulation results, it can be concluded that the decrease in conductivity is related to the formation of Zn2+-Cl- contact ion pairs in the solution. The interactions between Zn2+, Cl-, or contact ion pairs and water molecules, namely, hydrated ions or hydrated contact ion pairs, are the microscopic essential reason for the increase in viscosity.

Computational Method for Determining the Excess Chemical Potential Using Liquid-Vapor Phase Coexistence Simulations

Molecular dynamics simulations are a powerful tool for probing and understanding the theoretical aspects of chemical systems and solutions. Our research introduces a novel method for determining the excess chemical potential of non-ideal solutions by leveraging the equivalence between the chemical potential of the vapor phase and liquid phase. Traditional approaches have relied on bulk simulations and the integration of pair distribution functions (g(r)), which are computationally intensive to obtain accurate results. In contrast, our method utilizes a liquid-gas system, where determining the vapor pressure allows for a quick and accurate calculation of the excess chemical potential relative to a reference system, e.g., pure solvent. This approach significantly reduces computational effort while maintaining high accuracy and precision. We demonstrate the effectiveness of this method using a simplified Lennard-Jones model, although the method is broadly applicable to a wide range of systems, including those with complex interactions, varying concentrations, and different temperatures. The reduced computational demands and versatility of our approach make it a valuable tool for studying non-ideal solutions, including ionic solutions in molecular simulations.

Protein Design: From the Aspect of Water Solubility and Stability

Water solubility and structural stability are key merits for proteins defined by the primary sequence and 3D-conformation. Their manipulation represents important aspects of the protein design field that relies on the accurate placement of amino acids and molecular interactions, guided by underlying physiochemical principles. Emulated designer proteins with well-defined properties both fuel the knowledge-base for more precise computational design models and are used in various biomedical and nanotechnological applications. The continuous developments in protein science, increasing computing power, new algorithms, and characterization techniques provide sophisticated toolkits for solubility design beyond guess work. In this review, we summarize recent advances in the protein design field with respect to water solubility and structural stability. After introducing fundamental design rules, we discuss the transmembrane protein solubilization and de novo transmembrane protein design. Traditional strategies to enhance protein solubility and structural stability are introduced. The designs of stable protein complexes and high-order assemblies are covered. Computational methodologies behind these endeavors, including structure prediction programs, machine learning algorithms, and specialty software dedicated to the evaluation of protein solubility and aggregation, are discussed. The findings and opportunities for Cryo-EM are presented. This review provides an overview of significant progress and prospects in accurate protein design for solubility and stability.

Fick Diffusion Coefficient in Binary Mixtures of [HMIM][NTf2] and Carbon Dioxide by Dynamic Light Scattering and Molecular Dynamics Simulations

Dynamic light scattering (DLS) experiments and equilibrium molecular dynamics (EMD) simulations were performed in the saturated liquid phase of the binary mixture of 1-hexyl-3-methylimidazolium bis(trifluormethylsulfonyl)imide ([HMIM][NTf₂]) and carbon dioxide (CO₂) to access the Fick diffusion coefficient (D₁₁). The investigations were performed within or close to saturation conditions at temperatures between (298.15 and 348.15) K and CO₂ mole fractions (x_CO2) up to 0.81. The DLS experiments were combined with polarization-difference Raman spectroscopy (PDRS) to simultaneously access the composition of the liquid phase. For the first time in an electrolyte-based system, D₁₁ was directly calculated from EMD simulations by accessing the Maxwell-Stefan (MS) diffusion coefficient and the thermodynamic factor. Agreement within combined uncertainties was found between D₁₁ from DLS and EMD simulations for CO₂ mole fractions up to 0.5. In general, an increasing D₁₁ with increasing x_CO2 could be observed, with a local maximum present at a CO₂ mole fraction of about 0.75. The local maximum could be explained by an increasing MS diffusion coefficient with increasing x_CO2 over the entire studied composition range and a decreasing thermodynamic factor at x_CO2 above 0.7. Finally, PDRS and EMD simulations were combined to investigate the influence of the fluid structure on the diffusive process.