Singularity of liquid water-data analysis and modelling

Accurate and efficient simulation of liquids, such as water and salt solutions, using high-level wave function theories is still a formidable task for computational chemists owing to the high computational costs. In this study, we develop a deep machine learning potential based on fragment-based second-order Møller-Plesset perturbation theory (DP-MP2) for water through neural networks. We show that the DP-MP2 potential predicts the structural, dynamical, and thermodynamic properties of liquid water in better agreement with the experimental data than previous studies based on density functional theory (DFT). The nuclear quantum effects (NQEs) on the properties of liquid water are also examined, which are noticeable in affecting the structural and dynamical properties of liquid water under ambient conditions. This work provides a general framework for quantitative predictions of the properties of condensed-phase systems with the accuracy of high-level wave function theory while achieving significant computational savings compared to ab initio simulations.

Coarse-grained water models offer opportunities to study the molecular processes in water on spatial and temporal scales inaccessible to conventional atomic-level simulations. Such a model that can accurately describe the structural, electrostatic and thermodynamic properties of liquid water is difficult to derive but invaluable. Here, we present FlexDQ, a flexible three-site coarse-grained model, representing clusters of water molecules. This model was derived using a full bottom-up approach in which atomistic information of water molecules is processed using clustering techniques based on considerations of both energy and geometry and a mapping algorithm that encodes information of dipole and quadrupole moments of water clusters into coarsely grained interaction sites. Parameterization of FlexDQ was conducted consistently and systematically, augmented by these data. The resulting model reproduces not only dipolar and quadrupolar fluctuations of water clusters, but also their local structural correlations in the bulk phase and, to a good extent, pressure-related properties, dielectric permittivity and water-air interfacial properties that were not targeted for parameterization. The ability of our model to reproduce various properties of water has been shown to originate from its explicit treatment of electrostatics. Coupled with the popular MARTINI CG model, FlexDQ captures the entropy-enthalpy balance of hydrophobic interactions and describes the dielectric behavior of water at the water-membrane interface, yielding a positive internal electrostatic potential in membranes, which is otherwise difficult to reproduce using MARTINI alone. Together, the FlexDQ model and its development framework reported here show promise for studies on the biomolecules in water.

Nowadays, although our understanding on liquid water have lots of progresses due to the development of experimental tools and computer simulation techniques, the molecular level structure of water, its heterogeneity, is still elusive. In the end of the nineteenth century, Rntgen proposed that the water is a mixture of two molecular complexes, which cannot be confirmed by experiments at that time. In the middle of the twentieth century, Bernal and his followers regarded the structure of liquid water as a random tetrahedral network, which was widely accepted by most scientists. With the development of computer science and the discovery of several amorphism, more and more attentions are paid on the mixture model of liquid water. In this paper, we firstly review some latest evidences about the multiple types of local structure in liquid water in both simulations and experiments. In all-atom simulation, the distributions of the local structure index obtained by minimizing the energy of samples are double peak at all temperatures. In experiment, the X-ray emission spectroscopy of liquid water at ambient pressure shows that there are two local structures in liquid water, one is order and ice-like, the other one is disorder and gas-like. Secondly, some results of our group on this topic are presented. We transformed the Raman spectra into the high-dimensional vectors and analyze the vectors with the principal component analysis method. The results show that all the end points of vectors are in a line in the high-dimensional space which implies that they can be obtained by linearly combining two basic points in that line. This means that the Raman spectra can be decomposed into two basic spectra. We also perform the same analysis on the distributions of tetrahedral order parameter in liquid water and obtained similar results. It is an obvious signal of the existence of multi-component in liquid water. Finally, we introduce the mixture model of liquid water which can be used to explain the thermodynamic properties of liquid water. In the mixture model, the form of the Gibbs free energy of liquid water is the same as the binary regular solution. The free energy is a function of the concentration of the disorder local structure. The anomalies of liquid water are directly caused by the change of concentration of the disorder local structure. In the low temperature and high pressure region, the mixture model has a critical point, which is consistent with the liquid-liquid phase transition theory.

Evident in many physical and chemical phenomena, thermodynamics is the study of how energy is stored, transformed and transferred in a molecule or material. However, prediction of these properties with simulation techniques is a non-trivial task as several factors such as composition and intermolecular interactions come into play. While molecular dynamics and ab initio molecular dynamics are the most common techniques for the prediction of thermodynamic properties, there exists many shortcomings associated with their use. Therefore, in this work we instead apply QCE theory to predict the thermodynamic properties of liquid water. This theory assumes that a condensed phase system can be represented as a 'mixture' of varying sized clusters rather than as a continuum. As QCE theory relies on first-principle simulations and statistical thermodynamics to determine the thermodynamic behavior of a system, appropriate selection of clusters is a crucial step towards achieving accurate predictions. In this study, we use molecular dynamics and ab initio calculations to obtain initial configurations of 400 water clusters, Wn where n = 3 to 10 and contrast their stability using two different criteria. The role of entropy towards cluster stabilization is investigated by comparing the binding (ΔEBIND/mol) and Gibbs free binding energy per molecule (ΔGBIND/mol) of various Wn at 298.15 K. Initial clustersets are constructed by exploring two-, three-, four and five-combinations of clustersets using the minimum ΔGBIND/mol structures of Wn. We also expand the ΔGBIND/mol criteria for Wn of sizes 3 to 7 to include values larger than 0.0 kJ mol-1 and smaller than 3.0 kJ mol-1 as a means of improving thermodynamic predictions. 37 of the 459 resulting clustersets predicted the correct boiling point of water and its thermodynamic properties with an accuracy of 95%. A scaled population-weighted infrared spectrum was compared to experimental results to validate the composition of the top 5 clustersets. The predicted spectra showed an exact match within the low frequency range (<1000 cm-1) with some discrepancy at the high frequency range (>3400 cm-1). This work highlights that ΔGBIND/mol is so far the best criteria to apply when determining an appropriate clusterset for QCE theory.

Thermodynamic properties of liquid water as well as hexagonal (Ih) and cubic (Ic) ice are predicted based on density functional theory at the hybrid-functional level, rigorously taking into account quantum nuclear motion, anharmonic fluctuations, and proton disorder. This is made possible by combining advanced free-energy methods and state-of-the-art machine-learning techniques. The ab initio description leads to structural properties in excellent agreement with experiments and reliable estimates of the melting points of light and heavy water. We observe that nuclear-quantum effects contribute a crucial [Formula: see text] to the stability of ice Ih, making it more stable than ice Ic. Our computational approach is general and transferable, providing a comprehensive framework for quantitative predictions of ab initio thermodynamic properties using machine-learning potentials as an intermediate step.

Cryopreservation is the preservation and storage of biomaterialsusing low temperatures. There are several approaches to cryopreservation,and these often include the use of cryoprotectants, which are solutesused to lower the freezing point of water. Isochoric (constant-volume)cryopreservation is a form of cryopreservation that has been gaininginterest over the past 18 years. This method utilizes the anomalousnature of water in that it expands as it freezes. The expansion ofice on freezing is used to induce a pressure in the system that limitsice growth. In this work, we use Gibbsian thermodynamics, the Elliottet al. multisolute osmotic virial equation, the Feistel and Wagnercorrelation for ice Ih, and the Grenke and Elliott correlation forthe thermodynamic properties of liquid water at low temperatures andhigh pressures to predict how the pressure, volume fraction of ice,and solute concentration in the unfrozen fraction change as the solutionis cooled isochorically. We then verified our model by predictingexperimental results for saline solutions and ternary aqueous solutionscontaining NaCl and organic compounds commonly used as cryoprotectants:glycerol, ethylene glycol, propylene glycol, and dimethyl sulfoxide.We found that our model accurately predicts experimental data thatwere collected for cryoprotectant concentrations as high as 5 M, andtemperatures as low as −25 °C. Since we have shown thatour liquid water correlation, on which this work was based, makesaccurate predictions to −70 °C, as long as the pressureis not higher than 400 MPa, we anticipate that the prediction methodspresented in this work will be accurate down to −70 °C.In this work we also modeled how sealing the isochoric chamber atroom temperature versus at the nucleation temperature impacts isochoricfreezing. The prediction methods developed in this work can be usedin the future design of isochoric cryopreservation experiments andprotocols.

The structural and thermodynamic properties of liquid water and of the dilute solutions of methane and ethane in water were calculated by Monte Carlo simulations in the temperature range 298 K to 318 K and 298 K to 333 K, respectively. The nonpolar molecules were modeled as one- and two-center Lennard–Jones particles; for the interaction potential of water a modified TIP5P model was used. The results indicate that the nonpolar solutes tend to aggregate with increasing temperature. Methane molecules preferably form water-separated pairs, even at higher temperatures, whereas for ethane contact pairs are more likely. For the thermodynamic conditions studied here, the residual chemical potential of water is a linear function of temperature.

Computing dissipative particle dynamics interactions to render molecular structure and temperature-dependent properties of simple liquids

Machine learning-generated TIP4P-BGWT model for liquid and supercooled water

Molecular interactions of local anesthetics in aqueous MgCl2 solutions: A volumetric, acoustic and spectroscopic analysis

Effect of sodium phosphate salts on the thermodynamic properties of aqueous solutions of poly(ethylene oxide) 6000 at different temperatures

Effect of temperature on the partial molar volumes, partial molar compressibility and viscosity B-coefficients of DL-4-aminobutyric acid in water and in aqueous sodium chloride solutions

In this study, the solute-cosolute interaction, solute-solvent interaction involved in the solubilisation process of ARG solutions and LVS-ARG solution systems are illustrated. The sound velocity values of both solution systems were determined at varying concentrations of ARG (0.01-0.8 mol.dm-3) at 298.15 K. Next, the refractive index and the density of the solution systems was measured at temperature range from 298.15 to 313.15K. Acoustic and volumetric parameters such as isentropic compressibility (KS), apparent isentropic molar compressibility (KSΦ), relative association (RA), acoustic impedance (Z), internal pressure (πi), free volume (Vf), molar volume (Φv0), molar expansibility (ΦE0) were calculated from sound velocity and density data. From the study, an increasing trend in sound velocity was observed with the increase in ARG concentration while compressibility values showed opposite trend. Additionally, solute-solvent interaction and structural effects of water for ARG and LVS-ARG systems are discussed regarding the changes in acoustic parameters.

Molar sound velocity, molar adiabatic compressibility and Van der Waals constant of gaseons, liquid and supercritical carbon dioxide at different temperature and pressure are calculated using liquid acoustical models and data of sound velocity, density, molar volume and adiabatic compressibility of carbon dioxide provided by National Institute of Standards and Technology, USA. The results show that the liquid acoustical models can be used in study acoustical property of supercritical carbon dioxide in wide ranges of temperature and pressure. The surface tension, conglutination and diffusivity at different temperatures and pressures are calculated. And the mutative rules of these physical quantities are analyzed. The data can provide reference for supercritical liquid technique.

The extraction of baicalin, wogonoside, baicalein, and wogonin from Radix Scutellariae was performed using subcritical water and conventional extraction. Compared with ethanol extraction, subcritical water extraction required shorter extraction time, yielded a higher efficiency, and required less extraction solvent. The stability of four flavonoids under subcritical water conditions was investigated, and the extraction products can be controlled through adjusting the properties of subcritical water, namely the selective extraction of some important components. The effects of key operation conditions including extraction temperature (110 to −160 °C), extraction time (10–90 min), water loadings (2.0–4.5 mL), and particle sizes (&gt;20 to &lt;100 mesh) were evaluated. The highest extraction yields of baicalin and wogonoside were obtained at extraction temperature of 12 °C, extraction time of 60 min, water loadings of 4 mL, and 60–100 mesh. The highest extraction yields of baicalein and wogonin were obtained at extraction temperature of 16 °C, extraction time of 20 min, water loadings of 4 mL, and 60–100 mesh.