Predictive Thermodynamicsfor Isochoric (Constant-Volume)Cryopreservation Systems

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.

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.

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.

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.

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.

In this study, the heat capacities of ternary systems of salt/glycol/H2O and buffer/glycol/H2O were measured over the temperature range 30 to 80℃ and different solute concentrations: salt/buffer (4.0, 9.0, 16.0 wt %) + glycol (40 wt %) using a heat flow differential scanning calorimeter (DSC). The salt was magnesium chloride (MgCl2．6H2O) ; the buffers were N-[tris(hydroxymethyl)methyl] -3-aminopropanesulfonic acid (TAPS) and tris (hydroxymethyl) amionmethane (TRIS); and the glycols were diethylene glycol (DEG), triethylene glycol (TEG), tetraethylene glycol (T4EG), propylene glycol (PG), tripropylene glycol (TPG), dipropylene glycol (DPG). For the pure system, the dependence of the molar heat capacity with temperature was correlated by a second order equation. The binary system of TPG + H2O for molar heat capacities and excess molar heat capacities were using a Redlich-Kister-type equation. The data were then reported as functions of temperature and composition. For the ternary systems, an equation proposed by Sohnel and Novotny was used to represent the measured heat capacity data. Results showed that the measured heat capacity data were satisfactorily correlated using the applied correlations. Therefore, results presented in this are, in general, of sufficient accuracy for most engineering-design calculations

Singularity of liquid water-data analysis and modelling

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

Ethylene glycol (EG) is a common cause of toxic ingestions. Gas chromatography (GC)-based laboratory assays are the gold standard for diagnosing EG intoxication. However, GC requires specialized instrumentation and technical expertise that limits feasibility for many clinical laboratories. The objective of this retrospective study was to determine the utility of incorporating a rapid EG assay for management of cases with suspected EG poisoning. The University of Iowa Hospitals and Clinics core clinical laboratory adapted a veterinary EG assay (Catachem, Inc.) for the Roche Diagnostics cobas 8000 c502 analyzer and incorporated this assay in an osmolal gap-based algorithm for potential toxic alcohol/glycol ingestions. The main limitation is that high concentrations of propylene glycol (PG), while readily identifiable by reaction rate kinetics, can interfere with EG measurement. The clinical laboratory had the ability to perform GC for EG and PG, if needed. A total of 222 rapid EG and 24 EG/PG GC analyses were documented in 106 patient encounters. Of ten confirmed EG ingestions, eight cases were managed entirely with the rapid EG assay. PG interference was evident in 25 samples, leading to 8 GC analyses to rule out the presence of EG. Chart review of cases with negative rapid EG assay results showed no evidence of false negatives. The results of this study highlight the use of incorporating a rapid EG assay for the diagnosis and management of suspected EG toxicity by decreasing the reliance on GC. Future improvements would involve rapid EG assays that completely avoid interference by PG.

Chapter 5 - Ethylene Glycol and Other Glycols: Analytical and Interpretation Issues

Propylene glycol and ethylene glycol recovery from aqueous solution via reactive distillation

Commentary on the paper by Hsieh et al (see page 510) The simultaneously hydrophilic and lipophilic properties of glycol ethers account for their use as solvents in a wide range...

Thermogelling polymers composed of poly(cyclohexylenedimethylene adipate) and poly(ethylene glycol)

For the moment, coolants that are composed of aqueous solutions of propylene glycol are widely used in chillers. Such coolants have some advantages over brines or ethylene glycol solutions: non-toxicity, low corrosivity, low crystallization temperature. However, aqueous solutions of the propylene glycol have poor heat transfer efficiency in heat exchangers at low temperatures. One of methods to improve the thermophysical properties of the propylene glycol based coolants and also increasing the heat transfer coefficient in forced convection flow in a tube is an addition of the metal or metal oxides nanoparticles. The prospects of nanoparticle additives to coolants for application in refrigeration systems have been studied. The method of preparation of the nanocoolants based on aqueous solutions of propylene glycol and Al2O3 nanoparticles has been considered. The aggregative stability of Al2O3 nanoparticles (0.53 and 1.03 % mass.) in nanocoolant has been investigated. The results of complex experimental investigation of the thermophysical properties of nanocoolant in temperature range 253-313 К are reported. The comparative analysis of thermophysical properties of nanocoolant and base fluid (aqueous solution of propylene glycol) has been carried out. The results of experimental investigation of the heat transfer coefficient in laminar flow forced convection of coolant and nanocoolant in pipe are presented. It was shown that the heat transfer coefficients for various values of the Reynolds number typical for laminar flow for the traditional coolant was generally less than for the nanocoolant.