Thermodynamic Properties of Octamethylcyclotetrasiloxane

A multitude of industries, including energy and process engineering, as well as academia are researching and utilizing new fluid substances to further the aim of sustainability. Knowledge of the thermodynamic properties of these substances is a prerequisite, if they are to be utilized to their fullest potential. To date, the way to acquire reliable knowledge of the thermodynamic behavior is through measurements. The ensuing experimental data are then used to develop equations of state, which efficiently embody the gained knowledge of the behavior of the fluid substance, allow for interpolation and, to some extent, extrapolation. However, the acquisition of low-uncertainty experimental data, and thus the development of accurate equations of state, is often time-consuming and expensive. For substances for which suitable force field models exist, molecular modeling and simulation are well-suited to generate thermodynamic data or to augment experimental data, however, at the expense of larger uncertainties. The major goal of this work is to present a new approach for the development of equations of state using (1) symbolic regression, which is a machine learning based model development approach, (2) optimal experimental design, and (3) efficient data acquisition. We demonstrate this approach using the example of density data of an air-like binary mixture (0.2094,hbox {O}_{2},+,0.7906,hbox {N}_{2}) over the temperature range from {100},{textrm{K}} to {300},{textrm{K}} at pressures of up to {8},{textrm{MPa}}, which covers the gaseous, liquid, and supercritical regions. For this purpose, an experimental data set published by von Preetzmann et al. (Int. J. Thermophys. 42, 2021) and molecular simulation data sampled in this work are used. The two data sets are compared in terms of acquisition time, cost, and uncertainty, showing that an optimized combination of experimental and simulation data leads to lower cost while maintaining low uncertainties.

A new equation of state for predicting the thermodynamic properties of liquid alkali metals

To date, it has been considered that all classical equations of state (EOS) have failed to describe the properties of fluids near the critical region, where the density fluctuations have a significant influence on fluid properties. In this paper, we suggest a newly constructed equation for fluid states, the generalized van der Waals (GvdW) EOS with the highly simplified Dieterici's form P = [RT/(V - b)] - a(b/V)c by a new model potential construction describing intermolecular interactions. On the basis of the model potential construction, it is shown that the a, b, and c parameters have physical interpretations as an internal pressure, a void volume, and a dimensionless value that represents an inharmonic intermolecular cell potential, respectively. As an illustration of our model approach, we initially apply it to near the critical point (cp) region, where all classical EOS descriptions have been incorporated with experimental thermodynamic data, and we obtain a table of three parameters for 12 pure normal fluids, which precisely describes thermodynamic critical values. On the basis of the basic relations between pressure and volume at the critical point, we express the corresponding EOS in terms of the c parameter, and by this means, we also obtain a theoretical vapor-liquid equilibrium (VLE) line, which closely coincides with the experimental data for several pure normal fluids near the critical region. As a result, we show that thermodynamic properties near the critical region can be described analytically by only three parameters. In addition, to validate our EOS for the temperature-differential derivatives, we show that the calculated isochoric heat capacity (Cv) of saturated argon closely coincides with the experimental data. Moreover, the possibility of a precise description with respect to the entire fluid region is also argued, in terms of the physical cases from the triple point to the ideal gas region.

Description of self-diffusion coefficients of gases, liquids and fluids at high pressure based on molecular simulation data

In the design and testing of gas compressors, the correct determination of the thermodynamic properties of the gas, such as enthalpy, entropy, and specific volume from pressure, temperature, and composition, plays an important role. Due to the wide range of conditions encountered, pressure, specific volume and temperature (p-v-T) equations of state (EOS) are used to determine the isentropic or polytropic efficiency, the work input, and capacity of a compressor configuration. However, accurate equations of state may be lacking for some more complicated gas mixtures. Experimentally determined thermodynamic state information is more accurate and is needed to validate, correct, or supplant existing equations of state. The methodology for calculating enthalpy and entropy from experimental data is presented including the full step-by-step derivation from first principles. The thermodynamic relations or calculus properties used in each step of the derivation are clearly identified to provide traceability and encourage verification. Results are presented in three forms to match all possible tabulation formats of temperature, pressure, and volume data. Calculation methods for other useful but unmeasured thermodynamic properties such as the specific heat at constant pressure and the ratio of specific heats are also given. The methodology is demonstrated in two examples. The first is a verification case where REFPROP, an equation of state software, is used to generate input data, and the enthalpy and entropy values calculated from the input data are shown to match those given directly by REFPROP. The second is a practical demonstration where the methodology is used with actual experimental data.

Asphaltene is a group of complex compounds commonly present in reservoir fluids, especially in viscous oils. It is conceivable that asphaltene strongly interacts with water through hydrogen bonding, affecting phase behavior of water/oil mixtures with/without forming an asphaltene-rich phase. Modeling of these polar components in reservoir fluids is challenging with cubic equations of state (EOS) due to the size-symmetricity and self- and cross-associations of asphaltene and water. In this research, the cubic-plus-association (CPA) EOS is applied to represent complex multiphase behavior associated with water and asphaltene. Asphaltene-containing heavy oils are characterized by the CPA EOS with four pseudo components (asphaltene and the other three pseudo components) based on their experimental data. Asphaltene is the only associating component in the oil models. Then, multiphase behavior data for mixtures of water with each of these oils are represented by the CPA EOS. Calculated phase behavior by the CPA EOS models is compared with experimental data and also with the Peng-Robinson EOS for several cases. This paper also presents a new correlation for binary interaction parameters (BIPs) for water with n-alkanes for the CPA EOS on the basis of experimental data for three-phase coexistence for water/n-alkane binaries (Brunner 1990). In case studies, the CPA EOS is shown to be able to represent multiphase behavior for water/oil mixtures with up to four equilibrium phases: asphaltene-rich, solvent-rich, aqueous, and vapor phases. In particular, the CPA EOS is successfully applied to bitumen/water mixtures, involving asphaltene-water emulsion, water solubility in bitumen, and their continuous transition with varying temperature. Furthermore, results show that the CPA EOS can reasonably represent the multiphase data measured for a n-butane/bitumen/water mixture that were not accurately correlated with the PR EOS in the literature. Modeling an asphaltene-rich phase in several cases is possible only with consideration of the water-asphaltene interaction, which is worth the additional complexities of the CPA EOS in comparison with the PR EOS.

A set of unified relativistic mean-field equations of state for hyperonic compact stars recently built in [M. Fortin, Ad. R. Raduta, S. Avancini, and C. Providencia, Phys. Rev. D {\bf 101}, 034017 (2020)] is used to study the thermal evolution of non-magnetized and non-rotating spherically-symmetric isolated and accreting neutron stars under different hypothesis concerning proton $S$-wave superfluidity. These equations of state have been obtained in the following way: the slope of the symmetry energy is in agreement with experimental data; the coupling constants of $\Lambda$ and $\Xi$-hyperons are determined from experimental hypernuclear data; uncertainties in the nucleon-$\Sigma$ interaction potential are accounted for; current constraints on the lower bound of the maximum neutron star mass are satisfied. Within the considered set of equations of state, the presence of hyperons is essential for the description of the cooling/heating curves. One of the conclusions we reach is that the criterion of best agreement with observational data leads to different equations of states and proton $S$-wave superfluidity gaps when applied separately for isolated neutron stars and accreting neutron stars in quiescence. This means that at least in one situation the traditional simulation framework that we employ is not complete and/or the equations of state are inappropriate. Another result is that, considering equations of state which do not allow for nucleonic dUrca or allow for it only in very massive NS, the low luminosity of SAX J1808 requires a repulsive $\Sigma$-hyperon potential in symmetric nuclear matter in the range $U_\Sigma^{(N)}\approx 10-30$ MeV. This range of values for $U_\Sigma^{(N)} $ is also supported by the criterion of best agreement with all available data from INS and XRT.

The evaluation of phase equilibria and solubility properties through theoretical approaches is a well-known field, where a significant amount of models are able to describe them with a good degree of accuracy. However, the simultaneous calculation of transport properties together with thermodynamic phase properties still remains a challenge, due to the difficulties in describing the behavior of properties like the viscosity of fluids with the same approach. In this work, the free-volume theory (FVT) has been coupled with the soft-SAFT equation for the first time to extend the capabilities of the equation to the calculation of transport properties. The theory has been first tested using simulation data of the viscosity of the Lennard-Jones (LJ) fluid and LJ chains over a wide range of temperature and pressure. Good agreement has been found at all chain lengths, except for some deviations at near-zero density values. Several trends of the viscosity parameters with the length of the chain are identified, allowing the prediction of other chain fluids. Finally, the new equation has been applied to the n-alkanes family, where viscosity is a key property, and results are compared with experimental data. The three viscosity parameters were fitted to viscosity data of the pure fluid at several isotherms or isobars, whereas the density and pressure (or temperature) were taken from the soft-SAFT output. Again, the effect of these parameters on the viscosity has been investigated and compared with results obtained for the LJ chains and with previous work of other authors. The new equation performs very well in all cases, with a global average absolute deviation of 2.12% and shows predictive capabilities for heavier compounds. This empowers soft-SAFT with new capabilities, allowing the equation to calculate phase, interfacial, and transport properties with the same model and degree of accuracy.

Volumetric and second-derivative thermodynamic properties of binary mixtures of carbon dioxide and methane were calculated under supercritical conditions at pressures up to 99.93 MPa and temperatures between (323.15 and 573.15) K using molecular dynamics simulations with the multistate Bennett acceptance ratio technique. Eleven compositions were studied, ranging from pure methane to pure carbon dioxide in 0.10 increments in carbon dioxide mole fraction. The molecular simulations utilized the TraPPE and SAFT-γ force fields to model methane and carbon dioxide. Because of the unavailability of experimental data, the results were compared against the extended range estimation and extrapolation of the GERG-2008 equation for the calculation of volume expansivity, isothermal compressibility, isobaric and isochoric heat capacities, Joule–Thomson coefficient, and speed of sound of the binary mixtures. The agreement between the simulation results and those obtained through the extrapolation of the GERG-2008 equation beyond its stated range of validity is quite good, suggesting that the force field representation of the binary mixture is accurate, especially when compared with the extrapolation of traditional cubic equations of state. Although more computationally expensive, molecular simulations relying upon only a few physically meaningful parameters are able to give similar results to those obtained with the semiempirical multiparameter GERG-2008 model.

Calculation of thermodynamic properties of water by the CPA equation of state

Prediction of the volumetric and vapor-liquid equilibrium properties of CO2-N2-O2-Ar fluid mixtures with a general Helmholtz equation of state

We use molecular dynamics simulations to study the thermodynamics, structure, and dynamics of the Li2CO3-K2CO3 (62:38 mol. %) eutectic mixture. We present a new classical non-polarizable force field for this molten salt mixture, optimized using experimental and first principles molecular dynamics simulations data as reference. This simple force field allows efficient molecular simulations of phenomena at long time scales. We use this optimized force field to describe the behavior of the eutectic mixture in the 900-1100 K temperature range, at pressures between 0 and 5 GPa. After studying the equation of state in these thermodynamic conditions, we present molecular insight into the structure and dynamics of the melt. In particular, we present an analysis of the temperature and pressure dependence of the eutectic mixture's self-diffusion coefficients, viscosity, and ionic conductivity.

Emissions of long-lived greenhouse gases are believed to be a major driver of climate change. Carbon dioxide is the most important greenhouse gas[1] and one of the most prominent strategies to lower its emissions is carbon capture and sequestration (CCS)[2]. CO2 can be stored in geological repositories, in which sodium chloride (NaCl) is the most common dissolved salt. For the optimum design of any CCS process, accurate experimental data and computational models are necessary. This study focuses on generating and validating molecular-based models and methodologies to allow for reliable prediction of the thermodynamic and transport properties of CO2-brine mixtures over a broad range of temperatures and pressures relevant for geological storage. We employ Atomistic Molecular Dynamics (MD) simulations, which is widely used to predict phase equilibria, transport, and other properties of gases, liquids etc. The current study aims at: (a)Determining the accuracy of current molecular models over a broad range of temperatures, pressures and salt concentration relevant to CCS processes with respect to phase behavior and transport properties of CO2 - H2O - NaCl mixture, (b)Developing efficient computational methods and improved potential models for these properties, (c) Assessing the accuracy of SAFT/PC-SAFT based models for the phase behavior of CO2-H2O-NaCl mixture and improving the models using also data generated through molecular simulations and (d)Developing appropriate engineering models for the correlation of viscosity and self-diffusion coefficient experimental and molecular simulation data for the CO2-H2O-NaCl mixture. More specifically, in this work, we study the mutual solubility and interfacial tension in the CO2-H2O-NaCl system over a broad range of temperatures, pressures and NaCl concentrations, using direct interfacial MD simulations. Also we calculate transport properties such as viscosity, self-diffusion coefficient, thermal conductivity. Additionally, we assess the predictive abilities of several combinations of existing H2O, CO2 and NaCl models. To describe water, CO2 and NaCl we use various intermolecular potential models[4,5,6,7,8] that provide property predictions for the CO2-H2O-NaCl mixture over a broad range of temperature, pressure and composition. In addition, the estimated accuracy of the model for each property and for specific conditions will be reported. Our group takes advantage of recent developments of efficiently parallelized codes such as LAMMPS[9] and GROMACS[10]. [1] Metz B, Intergovernmental Panel on Climate Change. Working Group III. Climate Change 2007: Mitigation of Climate Change: Contribution of Working Group III to the Fourth Assessment Report of the IInter-governmental Panel on Climate Change. Cambridge; New York: Cambridge University Press (2007). [2] International Energy Agency, A Policy Strategy for Carbon Capture and Storage (2012). [3] Jorgensen, W.L. J. Am. Chem. Soc., 103(2), 335 - 340 (1981). [4] Berendsen, H.J.C., Grigera, J.R. and Straatsma, T.P., J. Chem. Phys., 91(24), 6269 - 6271 (1987). [5] Harris, J.G. and Yung, K.H. J. Phys. Chem., 99(31), 12021 - 12024 (1995). [6] Potoff, J.J. and Siepmann, J.I. AlChE J., 47(7), 1676 - 1682 (2001). [7] Smith, D.E. and Dang, L.X. J. Chem. Phys., 100(5), 3757 - 3766 (1994). [8] Deublein, S., Reiser, S., Vrabec, J. and Hasse H. to appear (2012). [9] See: http://lammps.sandia.gov/. [10] See: http://www.gromacs.org/.

Representation of solid-supercritical fluid phase equilibria using cubic equations of state

Accurate prediction of the thermodynamic properties of fluids in the system H 2O–CO 2–CH 4–N 2 up to 2000 K and 100 kbar from a corresponding states/one fluid equation of state