Modification of a model for mixed hydrates to represent double cage occupancy

Hielscher, Sebastian; Semrau, Benedikt; Jäger, Andreas; Vinš, Václav; Breitkopf, Cornelia; Hrubý, Jan

doi:10.1016/j.fluid.2019.02.019

Cited by 11 publications

(29 citation statements)

References 61 publications

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“…In order to investigate the influence of the incorporated methane molecules on the lattice constant of the hydrate structure, the degree of filling of the hydrates was systematically varied. For this purpose, the individual methane molecules were randomly distributed among the cavities, but in such a way that, in agreement with the results shown previously, experimental studies 53, and previous models 20–28, 51, there is a maximum of one methane molecule in each cavity only. In Fig.…”

Section: Resultssupporting

confidence: 79%

“…The statistical gas hydrate model of van der Waals and Platteeuw 38 is commonly used for modeling pure as well as mixed gas hydrates and can also be used in case of multiple cage occupancies. Different research groups modified and applied this model, as for example 20–28, 39–52. In the case of single occupancy of cages (such as for methane hydrates), the gas hydrate model can be expressed explicitly in the chemical potential of water in the hydrate phase, e.g., 28, in the following way

true μ_{normalw}^{normalH} (T, p, f_{J}) = g_{normalw}^{β} (T, p) - RT \sum_{i} ν_{i} \ln [1 + \sum_{J} C_{i, J} (T, p) f_{J}]

…”

Section: Computational Methods and Modelingmentioning

confidence: 99%

“…While different potential functions have been investigated 52, the most commonly used potential that was found to yield good results in describing macroscopic properties of gas hydrates (see, e.g. 22, 23, 25, 42) is the Kihara potential 47 assuming spherical molecules with a hard core radius a c . Combining the Kihara potential with the Lennard Jones and Devonshire cell theory, the Kihara cell potential yields

true w_{i, J} (r) = 2 ε_{J} z_{i} {\frac{σ_{J}^{12}}{{rR}_{i}^{11}} (δ_{i, J}^{10} + \frac{a_{normalc, J}}{R_{i}} δ_{i, J}^{11}) - \frac{σ_{J}^{6}}{{rR}_{i}^{5}} (δ_{i, J}^{4} + \frac{a_{normalc, J}}{R_{i}} δ_{i, J}^{5})}

…”

Section: Computational Methods and Modelingmentioning

confidence: 99%

“…On the other hand, mixture models were developed and applied to calculate the phase equilibria and investigate the phase stabilities of several gas hydrates. These mixtures were modeled with highly accurate reference equations of state [22][23][24][25][26][27][28]. However, this requires sufficiently precise substance data, which are sometimes very difficult to obtain experimentally and are due to this often not available.…”

Section: Introductionmentioning

confidence: 99%

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Predicting Material Properties of Methane Hydrates with Cubic Crystal Structure Using Molecular Simulations

Lorenz

Jäger

Breitkopf

2022

Chemie Ingenieur Technik

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Formation of gas hydrates is an important feature of water systems. It occurs undesirably in natural gas pipelines, but also in deep-sea deposits and unfreezing permafrost. However, the natural occurrence is of particular interest because methane hydrates have one of the highest energy densities of all naturally occurring forms of methane. Therefore, an accurate description of its thermodynamic properties is required. In this work, we demonstrate how the material properties of methane hydrate can be more easily calculated compared to ab initio methods. Furthermore, it is shown how the material properties depend on the cage occupancy by using the comparably fast self-consistent-charge density-functional tightbinding (SCC-DFTB) method. The cell potential is calculated and compared to a numerical as well as an ab initio model, and is in good agreement with the literature.

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Section: Resultssupporting

confidence: 79%

true μ_{normalw}^{normalH} (T, p, f_{J}) = g_{normalw}^{β} (T, p) - RT \sum_{i} ν_{i} \ln [1 + \sum_{J} C_{i, J} (T, p) f_{J}]

…”

Section: Computational Methods and Modelingmentioning

confidence: 99%

true w_{i, J} (r) = 2 ε_{J} z_{i} {\frac{σ_{J}^{12}}{{rR}_{i}^{11}} (δ_{i, J}^{10} + \frac{a_{normalc, J}}{R_{i}} δ_{i, J}^{11}) - \frac{σ_{J}^{6}}{{rR}_{i}^{5}} (δ_{i, J}^{4} + \frac{a_{normalc, J}}{R_{i}} δ_{i, J}^{5})}

…”

Section: Computational Methods and Modelingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Predicting Material Properties of Methane Hydrates with Cubic Crystal Structure Using Molecular Simulations

Lorenz

Jäger

Breitkopf

2022

Chemie Ingenieur Technik

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show abstract

“…Moreover, precise solid models for hydrates in the form of Helmholtz energy have been continuously developed by Jäger, Span, and co-workers. [30][31][32][33][34][35][36] In contrast to the empirical approach, where the errors in the solid model from Eq. ( 2) are offset by those introduced to the fluid EOS in the phase equilibrium regression, this new approach, in principle, allows fugacities in both the solid and fluid phases to be predicted accurately.…”

Section: Articlementioning

confidence: 99%

Equation of State for Solid Benzene Valid for Temperatures up to 470 K and Pressures up to 1800 MPa

Xiao

Trusler

Yang

et al. 2021

Journal of Physical and Chemical Reference Data

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The thermodynamic property data for solid phase I of benzene are reviewed and utilized to develop a new fundamental equation of state (EOS) based on Helmholtz energy, following the methodology used for solid phase I of CO 2 by Trusler [J. Phys. Chem. Ref. Data 40, 043105 (2011)]. With temperature and molar volume as independent variables, the EOS is able to calculate all thermodynamic properties of solid benzene at temperatures up to 470 K and at pressures up to 1800 MPa. The model is constructed using the quasi-harmonic approximation, incorporating a Debye oscillator distribution for the vibrons, four discrete modes for the librons, and a further 30 distinct modes for the internal vibrations of the benzene molecule. An anharmonic term is used to account for inevitable deviations from the quasi-harmonic model, which are particularly important near the triple point. The new EOS is able to describe the available experimental data to a level comparable with the likely experimental uncertainties. The estimated relative standard uncertainties of the EOS are 0.2% and 1.5% for molar volume on the sublimation curve and in the compressed solid region, respectively; 8%-1% for isobaric heat capacity on the sublimation curve between 4 K and 278 K; 4% for thermal expansivity; 1% for isentropic bulk modulus; 1% for enthalpy of sublimation and melting; and 3% and 4% for the computed sublimation and melting pressures, respectively. The EOS behaves in a physically reasonable manner at temperatures approaching absolute zero and also at very high pressures.

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Cryogenic Solid Solubility Measurements for HFC-32 + CO2 Binary Mixtures at Temperatures Between (132 and 217) K

et al. 2023

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Accurate phase equilibrium data for mixtures of eco-friendly but mildly-flammable refrigerants with inert components like CO2 will help the refrigeration industry safely employ working fluids with 80 % less global warming potential than those of many widely-used refrigerants. In this work, a visual high-pressure measurement setup was used to measure solid–fluid equilibrium (SFE) of HFC-32 + CO2 binary systems at temperatures between (132 and 217) K. The experimental data show a eutectic composition of around 11 mol % CO2 with a eutectic temperature of 131.9 K at solid–liquid–vapour (SLVE) condition. Measured SLVE and solid–liquid equilibrium data were used to tune a thermodynamic model implemented in the ThermoFAST software package by adjusting the binary interaction parameter (BIP) in the Peng–Robinson equation of state. The tuned model represents the measured melting points for binary mixtures with a root mean square deviation (RMSD) of 3.2 K, which is 60 % less than achieved with the default BIP. An RMSD of 0.5 K was obtained using the tuned model for the mixtures with CO2 fractions over 28 mol % relative to an RMSD of 3.4 K obtained with the default model. The new property data and improved model presented in this work will help avoid solid deposition risk in cryogenic applications of the HFC-32 + CO2 binary system and promote wider applications of more environmentally-friendly refrigerant mixtures.

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Modification of a model for mixed hydrates to represent double cage occupancy

Cited by 11 publications

References 61 publications

Predicting Material Properties of Methane Hydrates with Cubic Crystal Structure Using Molecular Simulations

Predicting Material Properties of Methane Hydrates with Cubic Crystal Structure Using Molecular Simulations

Equation of State for Solid Benzene Valid for Temperatures up to 470 K and Pressures up to 1800 MPa

Cryogenic Solid Solubility Measurements for HFC-32 + CO2 Binary Mixtures at Temperatures Between (132 and 217) K

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