<i>Ab initio</i> intermolecular potential energy surface for the CO2—N2 system and related thermophysical properties

Crusius, Johann-Philipp; Hellmann, Robert; Castro-Palacio, Juan Carlos; Vesovic, Velisa

doi:10.1063/1.5034347

Cited by 26 publications

(56 citation statements)

References 82 publications

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“…As shown in section 3 and as can already be assumed from the Eqs. 1, (2), and 3, various combinations of LJ parameters lead to an agreement between experimental and calculated transport coefficients within the experimental uncertainty for each transport property. Hence, for all experimental uncertainties ξ > 0, a set M ⊆ℝ 2…”

Section: Determination Of Lennard-jones Parameterssupporting

confidence: 55%

“…When comparing the results based on his theoretical approach with experimental data of the thermal conductivity, deviations of up to 6% can be observed. In a similar article, Crusius et al determined the transport properties for a CO 2 -N 2 mixture and show maximum deviations of up to 8% from experimental data for the binary diffusion coefficient and also the thermal conductivity [2]. For nitrous oxide, they were able to predict the viscosity with in the experimental uncertainty, the second virial coefficient however, was predicted poorly [3].…”

Section: Resultsmentioning

confidence: 99%

“…These subsets can be determined for each different transport property and since the diffusion coefficient is based on a collision integral with a different order than the thermal conductivity and the viscosity (please see Eqs. (1), (2), and (3)), these subsets can differ markedly.…”

Section: Resultsmentioning

confidence: 99%

“…For a monoatomic gas this is equivalent to the expression that can be obtained by dividing Eqs. (2) and (3). Based on Eq.…”

Section: Eucken Correctionmentioning

confidence: 99%

“…The accurate determination of diffusion coefficients, thermal conductivities and viscosities of gases has a decisive impact on the precision of computational models in chemical engineering. In recent years, the development of potential energy surfaces (PES) for interactions between two gas molecules using quantum mechanical ab initio calculations was employed extensively for calculating properties like the second virial coefficient, diffusion coefficients, thermal conductivities and viscosities of gases based on the kinetic theory for polyatomic gases [1,2]. This approach is not only fully predictive but also showed good precision for a variety of gases [3,4].…”

Section: Introduction and Theorymentioning

confidence: 99%

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Precise determination of LJ parameters and Eucken correction factors for a more accurate modeling of transport properties in gases

et al. 2020

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The kinetic gas theory, in particular the equations of Chapman and Enskog, proved to be good and widely applicable approximations for modeling transport properties like diffusion coefficients, viscosities and thermal conductivities. However, these equations rely on at least the Lennard-Jones parameters and for polar gases also the dipole moment. In the scientific literature, the Lennard-Jones parameters are fitted to only one experimentally determined transport coefficient. This approach leads to good agreement between the Chapman Enskog equations employing the so obtained parameters with the experimental data for this specific transport property. However, utilizing the same parameters for modeling different transport properties oftentimes leads to distinct deviations. In this work, it is shown that the subset of Lennard-Jones parameters with which the Chapman Enskog equations can predict the experimental results with deviations comparable to the experimental uncertainty are not identical for each transport property. Hence, fitting towards one property doesn't necessarily yield parameters that are suited to describe the other transport properties. In this publication, the Lennard-Jones parameters and a temperature dependent Eucken correction factor, leading to a significantly higher accuracy than the classical Eucken correction and also its modification by Hirschfelder, are therefore fitted towards all three transport properties simultaneously for seven exemplary gases. This approach leads to a significantly better agreement with experimental data for the three transport properties than the classical approach that relies on fitting to one single transport property and can be utilized to determine accurate sets of Lennard-Jones parameters and Eucken correction factors for any gas species. It provides a computationally inexpensive and practical method for the precise calculation of transport properties over a wide range of temperatures relevant for processes in the chemical industry.

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Section: Determination Of Lennard-jones Parameterssupporting

confidence: 55%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

“…For a monoatomic gas this is equivalent to the expression that can be obtained by dividing Eqs. (2) and (3). Based on Eq.…”

Section: Eucken Correctionmentioning

confidence: 99%

Section: Introduction and Theorymentioning

confidence: 99%

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Precise determination of LJ parameters and Eucken correction factors for a more accurate modeling of transport properties in gases

et al. 2020

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The accurate estimation of the third virial coefficients for helium using three‐body neural network potentials

Kwon

Song

Woo

et al. 2022

Bulletin Korean Chem Soc

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The description of many‐body interactions is one of challenging problems in molecular dynamics simulations. Recently, neural network potentials have been spotlighted as an approach to describe many‐body interactions. In this study, we obtain the neural network potentials for three‐body interactions of helium using a deep learning method. We perform quantum calculations to obtain single point energies for helium trimers and obtain the neural network potentials for three‐body interactions by performing a deep learning method. In order to test the validity of the neural network three‐body interactions, we perform Mayer‐sampling Monte Carlo simulations and calculate third virial coefficients for helium. We show that the third virial coefficients obtained from three‐body neural network potentials are more accurate than those obtained from two‐body neural network potentials. The deep learning method in our study would be extended to obtain the high‐order virial coefficients for complex molecules.

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Determination of the Binary Diffusion Coefficients and Interaction Viscosities of the Systems Carbon Dioxide–Nitrogen and Ethane–Methane in the Dilute Gas Phase from Accurate Experimental Viscosity Data Using the Kinetic Theory of Gases

2023

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The results of viscosity measurements at moderate densities on the two gaseous mixtures carbon dioxide–nitrogen and ethane–methane including the pure gases between 253.15 K and 473.15 K, originally performed by Humberg et al. at Ruhr University Bochum, Germany, using a rotating-cylinder viscometer between 0.1 MPa and 2.0 MPa, were employed to determine the interaction viscosity, $$\eta _{12}^{(0)}$$ η 12 ( 0 ) , and the product of molar density and diffusion coefficient, $$(\rho D_{12})^{(0)}$$ ( ρ D 12 ) ( 0 ) , each in the limit of zero density. The isothermal viscosity data were evaluated by those authors with density series restricted to the second order at most to derive the zero-density viscosities and initial density viscosity coefficients, $$\eta _\textrm{mix}^{(0)}$$ η mix ( 0 ) and $$\eta _\textrm{mix}^{(1)}$$ η mix ( 1 ) , for the mixtures, as well as, $$\eta _i^{(0)}$$ η i ( 0 ) and $$\eta _i^{(1)}$$ η i ( 1 ) ($$i=1,2$$ i = 1 , 2 ), respectively, for the pure gases. Humberg et al. have already compared their $$\eta _\textrm{mix}^{(0)}$$ η mix ( 0 ) and $$\eta _i^{(0)}$$ η i ( 0 ) data for carbon dioxide–nitrogen and ethane–methane with corresponding viscosity values theoretically computed for the nonspherical potentials of the intermolecular interaction. Now we employed $$\eta _\textrm{mix}^{(0)}$$ η mix ( 0 ) and $$\eta _\textrm{mix}^{(1)}$$ η mix ( 1 ) as well as $$\eta _i^{(0)}$$ η i ( 0 ) and $$\eta _i^{(1)}$$ η i ( 1 ) in two procedures to derive $$\eta _{12}^{(0)}$$ η 12 ( 0 ) values. For this, we needed $$A_{12}^*$$ A 12 ∗ values (ratio between effective cross-sections of viscosity and diffusion). But the second procedure applying the initial density viscosity coefficients $$\eta _\textrm{mix}^{(1)}$$ η mix ( 1 ) and $$\eta _i^{(1)}$$ η i ( 1 ) failed to yield reasonable $$\eta _{12}^{(0)}$$ η 12 ( 0 ) values. The first procedure should provide the best results when it is possible to use $$A_{12}^*$$ A 12 ∗ values computed for the nonspherical potential. The effect is comparatively small if $$\eta _{12}^{(0)}$$ η 12 ( 0 ) is determined. But if $$(\rho D_{12})^{(0)}$$ ( ρ D 12 ) ( 0 ) is calculated from $$\eta _{12}^{(0)}$$ η 12 ( 0 ) using $$A_{12}^*$$ A 12 ∗ values for the nonspherical potential, the impact is several percent. Moreover, the experimentally based $$\eta _{12}^{(0)}$$ η 12 ( 0 ) and $$(\rho D_{12})^{(0)}$$ ( ρ D 12 ) ( 0 ) data agree with theoretically calculated values for the nonspherical potentials.

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Ab initio intermolecular potential energy surface for the CO2—N2 system and related thermophysical properties

Cited by 26 publications

References 82 publications

Precise determination of LJ parameters and Eucken correction factors for a more accurate modeling of transport properties in gases

Precise determination of LJ parameters and Eucken correction factors for a more accurate modeling of transport properties in gases

The accurate estimation of the third virial coefficients for helium using three‐body neural network potentials

Determination of the Binary Diffusion Coefficients and Interaction Viscosities of the Systems Carbon Dioxide–Nitrogen and Ethane–Methane in the Dilute Gas Phase from Accurate Experimental Viscosity Data Using the Kinetic Theory of Gases

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