Skip to main content
SpringerLink
Log in

A Comparative Study of TIP4P-2005, SPC/E, SPC, and TIP3P-Ew Models for Predicting Water Transport Coefficients Using EMD and NEMD Simulations

  • Published:
Journal of Engineering Thermophysics Aims and scope

Abstract

Paying attention to transport phenomena in fluids has always been an integral part in designing chemical processes and water has always been a major part of scientific researches. In this study, the self-diffusion coefficient, shear viscosity and thermal conductivity of water at 298.15 K and 1 atm pressure were predicted and compared using four models of TIP3P-Ew, SPC, SPC/E and TIP4P-2005 by equilibrium and non-equilibrium molecular dynamics (NEMD) simulations. To predict the self-diffusion coefficient and shear viscosity, two equilibrium methods of Green-Kubo and Einstein were applied and there was approximately no difference between the results of these methods. Among the studied models, the results of TIP4P-2005 had the highest consistency with experimental data. To predict the thermal conductivity, Green-Kubo and NEMD methods were employed. The NEMD was a far more accurate and better method than Green-Kubo method and the results of TIP3P-Ew model had the highest agreement with the experimental data.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. S.1.
Fig. S.2.
Fig. S.3.
Fig. S.4.
Fig. S.5.

REFERENCES

  1. Mao, Y. and Zhang, Y., Thermal Conductivity, Shear Viscosity and Specific Heat of Rigid Water Models, Chem. Phys. Lett., 2012, vol. 542, pp. 37–41; https://doi.org/10.1016/j.cplett.2012.05.044.

    Article  ADS  Google Scholar 

  2. Lee, S.H., Temperature Dependence of the Thermal Conductivity of Water: A Molecular Dynamics Simulation Study Using The SPC/E Model, Mol. Phys., 2014, vol. 112, pp. 2155–2159; https://doi.org/ 10.1080/00268976.2014.891769.

    Article  ADS  Google Scholar 

  3. Lee, S.H. and Kim, J., Transport Properties of Bulk Water at 243–550 K: A Comparative Molecular Dynamics Simulation Study Using SPC/E, TIP4P, and TIP4P/2005 Water Models, Mol. Phys., 2019, vol. 117, pp. 1926–1933; https://doi.org/10.1080/00268976.2018.1562123.

    Article  ADS  Google Scholar 

  4. Guevara-Carrion, G., Vrabec, J., and Hasse, H., Prediction of Self-Diffusion Coefficient and Shear Viscosity of Water and Its Binary Mixtures with Methanol and Ethanol by Molecular Simulation, J. Chem. Phys., 2011, vol. 134; https://doi.org/10.1063/1.3515262.

    Article  ADS  Google Scholar 

  5. Müller-Plathe, F., Reversing the Perturbation in Nonequilibrium Molecular Dynamics: An Easy Way to Calculate the Shear Viscosity of Fluids, Phys. Rev. E, Stat. Phys., Plasmas, Fluids, Relat. Interdiscip. Top., 1999, vol. 59, pp. 4894–4898; https://doi.org/10.1103/PhysRevE.59.4894.

    Article  ADS  Google Scholar 

  6. Müller-Plathe, F. and Bordat, P., Reverse Non-Equilibrium Molecular Dynamics, in Nov. Methods Soft Matter Simulations, Springer, 2004, pp. 310–326; https://doi.org/https://doi.org/10.1007/978-3-540-39895-0_10.

  7. Vega, C., Abascal, J.L.F., Conde, M.M., and Aragones, J.L., What Ice Can Teach Us about Water Interactions: A Critical Comparison of the Performance of Different Water Models, Faraday Discuss., 2008, vol. 141, pp. 251–276; https://doi.org/10.1039/b805531a.

    Article  ADS  Google Scholar 

  8. Fuentes-Azcatl, R., Mendoza, N., and Alejandre, J., Improved SPC Force Field of Water Based on the Dielectric Constant: SPC/\(\varepsilon\), Phys. A Stat. Mech. Its Appl., 2015, vol. 420, pp. 116–123; https://doi.org/ 10.1016/j.physa.2014.10.072.

    Article  ADS  Google Scholar 

  9. Sakuma, H., Ichiki, M., Kawamura, K., and Fuji-Ta, K., Prediction of Physical Properties of Water under Extremely Supercritical Conditions: A Molecular Dynamics Study, J. Chem. Phys., 2013, vol. 138; https://doi.org/10.1063/1.4798222.

    Article  ADS  Google Scholar 

  10. Alkhwaji, A., Elbahloul, S., Abdullah, M.Z., and Bakar, K.F.B.A., Selected Water Thermal Properties from Molecular Dynamics for Engineering Purposes, J. Mol. Liq., 2020; https://doi.org/10.1016/ j.molliq.2020.114703.

    Article  Google Scholar 

  11. Abbasi, M., Heyhat, M.M., and Rajabpour, A., Study of the Effects of Particle Shape and Base Fluid Type on Density of Nanofluids Using Ternary Mixture Formula: A Molecular Dynamics Simulation, J. Mol. Liq., 2020, vol. 305; https://doi.org/10.1016/j.molliq.2020.112831.

    Article  Google Scholar 

  12. Wang, X. and Jing, D., Determination of Thermal Conductivity of Interfacial Layer in Nanofluids by Equilibrium Molecular Dynamics Simulation, Int. J. Heat Mass Transfer, 2019, vol. 128, pp. 199–207; https://doi.org/10.1016/j.ijheatmasstransfer.2018.08.073.

    Article  Google Scholar 

  13. Sirk, T.W., Moore, S., and Brown, E.F., Characteristics of Thermal Conductivity in Classical Water Models, J. Chem. Phys., 2013, vol. 138; https://doi.org/10.1063/1.4789961.

    Article  ADS  Google Scholar 

  14. Orsi, M., Comparative Assessment of the ELBA Coarse-Grained Model for Water, Mol. Phys., 2014, vol. 112, pp. 1566–1576; https://doi.org/10.1080/00268976.2013.844373.

    Article  ADS  Google Scholar 

  15. Helfand, E., Transport Coefficients from Dissipation in a Canonical Ensemble, Phys. Rev., 1960, vol. 119, pp. 1–9; https://doi.org/10.1103/PhysRev.119.1.

    Article  ADS  MathSciNet  MATH  Google Scholar 

  16. Kirova, E.M. and Norman, G.E., Viscosity Calculations at Molecular Dynamics Simulations, 2016; https://doi.org/10.1088/1742-6596/653/1/012106.

    Article  Google Scholar 

  17. Zhao, X. and Jin, H., Investigation of Hydrogen Diffusion in Supercritical Water: A Molecular Dynamics Simulation Study, Int. J. Heat Mass Transfer, 2019, vol. 133, pp. 718–728; https://doi.org/10.1016/ j.ijheatmasstransfer.2018.12.164.

    Article  Google Scholar 

  18. Erdös, M., Frangou, M., Vlugt, T.J.H., and Moultos, O.A., Diffusivity of \(\alpha\)-, \(\beta\)-, \(\gamma\)-Cyclodextrin and the Inclusion Complex of \(\beta\)-Cyclodextrin: Ibuprofen in Aqueous Solutions; A Molecular Dynamics Simulation Study, Fluid Phase Equilib., 2021, vol. 528; https://doi.org/10.1016/j.fluid.2020.112842.

    Article  Google Scholar 

  19. Boyd, S.J., Krishnan, Y., Ghaani, M.R., and English, N.J., Influence of External Static and Alternating Electric Fields on Self-Diffusion of Water from Molecular Dynamics, J. Mol. Liq., 2021, vol. 327, p. 114788; https://doi.org/10.1016/j.molliq.2020.114788.

    Article  Google Scholar 

  20. Meyer, N., Piquet, V., Wax, J.F., Xu, H., and Millot, C., Rotational and Translational Dynamics of the SPC/E Water Model, J. Mol. Liq., 2019, vol. 275, pp. 895–908; https://doi.org/10.1016/j.molliq.2018.08.024.

    Article  Google Scholar 

  21. Arismendi-Arrieta, D., Medina, J.S., Fanourgakis, G.S., Prosmiti, R., and Delgado-Barrio, G., Simulating Liquid Water for Determining Its Structural and Transport Properties, Appl. Radiat. Isot., 2014, vol. 83, pp. 115–121; https://doi.org/10.1016/j.apradiso.2013.01.020.

    Article  Google Scholar 

  22. Meier, K., Laesecke, A., and Kabelac, S., Transport Coefficients of the Lennard-Jones Model Fluid. I. Viscosity, J. Chem. Phys., 2004, vol. 121, pp. 671–3687; https://doi.org/10.1063/1.1770695.

    Article  ADS  Google Scholar 

  23. Scott, R., Allen, M.P., and Tildesley, D.J., Computer Simulation of Liquids, Math. Comput., 1991, vol. 57, p. 442; https://doi.org/10.2307/2938686.

    Article  Google Scholar 

  24. Jamali, S.H., Hartkamp, R., Bardas, C., Söhl, J., Vlugt, T.J.H., and Moultos, O.A., Shear Viscosity Computed from the Finite-Size Effects of Self-Diffusivity in Equilibrium Molecular Dynamics, J. Chem. Theory Comput., 2018, vol. 14, pp. 5959–5968; https://doi.org/10.1021/acs.jctc.8b0062.

    Article  Google Scholar 

  25. Jabbari, F., Rajabpour, A., and Saedodin, S., Viscosity of Carbon Nanotube/Water Nanofluid: Equilibrium Molecular Dynamics, J. Therm. An. Calorim., 2019, vol. 135, pp. 1787–1796; https://doi.org/10.1007/ s10973-018-7458-6.

    Article  Google Scholar 

  26. Mori, H., Statistical-Mechanical Theory of Transport in Fluids, Phys. Rev., 1958, vol. 112, pp. 1829–1842; https://doi.org/10.1103/PhysRev.112.1829.

    Article  ADS  MathSciNet  MATH  Google Scholar 

  27. Abou-Tayoun, N.H., Molecular Dynamics Simulation of Thermal Conductivity Enhancement of Copper-Water Nanofluid, 2012; http://hdl.handle.net/11073/2765.

  28. Zhao, Z., Sun, C., and Zhou, R., Thermal Conductivity of Confined-Water in Graphene Nanochannels, Int. J. Heat Mass Transfer, 2020, vol. 152; https://doi.org/10.1016/j.ijheatmasstransfer.2020.119502.

    Article  Google Scholar 

  29. Ghasemi, M., Niknejadi, M., and Toghraie, D., Direct Effect of Nanoparticles on the Thermal Conductivity of CuO-Water Nanofluid in a Phase Transition Phenomenon Using Molecular Dynamics Simulation, J. Therm. An. Calorim., 2021; https://doi.org/10.1007/s10973-020-10453-z.

    Article  Google Scholar 

  30. Ju, L., Basics of Thermal Conductivity Calculations, 1995; http://li.mit.edu/Archive/Papers/95/ Li95.pdf.

  31. Zhang, M., Lussetti, E., De Souza, L.E.S., and Müller-Plathe, F., Thermal Conductivities of Molecular Liquids by Reverse Nonequilibrium Molecular Dynamics, J. Phys. Chem. B., 2005, vol. 109, pp. 15060–15067; https://doi.org/10.1021/jp0512255.

    Article  Google Scholar 

  32. Jabbari, F., Rajabpour, A., and Saedodin, S., Thermal Conductivity and Viscosity of Nanofluids: A Review of Recent Molecular Dynamics Studies, Chem. Eng. Sci., 2017, vol. 174, pp. 67–81; https://doi.org/10.1016/ j.ces.2017.08.034.

    Article  ADS  Google Scholar 

  33. Abu-Hamdeh, N.H., Almatrafi, E., Hekmatifar, M., Toghraie, D., and Golmohammadzadeh, A., Molecular Dynamics Simulation of the Thermal Properties of the Cu-Water Nanofluid on a Roughed Platinum Surface: Simulation of Phase Transition in Nanofluids, J. Mol. Liq., 2020; https://doi.org/10.1016/ j.molliq.2020.114832.

    Article  Google Scholar 

  34. Bresme, F. and Römer, F., Heat Transport in Liquid Water at Extreme Pressures: A Non Equilibrium Molecular Dynamics Study, J. Mol. Liq., 2013, vol. 185, pp. 1–7; https://doi.org/10.1016/j.molliq.2012.09.013.

    Article  Google Scholar 

  35. Tsimpanogiannis, I.N., Moultos, O.A., Franco, L.F.M., de M. Spera, M.B., Erdös, M., and Economou, I.G., Self-Diffusion Coefficient of Bulk and Confined Water: A Critical Review of Classical Molecular Simulation Studies, Mol. Simul., 2019, vol. 45, pp. 425–453; https://doi.org/10.1080/08927022.2018.1511903.

    Article  Google Scholar 

  36. Jamali, S.H., Wolff, L., Becker, T.M., Bardow, A., Vlugt, T.J.H., and Moultos, O.A., Finite-Size Effects of Binary Mutual Diffusion Coefficients from Molecular Dynamics, J. Chem. Theory Comput., 2018, vol. 14, pp. 2667–2677; https://doi.org/10.1021/acs.jctc.8b00170.

    Article  Google Scholar 

  37. Pouramini, Z., Mohebbi, A., and Kowsari, M.H., Atomistic Insights into the Thermodynamics, Structure, and Dynamics of Ionic Liquid 1-hexyl-3-methylimidazolium Hexafluorophosphate via Molecular Dynamics Study, J. Mol. Liq., 2017, vol. 246, pp. 39–47; https://doi.org/10.1016/j.molliq.2017.09.043.

    Article  Google Scholar 

  38. Srivastava, A., Malik, S., and Debnath, A., Heterogeneity in Structure and Dynamics of Water near Bilayers Using TIP3P and TIP4P/2005 Water Models, Chem. Phys., 2019, vol. 525, p. 110396; https://doi.org/ 10.1016/j.chemphys.2019.110396.

    Article  Google Scholar 

  39. Holz, M., Heil, S.R., and Sacco, A., Temperature-Dependent Self-Diffusion Coefficients of Water and Six Selected Molecular Liquids for Calibration in Accurate 1H NMR PFG Measurements, Phys. Chem. Chem. Phys. 2, 2000, vol. 4740–4742; https://doi.org/10.1039/b005319h.

    Article  Google Scholar 

  40. Korson, L., Drost-Hansen, W., and Millero, F.J., Viscosity of Water at Various Temperatures, J. Phys. Chem., 1969, vol. 73, pp. 34–39; https://doi.org/10.1021/j100721a006.

    Article  Google Scholar 

  41. Haynes, W.M., CRC Handbook of Chemistry and Physics, 95th ed. ( Internet Version 2015), 2015.

Download references

Author information

Authors and Affiliations

  1. Department of Chemical Engineering, Faculty of Engineering, Shahid Bahonar University of Kerman, Kerman, Iran

    H. Dorrani & A. Mohebbi

Authors
  1. H. Dorrani
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. Mohebbi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to A. Mohebbi.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dorrani, H., Mohebbi, A. A Comparative Study of TIP4P-2005, SPC/E, SPC, and TIP3P-Ew Models for Predicting Water Transport Coefficients Using EMD and NEMD Simulations. J. Engin. Thermophys. 32, 138–161 (2023). https://doi.org/10.1134/S1810232823010113

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S1810232823010113

Search

Navigation