Skip to main content
Log in

Studying the viscosity of methane fluid for different resolution levels models using Poiseuille flow in a nano-channel

  • Research Paper
  • Published:
Microfluidics and Nanofluidics Aims and scope Submit manuscript

Abstract

In this work, the viscosity–temperature–density relationship of methane is investigated for three fully atomistic models (RISM, OPLS and MOPLS) and the corresponding coarse-grained models (CGRISM, CGOPLS and CGMOPLS) by studying the Poiseuille flow inside a silicon nano-channel using molecular dynamic simulation. In order to solve the interaction problem of nano-channel atom and methane molecule, the coarse-grained methane model and the classical Berthelot–Lorentz mixing rules are employed. The optimized coarse-grained methane models are determined using the relative entropy minimization method. The density distribution, stress force profile and velocity profile of coarse-grained models are compared with the fully atomistic models for different nano-channel widths. It is concluded that the results of coarse-grained model are in reasonable agreement with those of the corresponding fully atomistic model. Furthermore, the value of viscosity is calculated by fitting the velocity profile to the continuum solution from the Navier–Stokes equations and then compared to experimental value. The results show that the MOPLS and CGMOPLS models could well predict the viscosity of methane fluid, while the OPLS model performed worst. All simulation results indicate that the coarse-grained models can be used to predict the viscosity of methane fluid accurately.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Abbaspour M (2011) Computation of some thermodynamics, transport, structural properties, and new equation of state for fluid methane using two-body and three-body intermolecular potentials from molecular dynamics simulation. J Mol Liq 161:30–35

  • Allen MP, Tildesley DJ (1989) Computer simulation of liquids. Oxford University Press

  • Arya G, Maginn EJ, Chang H-C (2000) Efficient viscosity estimation from molecular dynamics simulation via momentum impulse relaxation. J Chem Phys 113:2079–2087

    Article  Google Scholar 

  • Backer J, Lowe C, Hoefsloot H, Iedema P (2005) Poiseuille flow to measure the viscosity of particle model fluids. J Chem Phys 122:154503

    Article  Google Scholar 

  • Beerling D, Berner RA, Mackenzie FT, Harfoot MB, Pyle JA (2009) Methane and the CH4 related greenhouse effect over the past 400 million years. Am J Sci 309:97–113

    Article  Google Scholar 

  • Bhadauria R, Aluru N (2013) A quasi-continuum hydrodynamic model for slit shaped nanochannel flow. J Chem Phys 139:074109

    Article  Google Scholar 

  • Bhadauria R, Sanghi T, Aluru N (2015) Interfacial friction based quasi-continuum hydrodynamical model for nanofluidic transport of water. J Chem Phys 143:174702

    Article  Google Scholar 

  • Bird RB (2002) Transport phenomena. Appl Mech Rev 55:R1–R4

    Article  Google Scholar 

  • Bird R, Stewart W, Lightfoot E (1960) Transport phenomena. Wiley, New York, pp 59, 67

  • Boon J-P, Legros JC, Thomaes G (1967) On the principle of corresponding states for the viscosity of simple liquids. Physica 33:547–557

    Article  Google Scholar 

  • Bruhn D, Møller IM, Mikkelsen TN, Ambus P (2012) Terrestrial plant methane production and emission. Physiol Plant 144:201–209

    Article  Google Scholar 

  • Chan DY, Horn R (1985) The drainage of thin liquid films between solid surfaces. J Chem Phys 83:5311–5324

    Article  Google Scholar 

  • Diller DE (1980) Measurements of the viscosity of compressed gaseous and liquid methane. Phys A 104:417–426

    Article  Google Scholar 

  • El-Sheikh SM, Barakat K, Salem NM (2006) Phase transitions of methane using molecular dynamics simulations. J Chem Phys 124(12):124517

    Article  Google Scholar 

  • Frenkel D, Smit B (2001) Understanding molecular simulation: from algorithms to applications. Academic press, New Jersey

    MATH  Google Scholar 

  • García-Rojo R, Luding S, Brey JJ (2006) Transport coefficients for dense hard-disk systems. Phys Rev E 74:061305

    Article  Google Scholar 

  • Goodwin AR (2008) A MEMS vibrating edge supported plate for the simultaneous measurement of density and viscosity: results for argon, nitrogen, and methane at temperatures from (297 to 373) K and pressures between (1 and 62) MPa. J Chem Eng Data 54:536–541

    Article  Google Scholar 

  • Gosling EM, McDonald I, Singer K (1973) On the calculation by molecular dynamics of the shear viscosity of a simple fluid. Mol Phys 26:1475–1484

    Article  Google Scholar 

  • Habenschuss A, Johnson E, Narten A (1981) X-ray diffraction study and models of liquid methane at 92 K. J Chem Phys 74:5234–5241

    Article  Google Scholar 

  • Haile J (1993) Molecular dynamics simulation: elementary methods. Comput Phys 7:625

    Article  Google Scholar 

  • Hanley HJ, McCarty RD, Haynes WM (1974) The viscosity and thermal conductivity coefficients for dense gaseous and liquid argon, krypton, xenon, nitrogen, and oxygen. J Phys Chem Ref Data 3:979–1017

    Article  Google Scholar 

  • Hanley HJ, Haynes WM, McCarty RD (1977) The viscosity and thermal conductivity coefficients for dense gaseous and liquid methane. J Phys Chem Ref Data 6:597–610

    Article  Google Scholar 

  • Hansen J-P, McDonald IR (1990) Theory of simple liquids. Elsevier, New York

    MATH  Google Scholar 

  • Hartkamp R, Ghosh A, Weinhart T, Luding S (2012) A study of the anisotropy of stress in a fluid confined in a nanochannel. J Chem Phys 137:044711

    Article  Google Scholar 

  • Haynes W (1973) Viscosity of saturated liquid methane. Physica 70:410–412

    Article  Google Scholar 

  • Hess B (2002) Determining the shear viscosity of model liquids from molecular dynamics simulations. J Chem Phys 116:209–217

    Article  Google Scholar 

  • Heyes DM (1988) Transport coefficients of Lennard–Jones fluids: a molecular-dynamics and effective-hard-sphere treatment. Phys Rev B 37:5677

    Article  Google Scholar 

  • Horsch M, Vrabec J, Bernreuther M, Hasse H (2009) Poiseuille flow of liquidmethane in nanoscopic graphite channels by molecular dynamics simulation. In ICHMT digital library online. Begel House Inc, Danbury

    Google Scholar 

  • Hu C, Bai M, Lv J, Kou Z, Li X (2015) Molecular dynamics simulation on the tribology properties of two hard nanoparticles (diamond and silicon dioxide) confined by two iron blocks. Tribol Int 90:297–305

    Article  Google Scholar 

  • Hurly J, Gillis K, Mehl J, Moldover M (2003) The viscosity of seven gases measured with a greenspan viscometer. Int J Thermophys 24:1441–1474

    Article  Google Scholar 

  • Jiang C, Ouyang J, Zhuang X, Wang L, Li W (2016) An efficient fully atomistic potential model for dense fluid methane. J Mol Struct 1117:192–200

    Article  Google Scholar 

  • Jorgensen WL, Madura JD, Swenson CJ (1984) Optimized intermolecular potential functions for liquid hydrocarbons. J Am Chem Soc 106:6638–6646

    Article  Google Scholar 

  • Kamal C, Chakrabarti A, Banerjee A, Deb S (2013) Silicene beyond mono-layers-different stacking configurations and their properties. J Phys Condens Mat 25:085508

    Article  Google Scholar 

  • Karniadakis GE, Beskok A, Aluru N (2006) Microflows and nanoflows: fundamentals and simulation. Springer, New York

    MATH  Google Scholar 

  • Kim JM, Phillips RJ (2004) Dissipative particle dynamics simulation of flow around spheres and cylinders at finite Reynolds numbers. Chem Eng Sci 59:4155–4168

    Article  Google Scholar 

  • Kong CL (1973) Combining rules for intermolecular potential parameters. II. Rules for the Lennard–Jones (12–6) potential and the Morse potential. J Chem Phys 59:2464–2467

    Article  Google Scholar 

  • Li T-D, Gao J, Szoszkiewicz R, Landman U, Riedo E (2007) Structured and viscous water in subnanometer gaps. Phys Rev B 75:115415

    Article  Google Scholar 

  • Markesteijn A, Hartkamp R, Luding S, Westerweel J (2012) A comparison of the value of viscosity for several water models using Poiseuille flow in a nano-channel. J Chem Phys 136:134104

    Article  Google Scholar 

  • Mashayak S, Aluru N (2012a) Coarse-grained potential model for structural prediction of confined water. J Chem Theory Comput 8:1828–1840

    Article  Google Scholar 

  • Mashayak S, Aluru N (2012b) Thermodynamic state-dependent structure-based coarse-graining of confined water. J Chem Phys 137:214707

    Article  Google Scholar 

  • Matthews GP, Smith EB (1976) An intermolecular pair potential energy function for methane. Mol Phys 32:1719–1729

    Article  Google Scholar 

  • Meda B, Flechard C, Germain K, Robin P, Walter C, Hassouna M (2012) Greenhouse gas emissions from the grassy outdoor run of organic broilers. Biogeosciences 9:1493–1508

    Article  Google Scholar 

  • Mei J, Diao Y, Appleton AL, Fang L, Bao Z (2013) Integrated materials design of organic semiconductors for field-effect transistors. J Am Chem Soc 135:6724–6746

    Article  Google Scholar 

  • Meier K, Laesecke A, Kabelac S (2004) Transport coefficients of the Lennard–Jones model fluid. I. Viscosity. J Chem Phys 121:3671–3687

    Article  Google Scholar 

  • Meier K, Laesecke A, Kabelac S (2005) Transport coefficients of the Lennard–Jones model fluid. III. Bulk viscosity. J Chem Phys 122:014513

    Article  Google Scholar 

  • Murad S, Evans D, Gubbins K, Streett W, Tildesley D (1979) Molecular dynamics simulation of dense fluid methane. Mol Phys 37:725–736

    Article  Google Scholar 

  • Poling BE, Prausnitz JM, O’connell JP (2001) The properties of gases and liquids. McGraw-Hill, New York

    Google Scholar 

  • Ranjith SK, Patnaik B, Vedantam S (2013) No-slip boundary condition in finite-size dissipative particle dynamics. J Comput Phys 232:174–188

    Article  MathSciNet  Google Scholar 

  • Rapaport DC (2004) The art of molecular dynamics simulation. Cambridge University Press, Cambridge

    Book  MATH  Google Scholar 

  • Righini R, Maki K, Klein ML (1981) An intermolecular potential for methane. Chem Phys Lett 80:301–305

    Article  Google Scholar 

  • Sadus RJ (2002) Molecular simulation of fluids. Elsevier, New York

    Google Scholar 

  • Schiermeier Q (2006) Methane finding baffles scientists. Nature 439:128

    Article  Google Scholar 

  • Schley P, Jaeschke M, Küchenmeister C, Vogel E (2004) Viscosity measurements and predictions for natural gas. Int J Therm 25:1623–1652

    Article  Google Scholar 

  • Shell MS (2008) The relative entropy is fundamental to multiscale and inverse thermodynamic problems. J Chem Phys 129:108

    Article  Google Scholar 

  • Stassen H (1999) On the pair potential in dense fluid methane. J Mol Struct Theochem 464:107–119

    Article  Google Scholar 

  • Sun C-Z, Lu W-Q, Bai B-F, Liu J (2014) Novel flow behaviors induced by a solid particle in nanochannels: Poiseuille and Couette. Chin Sci Bull 59:2478–2485

    Article  Google Scholar 

  • Travis KP, Todd B, Evans DJ (1997) Departure from Navier-Stokes hydrodynamics in confined liquids. Phys Rev E 55:4288

    Article  Google Scholar 

  • Van Der Gulik P, Mostert R, Van den Berg H (1992) The viscosity of methane at 273 K up to 1 GPa. Fluid Phase Equilib 79:301–311

    Article  Google Scholar 

  • Williams DE (1966) Nonbonded potential parameters derived from crystalline aromatic hydrocarbons. J Chem Phys 45:3770–3778

    Article  Google Scholar 

  • Xu J, Zhou Z, Xu X (2004) Molecular dynamics simulation of micro-Poiseuille flow for liquid argon in nanoscale. Int J Numer Method H 14:664–688

    Article  MATH  Google Scholar 

  • Zarkova L, Hohm U, Damyanova M (2006) Viscosity, second pVT-virial coefficient, and diffusion of pure and mixed small alkanes CH4, C2H6, C3H8, n-C4H10, i-C4H10, n-C5H12, i-C5H12, and C(CH3)4 calculated by means of an isotropic temperature-dependent potential. I. Pure alkanes. J Phys Chem Ref Data 35:1331–1364

    Article  Google Scholar 

  • Zhang C, Duan Z, Zhang Z (2007) Molecular dynamics simulation of the CH4 and CH4–H2O systems up to 10 GPa and 2573K. Geochim Cosmochim Acta 71:2036–2055

    Article  Google Scholar 

  • Ziarani A, Mohamad A (2006) A molecular dynamics study of perturbed Poiseuille flow in a nanochannel. Microfluid Nanofluid 2:12–20

    Article  Google Scholar 

Download references

Acknowledgements

We gratefully acknowledge the anonymous referees for the valuable suggestions and discussions that helped improving the paper clarity and readability. This work is financially supported by the National Basic Research Program of China (973 Program) (Grant No. 2012CB025903), the Major Research Plan of the National Natural Science Foundation of China (Grant No. 91434201) and the National Natural Science Foundation of China (Grant No. 11402210).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jie Ouyang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jiang, C., Ouyang, J., Liu, Q. et al. Studying the viscosity of methane fluid for different resolution levels models using Poiseuille flow in a nano-channel. Microfluid Nanofluid 20, 157 (2016). https://doi.org/10.1007/s10404-016-1824-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10404-016-1824-0

Keywords

Navigation