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Studying the influence of surface roughness with different shapes and quantities on convective heat transfer of fluid within nanochannels using molecular dynamics simulations

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Abstract

Context

In the past decade, rapid advancements in microtechnology and nanotechnology have propelled modern science and technology into the nanoscale domain, where miniaturization and high integration have found extensive applications across various fields, including industry, biotechnology, and information technology. Mechanisms of nanofluid flow and heat transfer properties have received increasing attention. In the flow and convective heat transfer of fluids at the nanoscale, the shape and dimensions of the surfaces play a crucial role. So, the main purpose of our paper is to investigate the influence of surface roughness with different shapes and quantities on fluid flow and convective heat transfer. In this study, we have chosen argon atoms as the fluid and used copper atoms to simulate the nanochannel walls. In order to investigate the influence of the shape and quantity of roughness on the convective heat transfer of fluids within nanochannels, we computed and analyzed the velocity, temperature, and density distributions of fluids inside channels with triangular, hemispherical, and rectangular roughness. Through simulation results, we found that triangular, hemispherical, and rectangular surface roughness at the same height can result in differences in temperature and velocity of the fluid within nanochannels. With a nanochannel roughness number of 5, the temperature and velocity of the fluid at the middle position of the nano-channel for the triangular roughness increased by 6% and 25% compared to the rectangular roughness, and by 4% and 10% compared to the hemispherical roughness. The fluid temperature and velocity are highest in channels with triangular surface roughness and lowest in those with rectangular roughness. Furthermore, increasing the quantity of surface roughness decreases the temperature and velocity of the fluid within nanochannels. When the quantity of rectangular surface roughness is 5, the fluid temperature within the nanochannel decreases by 12%, and the velocity decreases by 38% compared to a roughness quantity of 1. We also found, through velocity contours, that the presence of roughness increases the local fluid velocity in the rough regions of nanochannels. Roughness also reduces the density fluctuations of the fluid near the walls within the nanochannel. Roughness significantly affects the heat transfer performance of the fluid during its flow, and this influence should not be overlooked.

Methods

In this study, molecular dynamics theory was employed, and simulations were conducted using the open-source software LAMMPS to investigate the influence of different shapes and quantities of surface roughness on fluid flow within nanochannels. The model in this paper was constructed using the LAMMPS software, and the surface roughness shapes on the walls were implemented as rectangular, hemispherical, and triangular. The wall surfaces were composed of copper atoms, while the fluid consisted of argon atoms. The copper atoms were arranged in a face-centered cubic (FCC) lattice with a lattice constant of 3.615 Å. Similarly, the argon atoms were arranged in a face-centered cubic (FCC) lattice with a lattice constant of 5.62 Å. The interactions between copper atoms were modeled using the EAM (Embedded Atom Method) potential, while the interactions between argon atoms were described using the LJ (Lennard-Jones) potential. The LJ potential was also employed to represent interactions between argon and copper atoms.

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Data Availability

The data and materials used in this study are available upon request.

References

  1. Ahmad F, Cheema TA, Ur Rehman MM et al (2019) Thermal enhancement of microchannel heat sink using rib surface refinements. Numer Heat Transf A: Appl 76:851–870

    Article  ADS  Google Scholar 

  2. Kurtulmuş N, Sahin B (2019) A review of hydrodynamics and heat transfer through corrugated channels. Int Commun Heat Mass Transf 108. https://doi.org/10.1016/j.icheatmasstransfer.2019.104307

  3. Arora N, Gupta M (2020) An updated review on application of nanofluids in flat tubes radiators for improving cooling performance. Renew Sust Energ Rev 134. https://doi.org/10.1016/j.rser.2020.110242

  4. Mahian O, Kolsi L, Amani M et al (2019) Recent advances in modeling and simulation of nanofluid flows-Part I: Fundamentals and theory. Phys Rep 790:1–48

    Article  MathSciNet  CAS  ADS  Google Scholar 

  5. Wen D, Ding Y (2004) Experimental investigation into convective heat transfer of nanofluids at the entrance region under laminar flow conditions. Int J Heat Mass Transf 47:5181–5188

    Article  CAS  Google Scholar 

  6. Allen MP, Tildesley DJ, Banavar JR (1989) Computer simulation of liquids. Phys Today 42:105–106

    Article  Google Scholar 

  7. Brown WM, Wang P, Plimpton SJ et al (2011) Implementing molecular dynamics on hybrid high performance computers – short range forces. Comput Phys Commun 182:898–911

    Article  CAS  ADS  Google Scholar 

  8. Plimpton SJ, Thompson AP (2012) Computational aspects of many-body potentials. MRS Bull 37:513–521

    Article  CAS  Google Scholar 

  9. Rezaei M, Azimian AR, Toghraie D (2015) Molecular dynamics study of an electro-kinetic fluid transport in a charged nanochannel based on the role of the stern layer. Physica A: Stat Mech Appl 426:25–34

    Article  CAS  Google Scholar 

  10. Toghraie Semironi D, Azimian AR (2009) Molecular dynamics simulation of liquid–vapor phase equilibrium by using the modified Lennard-Jones potential function. Heat Mass Transf 46:287–294

    Article  ADS  Google Scholar 

  11. Noorian H, Toghraie D, Azimian AR (2013) The effects of surface roughness geometry of flow undergoing Poiseuille flow by molecular dynamics simulation. Heat Mass Transf 50:95–104

    Article  ADS  Google Scholar 

  12. Qin Y, Zhao J, Liu Z et al (2022) Study on effect of different surface roughness on nanofluid flow in nanochannel by using molecular dynamics simulation J Mol Liq 346. https://doi.org/10.1016/j.molliq.2021.117148

  13. Raj V, Babu JS (2019) Effect of roughness structures on the fluid-solid interfacial properties in nanoscale channels. In: Proceedings of the International Engineering Research Conference - 12th Eureca 2019. https://doi.org/10.1063/1.5120209

  14. Li Q, Liu C (2012) Molecular dynamics simulation of heat transfer with effects of fluid–lattice interactions. Int J Heat Mass Transf 55:8088–8092

    Article  CAS  Google Scholar 

  15. Sofos F, Karakasidis T, Liakopoulos A (2009) Transport properties of liquid argon in krypton nanochannels: anisotropy and non-homogeneity introduced by the solid walls. Int J Heat Mass Transf 52:735–743

    Article  CAS  Google Scholar 

  16. Sofos F, Karakasidis TE, Giannakopoulos AE et al (2015) Molecular dynamics simulation on flows in nano-ribbed and nano-grooved channels. Heat Mass Transf 52:153–162

    Article  ADS  Google Scholar 

  17. Zhang Y (2016) Effect of wall surface roughness on mass transfer in a nano channel. Int J Heat Mass Transf 100:295–302

    Article  CAS  Google Scholar 

  18. Yan S-R, Toghraie D, Hekmatifar M et al (2020) Molecular dynamics simulation of Water-Copper nanofluid flow in a three-dimensional nanochannel with different types of surface roughness geometry for energy economic management. J Mol Liq 311. https://doi.org/10.1016/j.molliq.2020.113222

  19. Alipour P, Toghraie D, Karimipour A (2019) Investigation the atomic arrangement and stability of the fluid inside a rough nanochannel in both presence and absence of different roughness by using of accurate nano scale simulation. Physica A: Stat Mech Appl 524:639–660

    Article  CAS  Google Scholar 

  20. Toghraie Semiromi D, Azimian AR (2010) Nanoscale Poiseuille flow and effects of modified Lennard–Jones potential function. Heat Mass Transf 46:791–801

    Article  CAS  ADS  Google Scholar 

  21. Toghraie D, Hekmatifar M, Salehipour Y et al (2019) Molecular dynamics simulation of Couette and Poiseuille Water-Copper nanofluid flows in rough and smooth nanochannels with different roughness configurations. Chem Phys 527. https://doi.org/10.1016/j.chemphys.2019.110505

  22. Yan S-R, Shirani N, Zarringhalam M et al (2020) Prediction of boiling flow characteristics in rough and smooth microchannels using molecular dynamics simulation: investigation the effects of boundary wall temperatures. J Mol Liq 306. https://doi.org/10.1016/j.molliq.2020.112937

  23. Yao S, Wang J, Liu X (2021) The impacting mechanism of surface properties on flow and heat transfer features in nanochannel. Int J Heat Mass Transf 176. https://doi.org/10.1016/j.ijheatmasstransfer.2021.121441

  24. Yao S, Wang J, Liu X (2021) Role of wall-fluid interaction and rough morphology in heat and momentum exchange in nanochannel. Appl Energy 298. https://doi.org/10.1016/j.apenergy.2021.117183

  25. Song Z, Cui Z, Cao Q et al (2021) Molecular dynamics study of convective heat transfer in ordered rough nanochannels. J Mol Liq 337. https://doi.org/10.1016/j.molliq.2021.116052

  26. Marable DC, Shin S, Yousefzadi Nobakht A (2017) Investigation into the microscopic mechanisms influencing convective heat transfer of water flow in graphene nanochannels. Int J Heat Mass Transf 109:28–39

    Article  CAS  Google Scholar 

  27. Bagheri Motlagh M, Kalteh M (2020) Molecular dynamics simulation of nanofluid convective heat transfer in a nanochannel: effect of nanoparticles shape, aggregation and wall roughness. J Mol Liq 318. https://doi.org/10.1016/j.molliq.2020.114028

  28. Bagheri Motlagh M, Kalteh M (2020) Simulating the convective heat transfer of nanofluid Poiseuille flow in a nanochannel by molecular dynamics method. Int Commun Heat Mass Transf 111. https://doi.org/10.1016/j.icheatmasstransfer.2020.104478

  29. Plimpton S (1995) Fast parallel algorithms for short-range molecular dynamics. J Comput Phys 117:1–19

    Article  CAS  ADS  Google Scholar 

  30. Stukowski A, Albe K (2010) Extracting dislocations and non-dislocation crystal defects from atomistic simulation data. Model Simul Mater Sci Eng 18. https://doi.org/10.1088/0965-0393/18/8/085001

  31. Li Y, Xu J, Li D (2010) Molecular dynamics simulation of nanoscale liquid flows. Microfluid Nanofluid 9:1011–1031

    Article  Google Scholar 

  32. Foiles SM, Baskes MI, Daw MS (1986) Embedded-atom-method functions for the fcc metals Cu, Ag, Au, Ni, Pd, Pt, and their alloys. Phys Rev B Condens Matter 33:7983–7991

    Article  CAS  PubMed  ADS  Google Scholar 

  33. Caro A, Crowson DA, Caro M (2005) Classical many-body potential for concentrated alloys and the inversion of order in iron-chromium alloys. Phys Rev Lett 95:075702

    Article  CAS  PubMed  ADS  Google Scholar 

  34. Stukowski A, Sadigh B, Erhart P et al (2009) Efficient implementation of the concentration-dependent embedded atom method for molecular-dynamics and Monte-Carlo simulations. Model Simul Mater Sci Eng 17. https://doi.org/10.1088/0965-0393/17/7/075005

  35. Mayo SL, Olafson BD, Goddard WA (2002) DREIDING: a generic force field for molecular simulations. J Phys Chem 94:8897–8909

    Article  Google Scholar 

  36. Ge S, Gu Y, Chen M (2014) A molecular dynamics simulation on the convective heat transfer in nanochannels. Mol Phys 113:703–710

    Article  ADS  Google Scholar 

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YL: writing—review and editing, investigation. CC: methodology, software.

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Correspondence to Yaxin Li.

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Chen, C., Li, Y. Studying the influence of surface roughness with different shapes and quantities on convective heat transfer of fluid within nanochannels using molecular dynamics simulations. J Mol Model 30, 42 (2024). https://doi.org/10.1007/s00894-024-05840-4

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