4.7 Article

Mesoscopic method to study water flow in nanochannels with different wettability

期刊

PHYSICAL REVIEW E
卷 102, 期 1, 页码 -

出版社

AMER PHYSICAL SOC
DOI: 10.1103/PhysRevE.102.013306

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资金

  1. National Natural Science Foundation Projects of China [50974128, 51504269, 51490654]
  2. National Science and Technology Major Projects of China [2016ZX05042, 2017ZX05009003, 2017ZX05039005]
  3. Science Foundation of China University of Petroleum, Beijing [2462018YJRC033, C201605]
  4. NanoGeosciences lab
  5. Mudrock Systems Research Laboratory at the Bureau of Economic Geology
  6. China Scholarship Council (CSC)

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Molecular dynamics (MD) simulations is currently the most popular and credible tool to model water flow in nanoscale where the conventional continuum equations break down due to the dominance of fluid-surface interactions. However, current MD simulations are computationally challenging for the water flow in complex tube geometries or a network of nanopores, e.g., membrane, shale matrix, and aquaporins. We present a novel mesoscopic lattice Boltzmann method (LBM) for capturing fluctuated density distribution and a nonparabolic velocity profile of water flow through nanochannels. We incorporated molecular interactions between water and the solid inner wall into LBM formulations. Details of the molecular interactions were translated into true and apparent slippage, which were both correlated to the surface wettability, e.g., contact angle. Our proposed LBM was tested against 47 published cases of water flow through infinite-length nanochannels made of different materials and dimensions-flow rates as high as seven orders of magnitude when compared with predictions of the classical no-slip Hagen-Poiseuille (HP) flow. Using the developed LBM model, we also studied water flow through finite-length nanochannels with tube entrance and exit effects. Results were found to be in good agreement with 44 published finite-length cases in the literature. The proposed LBM model is nearly as accurate as MD simulations for a nanochannel, while being computationally efficient enough to allow implications for much larger and more complex geometrical nanostructures.

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