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Abstract
It is well-known that the Poiseuille mass flow rate along microchannels shows a stationary point as the fluid density decreases, referred to as the Knudsen minimum. Surprisingly, if the flow characteristic length is comparable to the molecular size, the Knudsen minimum disappears, as reported for the first time by Wu et al. (J. Fluid Mech., vol. 794, 2016, pp. 252-266). However, there is still no fundamental understanding why the mass flow rate monotonically increases throughout the entire range of flow regimes. Although diffusion is believed to dominate the fluid transport at the nanoscale, here we show that the Fick’s first law fails in capturing this behaviour, and so diffusion alone is insufficient to explain this confined flow phenomenon. Rather, we show that the Knudsen minimum disappears in tight confinements because the decay of the mass flow rate due to the decreasing density effects is overcome by the enhancing contribution to the flow provided by the fluid velocity slip at the wall.
| Original language | English |
|---|---|
| Article number | A28 |
| Number of pages | 10 |
| Journal | Journal of Fluid Mechanics |
| Volume | 945 |
| Early online date | 25 Jul 2022 |
| DOIs | |
| Publication status | Published - 25 Aug 2022 |
Keywords / Materials (for Non-textual outputs)
- rarefied gas flow
- Molecular Dynamics
- KINETIC THEORY
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Dive into the research topics of 'Knudsen Minimum Disappearance in Molecular-Confined Flows'. Together they form a unique fingerprint.Projects
- 2 Finished
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Multiscale Simulation of Rarefied Gas Flow for Engineering Design
Borg, M. (Principal Investigator) & Gibelli, L. (Co-investigator)
Engineering and Physical Sciences Research Council
1/01/21 → 31/12/24
Project: Research
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From Kinetic Theory to Hydrodynamics: re-imagining two fluid models of particle-laden flows
Borg, M. (Principal Investigator) & Reese, J. (Co-investigator)
1/10/17 → 30/09/21
Project: Research
Datasets
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Knudsen minimum disappearance in molecular-confined flows
Corral-Casas, C. (Creator), Edinburgh DataShare, 28 Jun 2022
DOI: 10.7488/ds/3480
Dataset