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Molecular dynamics method is used to investigate gas flows in nanoscale channels. A set of Couette gas flows with the same Knudsen number but different channel heights and densities is simulated to study the dimensional effects on dynamically similar flow conditions. Results show that the gas flow in the channels is divided into two regions:near wall region affected by a wall force field and bulk flow region affected by no wall force field. The flow characteristics in the bulk flow region are in good accordance with the kinetic theory predictions, which are characterized by constant density, normal stress, shear stress and linear velocity distribution while within the near wall region, the velocity, density, normal stress and shear stress distributions exhibit deviations from the kinetic theory predictions. The density and velocity sharply increase, accompanied with a single peak appearing. The normal stress which is dominated by the surface virial is anisotropic and changes drastically. Shear stress value is constant in bulk flow region and part of the near wall region, while the surface virial induces variation at a place about one atom diameter far from the wall. In the near wall region, the normalized density, velocity and stress tensor are constant under different channel heights and densities, which indicates that the gas flow characteristics in this area are determined by the wall force field. Besides, the tangential momentum accommodation coefficient (TMAC) values for different cases can be obtained through the relationship between TAMC and shear stress. It is found that under the same Knudsen number, the TMAC remains constant no matter what the height and density are. Furthermore, another set of Couette gas flows with different gas-surface potential strength ratios but the same channel height and density is simulated to study the gas-surface interaction effects on nanoscale gas flow. The results show that the gas density and velocity in the near wall region increase with increasing potential strength ratio between wall atoms and gas molecules. Large potential strength ratio cases (C 3.0) result in velocity sticking on the surface, which is induced by the gas molecule accumulation and surface adsorption. Using the same approach, the TMAC values for various potential strength ratios are calculated, varying from 0.63 to 0.96 for different cases (C=0.5-4.0), which indicates that the stronger the potential energy acting on the gas molecules, the more easily the gas molecules generate the diffuse reflection on the walls
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Keywords:
- nanoscale gas flow /
- surface force effects /
- shear stress /
- tangential momentum accommodation coefficient
[1] Ekinci K L, Roukes M L 2005 Rev. Sci. Instrum. 76 061101
[2] Verbridge S S, Craighead H G, Parpia J M 2008 Appl. Phys. Lett. 92 013112
[3] Boettcher U, Li H, Callafon R A, Talke F E 2011 IEEE T. Magn. 47 1823
[4] Song H Q, Yu M X, Z H U W Y, Zhang Y, Jiang S X 2013 Chin. Phys. Lett. 30 014701
[5] Tsien H S 1964 J. Aero. Sci. 13 653
[6] Zhang Z Q, Zhang H W, Ye H F 2009 Appl. Phys. Lett. 95 154101
[7] Zhang H W, Zhang Z Q, Zheng Y G, Ye H F 2010 Phys. Rev. E 81 066303
[8] Sone Y, Takata S, Ohwada T 1990 Euro. J. Mech. B:Fluids 9 273
[9] Taheri P, Torrilhon M, Struchtrup H 2009 Phys. Fluids 21 017102
[10] Dehdashti E 2016 Chin. Phys. B 25 024702
[11] Bird G A 1994 Molecular Gas Dynamics and the Direct Simulation of Gas Flows (Oxford:Oxford University Press) pp199-206
[12] Fan J, Shen C 1999 J. Comput. Phys. 167 393
[13] Rapaport D C 2004 The Art of Molecular Dynamics Simulation (New York:Cambridge University Press) pp4-5
[14] Thompson P A, Troian S M 1997 Nature 389 360
[15] Zhu Y X, Granick S 2002 Phys. Rev. Lett. 88 106102
[16] Cao B Y, Sun J, Chen M, Guo Z Y 2009 Int. J. Mol. Sci. 10 4638
[17] Finger G W, Kapat J S, Bhattacharya A 2007 J. Fluid Eng.-T. ASME 129 31
[18] Sun J, Li Z X 2008 Mol. Phys. 106 2325
[19] Sun J, Li Z X 2010 Comput. Fluids 39 1645
[20] Markvoort A J, Hilbers P A J, Nedea S V 2005 Phys. Rev. E 71 066702
[21] Arya G, Chang H C, Maginn E J 2003 Mol. Simul. 29 697
[22] Cao B Y, Chen M, Guo Z Y 2005 Appl. Phys. Lett. 86 091905
[23] Cao B Y, Chen M, Guo Z Y 2006 Acta Phys. Sin. 55 5305 (in Chinese)[曹炳阳, 陈民, 过增元 2006 55 5305]
[24] Xie H, Liu C 2012 AIP Adv. 2 042126
[25] Barisik M, Beskok A 2011 Microfluid Nanofluid 11 269
[26] Barisik M, Beskok A 2012 Microfluid Nanofluid 13 789
[27] Bao F B, Huang Y L, Qiu L M, Lin J Z 2014 Mol. Phys. 113 561
[28] Bao F B, Huang Y L, Zhang Y H, Lin J Z 2015 Microfluid Nanofluid 18 1075
[29] Yang Y T, Callegari C, Feng X L, Roukes M L 2011 Nano Lett. 11 1753
[30] Zhang W M, Meng G, Zhou J B, Chen J Y 2009 Sensors 9 3854
[31] Wu L, Bogy D B 2002 J. Tribol. -T. ASME 124 562
[32] Allen M P, Tildesley D J 1991 Computer Simulation of Liquids (Oxford:Oxford University Press) pp145-146
[33] Hook J R, Hall H E 1991 Solid State Physics (Chichester:Wiley) pp96-106
[34] Evans D J, Hoover W G 1986 Annu. Rev. Fluid Mech. 18 243
[35] Irving J H, Kirkwood J G 1950 J. Chem. Phys. 18 817
[36] Todd B D, Evans D J, Davis P J 1995 Phys. Rev. E 52 1627
[37] Fukui S, Shimada H, Yamane K, Matsuoka H 2005 Microsyst. Technol. 11 805
[38] Bahukudumbi P, Park J H, Beskok A 2003 Microscale Thermophy. Eng. 7 291
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[1] Ekinci K L, Roukes M L 2005 Rev. Sci. Instrum. 76 061101
[2] Verbridge S S, Craighead H G, Parpia J M 2008 Appl. Phys. Lett. 92 013112
[3] Boettcher U, Li H, Callafon R A, Talke F E 2011 IEEE T. Magn. 47 1823
[4] Song H Q, Yu M X, Z H U W Y, Zhang Y, Jiang S X 2013 Chin. Phys. Lett. 30 014701
[5] Tsien H S 1964 J. Aero. Sci. 13 653
[6] Zhang Z Q, Zhang H W, Ye H F 2009 Appl. Phys. Lett. 95 154101
[7] Zhang H W, Zhang Z Q, Zheng Y G, Ye H F 2010 Phys. Rev. E 81 066303
[8] Sone Y, Takata S, Ohwada T 1990 Euro. J. Mech. B:Fluids 9 273
[9] Taheri P, Torrilhon M, Struchtrup H 2009 Phys. Fluids 21 017102
[10] Dehdashti E 2016 Chin. Phys. B 25 024702
[11] Bird G A 1994 Molecular Gas Dynamics and the Direct Simulation of Gas Flows (Oxford:Oxford University Press) pp199-206
[12] Fan J, Shen C 1999 J. Comput. Phys. 167 393
[13] Rapaport D C 2004 The Art of Molecular Dynamics Simulation (New York:Cambridge University Press) pp4-5
[14] Thompson P A, Troian S M 1997 Nature 389 360
[15] Zhu Y X, Granick S 2002 Phys. Rev. Lett. 88 106102
[16] Cao B Y, Sun J, Chen M, Guo Z Y 2009 Int. J. Mol. Sci. 10 4638
[17] Finger G W, Kapat J S, Bhattacharya A 2007 J. Fluid Eng.-T. ASME 129 31
[18] Sun J, Li Z X 2008 Mol. Phys. 106 2325
[19] Sun J, Li Z X 2010 Comput. Fluids 39 1645
[20] Markvoort A J, Hilbers P A J, Nedea S V 2005 Phys. Rev. E 71 066702
[21] Arya G, Chang H C, Maginn E J 2003 Mol. Simul. 29 697
[22] Cao B Y, Chen M, Guo Z Y 2005 Appl. Phys. Lett. 86 091905
[23] Cao B Y, Chen M, Guo Z Y 2006 Acta Phys. Sin. 55 5305 (in Chinese)[曹炳阳, 陈民, 过增元 2006 55 5305]
[24] Xie H, Liu C 2012 AIP Adv. 2 042126
[25] Barisik M, Beskok A 2011 Microfluid Nanofluid 11 269
[26] Barisik M, Beskok A 2012 Microfluid Nanofluid 13 789
[27] Bao F B, Huang Y L, Qiu L M, Lin J Z 2014 Mol. Phys. 113 561
[28] Bao F B, Huang Y L, Zhang Y H, Lin J Z 2015 Microfluid Nanofluid 18 1075
[29] Yang Y T, Callegari C, Feng X L, Roukes M L 2011 Nano Lett. 11 1753
[30] Zhang W M, Meng G, Zhou J B, Chen J Y 2009 Sensors 9 3854
[31] Wu L, Bogy D B 2002 J. Tribol. -T. ASME 124 562
[32] Allen M P, Tildesley D J 1991 Computer Simulation of Liquids (Oxford:Oxford University Press) pp145-146
[33] Hook J R, Hall H E 1991 Solid State Physics (Chichester:Wiley) pp96-106
[34] Evans D J, Hoover W G 1986 Annu. Rev. Fluid Mech. 18 243
[35] Irving J H, Kirkwood J G 1950 J. Chem. Phys. 18 817
[36] Todd B D, Evans D J, Davis P J 1995 Phys. Rev. E 52 1627
[37] Fukui S, Shimada H, Yamane K, Matsuoka H 2005 Microsyst. Technol. 11 805
[38] Bahukudumbi P, Park J H, Beskok A 2003 Microscale Thermophy. Eng. 7 291
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