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采用分子动力学模拟方法研究了气体分子Ar在光滑和粗糙Pt表面上的散射规律.提出了一种速度抽样方法，计算了不同温度条件下气体分子对光滑和粗糙表面的切向动量适应系数和吸附概率.结果显示：光滑表面条件下，气体分子的切向动量系数和吸附概率都随着温度的升高而降低；粗糙度对气体分子切向动量与表面的适应具有极大的促进作用，当粗糙度足够大时，切向动量适应系数的大小趋近于1.0，对温度的敏感性也逐渐降低.采用粒子束方法对气体分子在光滑和粗糙表面上的散射规律进行了定量分析.总结了散射过程中气体分子的典型轨迹和动量变化规律，将气体分子在光滑表面的散射分为两种类型：单次碰撞后散射和多次碰撞后散射.单次碰撞后散射的气体分子平均切向动量有所减小，而经过多次碰撞后散射的气体分子则倾向于保持原有的平均切向动量.对于粗糙表面，粗糙度的存在使气体分子与表面间的动量和能量适应更加充分，导致气体分子在较粗糙表面上散射后的平均切向动量大幅减小并接近于0，且气体分子在表面上经历的碰撞次数越多，其散射后的能量损失越严重.Molecular dynamics method is used to investigate the scattering characteristics of Ar molecule on smooth and rough Pt(100) surface. In this paper, a velocity sampling method is proposed to obtain the tangential momentum accommodation coefficients (TMACs) and the sticking probabilities of gas molecules on smooth and rough surface under different temperature conditions. The results show that the TMAC and the sticking probability decrease with increasing temperature under smooth surface condition. The results of our work are in excellent agreement with the results of the reference for a three-dimensional gas flow in a nanochannel. Unlike the scenario of smooth surfaces, the roughness of rough surfaces greatly promotes the accommodation of tangential momentum between the gas molecules and surfaces. When the roughness becoming larger, the TMAC approaches to 1.0 and the sensitivity to temperature decreases gradually. Unlike the relationship between TMAC and roughness, although the sticking probability of gas molecules increases with roughness increasing, its dependence on temperature does not change. Furthermore, the beam method where the incident velocity and angle are determined is used to quantitatively analyze the scattering characteristics of gas molecules on different surfaces. According to the number of collisions between gas molecule and the surface, we classify the scattering of gas molecules on a smooth surface into two types: single collision scattering and multiple collision scattering. For those gas molecules that experience one collision, their average tangential momentum decreases to a certain extent, however, the gas molecules scattered after multiple collisions tend to maintain the original tangential momentum. For gas molecules reflected from the smooth surface, their velocity distribution exhibits a typical bimodal distribution. The position of the first peak appears at the incident velocity value, and the position of the second peak appears at a velocity value of zero. Regarding rough surfaces, the existence of roughness changes the mode of exchange of momentum and energy between gas molecules and walls, resulting in a significant decrease in the average tangential momentum of gas molecules scattered on rough surfaces. Besides, the more the gas molecules colliding on the surface, the more severe the energy loss after scattering will be. For gas molecules reflected from the rough surfaces, their velocity distribution conforms to the characteristics of Gaussian distribution.
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Keywords:
- gas-surface interaction /
- surface roughness effects /
- sticking probability /
- tangential momentum accommodation coefficient
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[16] Beskok A, Karniadakis G E 1999 Microscale Thermophys. Eng. 3 43
[17] Zhang W M, Meng G, Wei X Y 2012 Microfluid Nanofluid 13 845
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[25] Spijker P, Markvoort A J, Nedea S V, Hilbers P A J 2010 Phys. Rev. E 81 011203
[26] Sun J, Li Z X 2008 Mol. Phys. 106 2325
[27] Sun J, Li Z X 2010 Comput. Fluids 39 1645
[28] Sun J, Li Z X 2011 Heat Transfer Eng. 32 658
[29] Barisik M, Beskok A 2011 Microfluid Nanofluid 11 269
[30] Barisik M, Beskok A 2012 Microfluid Nanofluid 13 789
[31] Chirita V, Pailthorpe B A, Collins R E 1993 Appl. Phys. 26 133
[32] Chirita V, Pailthorpe B A, Collins R E 1997 Nucl. Instrum. Meth. B 4 12
[33] Finger G W, Kapat J S, Bhattacharya A 2007 J. Fluids Eng. 129 31
[34] Pham T T, To Q D, Lauriat G, Leonard C 2012 Phys. Rev. E 86 051201
[35] Reinhold J, Veltzke T, Wells B, Schneider J, Meierhofer F, Colombi Ciacchi L, Chaffee A 2014 Comput. Fluids 97 31
[36] Kuscer I 1974 Proceeding of the Ninth International Symposium Goettengen, Germany, July 15-20, 1974 p21
[37] Maruyama S 2000 Advances in Numerical Heat Transfer (Vol.2) (Boca Raton: CRC Press) pp189
[38] Rapaport D C 2004 The Art of Molecular Dynamics Simulation (New York: Cambridge University Press) pp4-5
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[1] Karniadakis G, Beskok A, Aluru N 2005 Micro Flows and Nano Flows: Fundamentals and Simulation(New York: Springer) pp2-8
[2] Verbridge S S, Craighead H G, Parpia J M 2008 Appl. Phys. Lett. 92 013112
[3] Padilla J F, Boyd I D 2009 J. Thermo. Phys. Heat Tr. 23 96
[4] Rovenskaya O I 2015 Int. J. Heat Mass Trans. 89 1024
[5] Hadj Nacer M, Graur I, Perrier P, Molans J G, Wuest M 2014 J. Vac. Sci. Technol. A 32 021621
[6] Shen Q 2003 Rarefied Gas Dynamics (Beijing: National Defense Industry Press) p121 (in Chinese) [沈青 2003 稀薄气体动力学(北京: 国防工业出版社) 第121页]
[7] Hurlbut F C 1997 Adv. Mech. 27 549 (in Chinese) [Hurlbut F C 1997 力学进展 27 549]
[8] Maxwell J C 1879 Phil. Trans. R. Soc. Lond. 170 231
[9] Ohwada T, Sone Y, Aoki K 1989 Phys. Fluids A 1 1588
[10] Lockerby D A, Reese J M, Emerson D R, Barber R W 2004 Phys. Rev. E 70 017303
[11] Pan L S, Liu G R, Lam K Y 1999 J. Micromech. Microeng. 9 89
[12] Wu L, Bogy D B 2003 Trans. ASME J. Tribol. 125 558
[13] Lockerby D A, Reese J M 2008 J. Fluid. Mech. 604 235
[14] Li Q, He Y L, Tang G H, Tao W Q 2011 Microfluid Nanofluid 10 607
[15] Weng C I, Li W L, Hwang C C 1999 Nanotechnology 10 373
[16] Beskok A, Karniadakis G E 1999 Microscale Thermophys. Eng. 3 43
[17] Zhang W M, Meng G, Wei X Y 2012 Microfluid Nanofluid 13 845
[18] Cao B Y, Sun J, Chen M, Guo Z Y 2009 Int. J. Mol. Sci. 10 4638
[19] Markvoort A J, Hilbers P A J, Nedea S V 2005 Phys. Rev. E 71 066702
[20] Arya G, Chang H C, Maginn E J 2003 Mol. Simul. 29 697
[21] Yamamoto K 2002 JSME Int. J. Ser. B 45 788
[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 物理学报 55 5305]
[24] Cao B Y, Chen M, Guo Z Y 2006 Int. J. Eng. Sci. 44 927
[25] Spijker P, Markvoort A J, Nedea S V, Hilbers P A J 2010 Phys. Rev. E 81 011203
[26] Sun J, Li Z X 2008 Mol. Phys. 106 2325
[27] Sun J, Li Z X 2010 Comput. Fluids 39 1645
[28] Sun J, Li Z X 2011 Heat Transfer Eng. 32 658
[29] Barisik M, Beskok A 2011 Microfluid Nanofluid 11 269
[30] Barisik M, Beskok A 2012 Microfluid Nanofluid 13 789
[31] Chirita V, Pailthorpe B A, Collins R E 1993 Appl. Phys. 26 133
[32] Chirita V, Pailthorpe B A, Collins R E 1997 Nucl. Instrum. Meth. B 4 12
[33] Finger G W, Kapat J S, Bhattacharya A 2007 J. Fluids Eng. 129 31
[34] Pham T T, To Q D, Lauriat G, Leonard C 2012 Phys. Rev. E 86 051201
[35] Reinhold J, Veltzke T, Wells B, Schneider J, Meierhofer F, Colombi Ciacchi L, Chaffee A 2014 Comput. Fluids 97 31
[36] Kuscer I 1974 Proceeding of the Ninth International Symposium Goettengen, Germany, July 15-20, 1974 p21
[37] Maruyama S 2000 Advances in Numerical Heat Transfer (Vol.2) (Boca Raton: CRC Press) pp189
[38] Rapaport D C 2004 The Art of Molecular Dynamics Simulation (New York: Cambridge University Press) pp4-5
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