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Liquid gallium and its alloy with low melting point, low toxic and high electrical conductivity are used extensively in burgeoning microfluidic and flexible electronic devices. The key to producing these devices is to effectively control the wettability and morphology of liquid metal on the solid interface in different manufacturing processes. Based on the Lennard-Jones (L-J) potential describing the solid-liquid interaction, the wettabilities of liquid gallium film on the smooth and rough graphene surfaces are effectively investigated by molecular dynamics simulation which is an available and powerful option in this field. Different regimes of wetting are discovered by changing the depth of the L-J potential, and the stable contact angle increases with Ga-C potential depth decreases. The results show that the equilibrium contact angle and the retraction velocity increase with the decrease of the L-J potential between the gallium and graphene, showing that some properties change from complete wetting to hydrophilic and to hydrophobic. The L-J potential depth obtained from the simulation results can be effectively employed to describe the interaction between the liquid gallium and the substrate because the resulting wetting angle is extremely close to the experimental value. When employing the most appropriate L-J potential, it is found that although the initial retraction velocity increases with the proportional decrease of the thickness of the liquid Ga film, there are a few of differences in equilibrium contact angle and final retraction velocity in virtue of the competition between the surface tension of the Ga film and Ga-C interaction. It means that for the wetting state the film thickness is not the crux for changing the equilibrium contact angle and retraction velocity based on a similar conversion of potential energy into kinetic energy. Finally, we investigate the effects of the L-J potential on three rough surfaces which are patterned into three types of nanopillars with different top morphologies respectively. Specifically, it is shown that in spite of similar surface roughness, the wetting morphologies of liquid gallium deposited on various nano-textured graphene surfaces range from hydrophobic to dewetting state, suggesting that not only the roughness but also the morphology of surface can exert an available influence on the wettability of liquid. The wetting transition between the wetting and dewetting state can be achieved dynamically by adjusting the morphologies of nanopillars involved although we still need to go into more detail on the configurable way to fulfill the changing requirements.
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Keywords:
- molecular dynamics simulation /
- liquid gallium /
- graphene /
- Lennard-Jones potential
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[12] Gozen B A, Tabatabai A, Ozdoganlar O B, Majidi C 2014 Adv. Mater. 26 5211
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[14] So J H, Thelen J, Qusba A, Hayes G J, Lazzi G, Dickey M D 2009 Adv. Funct. Mater. 19 3632
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[17] Fuentes-Cabrera M, Rhodes B H, Fowlkes J D, López-Benzanilla A, Terrones H, Simpson M L, Rack P D 2011 Phys. Rev. E 83 041603
[18] Plimpton S 1995 J. Comput. Phys. 7 1
[19] Baskes M I, Chen S P, Cherne F J 2002 Phys. Rev. B 66 104107
[20] Lee T, Taylor C D, Lawson A C, Conradson S D, Chen S P, Caro A, Valone S M, Baskes M I 2014 Phys. Rev. B 89 174114
[21] Ren W 2014 Langmuir 30 2879
[22] de Coninck J, Blake T D 2008 Annu. Rev. Mater. Res. 38 1
[23] Blake T D, Clarke A J, de Coninck J, de Ruijter M J, Belgium M 1997 Langmuir 13 2164
[24] Bertrand E, Blake T D, de Coninck J 2009 Eur. Phys. J.: Spec. Top. 166 173
[25] Li K, He H Y, Xu B, Pan B C 2009 J. Appl. Phys. 105 054308
[26] NaidichJu J V, Chuvashov N 1983 J. Mater. Sci. 18 2071
[27] Stukowski A 2009 Model. Simul. Mater. Sci. Eng. 18 15012
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[1] Worthington A M 1876 Proc. R. Soc. 25 261
[2] Josserand C, Thoroddsen S T 2016 Annu. Rev. Fluid Mech. 48 365
[3] Nishimoto S, Bhushan B 2013 RSC Adv. 3 671
[4] Höcker H 2002 Pure Appl. Chem. 74 423
[5] Boreyko J B, Chen C H 2009 Phys. Rev. Lett. 103 184501
[6] Chu K H, Joung Y S, Enright R, Buie C R, Wang E N 2013 Appl. Phys. Lett. 102 151602
[7] Choi C H, Kim C J 2006 Phys. Rev. Lett. 96 066001
[8] Geim A K, Novoselov K S 2007 Nature Mater. 6 183
[9] Hu L, Wang L, Ding Y, Zhan S, Liu J 2016 Adv. Mater. 28 9210
[10] Ordonez R C, Yashi C K H, Torres C M, Hafner N, Adleman J R, Acosta N M, Melcher J, Kamin N M, Garmire D 2016 IEEE Trans. Electron Devices 63 4018
[11] Secor E B, Ahn B Y, Gao T Z, Lewis J A, Hersam M C 2015 Adv. Mater. 27 6683
[12] Gozen B A, Tabatabai A, Ozdoganlar O B, Majidi C 2014 Adv. Mater. 26 5211
[13] Dickey M D 2014 ACS Appl. Mater. Interfaces 6 18369
[14] So J H, Thelen J, Qusba A, Hayes G J, Lazzi G, Dickey M D 2009 Adv. Funct. Mater. 19 3632
[15] Paik J K, Kramer R K, Wood R J 2011 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS2011) San Francisco, CA, USA, 25-30 September, 2011 p414
[16] Zhang J, Yao Y Y, Sheng L, Liu J 2015 Adv. Mater. 27 2648
[17] Fuentes-Cabrera M, Rhodes B H, Fowlkes J D, López-Benzanilla A, Terrones H, Simpson M L, Rack P D 2011 Phys. Rev. E 83 041603
[18] Plimpton S 1995 J. Comput. Phys. 7 1
[19] Baskes M I, Chen S P, Cherne F J 2002 Phys. Rev. B 66 104107
[20] Lee T, Taylor C D, Lawson A C, Conradson S D, Chen S P, Caro A, Valone S M, Baskes M I 2014 Phys. Rev. B 89 174114
[21] Ren W 2014 Langmuir 30 2879
[22] de Coninck J, Blake T D 2008 Annu. Rev. Mater. Res. 38 1
[23] Blake T D, Clarke A J, de Coninck J, de Ruijter M J, Belgium M 1997 Langmuir 13 2164
[24] Bertrand E, Blake T D, de Coninck J 2009 Eur. Phys. J.: Spec. Top. 166 173
[25] Li K, He H Y, Xu B, Pan B C 2009 J. Appl. Phys. 105 054308
[26] NaidichJu J V, Chuvashov N 1983 J. Mater. Sci. 18 2071
[27] Stukowski A 2009 Model. Simul. Mater. Sci. Eng. 18 15012
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