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Artificial micro-scale or nano-scale machines that are capable of converting energy to mechanical work, have long been pursued by science and engineering communities for their potential applications in microfluidics, biology and medicine. From a physics point of view, they are also ideal models to investigate fundamental statistical phenomena in non-equilibrium active matters. Inspired by bio-machines and bio-motors like ATP synthase and flagellum motors, we propose a simple design of rotary motors based on pure self-diffusiophoresis effects. The basic design of the rotor consists of three colloidal beads with different surface properties, which leads to different interactions between the beads and solvent molecules. Chemical reactions are imposed on the surface of one of the beads, which creates a source of one of the two solvent molecules and generates a local concentration gradient. The other two beads connected to the catalytic bead have different affinities to the solvent molecules, which leads to asymmetric diffusiophoretic forces on the two non-catalytic beads. A net torque is thus obtained from difference of the diffusiophoretic forces between the two non-catalytic beads. In our simulation, we employ hybrid molecular dynamics (MD) simulations and multi-particle collision dynamics (MPC) to investigate the motion of microrotors. The binary fluid is composed with A-type and B-type solvent particle whose interactions are described by multi-particle collision dynamics while beads-particle interactions are modeled by molecular dynamics. In MPC, all fluid particles execute alternating streaming and collision steps. During streaming steps, the solvents move ballistically. During collision steps, particles are sorted into square cells and only interact with particles in the same cell under a specific stochastic rotation rule. MPC algorithm locally conserves mass, linear momentum, angular momentum and energy, and properly captures thermal fluctuation, mass diffusion, dissipation and hydrodynamic interactions. In our simulation, standard MPC parameters are employed which correspond to a liquid-like behavior of fluid. In MD, beads-solvent interactions are described by Lennard-Jones(LJ) potential with different parameter combinations and the equations of motion is integrated by velocity-Verlet algorithm. To perform hybrid molecular dynamic simulations with multi-particle collision dynamics, between two MPC collision steps, 50 MD steps are implemented for the solvent particles that are in the interaction range of colloidal beads. We first investigate the solvent concentration distribution around static microrotor, and confirm that the catalytic bead generates a steady-state local concentration gradient. Net angular displacements are obtained when the rotor is allowed to rotate freely. The rotational direction and speed of the micorotor are determined by bead-solvent interactions, the rotor geometry, the solvent viscosity and the catalytic reaction ratio. We also study the scenario in which two rotors are placed in close vicinity to each other. We find that the coupling between the concentration fields around the rotors reduces the rotational speed of both rotors.
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Keywords:
- self-diffusiophoretic microrotor /
- phoresis /
- molecular dynamic simulations /
- multi-particle collision dynamics
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[37] Grier D G 2003 Nature 424 810
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[1] Wang J 2013 Nanomachines: Fundamentals and Applications (Weinheim: John Wiley Sons) pp1-9
[2] Elgeti J, Winkler R G, Gompper G 2015 Rep. Prog. Phys. 78 056601
[3] Berg H C 2003 Annu. Rev. Biochem. 72 19
[4] Stock D, Leslie A G, Walker J E 1999 Science 286 1700
[5] Kay E R, Leigh D A, Zerbetto F 2007 Angew. Chem. Int. Ed. 46 72
[6] Sengupta S, Ibele M E, Sen A 2012 Angew. Chem. Int. Ed. 51 8434
[7] Purcell E M 1977 Am. J. Phys. 45 3
[8] Lauga E 2011 Soft Matter 7 3060
[9] Lauga E, Powers T R 2009 Rep. Prog. Phys. 72 096601
[10] Dey K K, Zhao X, Tansi B M, Mndez-Ortiz W J, Crdova-Figueroa U M, Golestanian R, Sen A 2015 Nano Lett. 15 8311
[11] Angelani L, Di Leonardo R, Ruocco G 2009 Phys. Rev. Lett. 102 048104
[12] Paxton W F, Kistler K C, Olmeda C C, Sen A, St. Angelo S K, Cao Y, Mallouk T E, Lammert P E, Crespi V H 2004 J. Am. Chem. Soc. 126 13424
[13] Schez S, Soler L, Katuri J 2015 Angew. Chem. Int. Ed. 54 1414
[14] Fournier-Bidoz S, Arsenault A C, Manners I, Ozin G A 2005 Chem. Commun. 4 441
[15] Catchmark J M, Subramanian S, Sen A 2005 Small 1 202
[16] He Y, Wu J, Zhao Y 2007 Nano Lett. 7 1369
[17] Qin L, Banholzer M J, Xu X, Huang L, Mirkin C A 2007 J. Am. Chem. Soc. 129 14870
[18] Fattah Z, Loget G, Lapeyre V, Garrigue P, Warakulwit C, Limtrakul J, Bouffier L, Kuhn A 2011 Electrochim. Acta 56 10562
[19] Wang Y, Fei S, Byun Y M, Lammert P E, Crespi V H, Sen A, Mallouk T E 2009 J. Am. Chem. Soc. 131 9926
[20] Ebbens S, Jones R A, Ryan A J, Golestanian R, Howse J R 2010 Phys. Rev. E 82 015304
[21] Anderson J L 1989 Annu. Rev. Fluid Mech. 21 61
[22] Yang M, Ripoll M, Chen K 2015 J. Chem. Phys. 142 054902
[23] Malevanets A, Kapral R 1999 J. Chem. Phys. 110 8605
[24] Yang M, Liu R, Ripoll M, Chen K 2015 Lab. Chip. 15 3912
[25] Padding J, Louis A 2006 Phys. Rev. E 74 031402
[26] Winkler R, Mussawisade K, Ripoll M, Gompper G 2004 J. Phys. Condens. Matter 16 S3941
[27] Peltomki M, Gompper G 2013 Soft Matter 9 8346
[28] Noguchi H, Gompper G 2004 Phys. Rev. Lett. 93 258102
[29] Gompper G, Ihle T, Kroll D, Winkler R 2009 Multi-particle Collision Dynamics: a Particle-based Mesoscale Simulation Approach to the Hydrodynamics of Complex Fluids (Berlin: Springer) pp1-87
[30] Ryder J F 2005 Ph. D. Dissertation (Oxford: University of Oxford)
[31] Yang M, Ripoll M 2014 Soft Matter 10 1006
[32] Yang M, Wysocki A, Ripoll M 2014 Soft Matter 10 6208
[33] Rckner G, Kapral R 2007 Phys. Rev. Lett. 98 150603
[34] Tao Y G, Kapral R 2010 Soft Matter 6 756
[35] Huang M J, Schofield J, Kapral R 2016 Soft Matter 12 5581
[36] Friese M, Rubinsztein-Dunlop H, Gold J, Hagberg P, Hanstorp D 2001 Appl. Phys. Lett. 78 547
[37] Grier D G 2003 Nature 424 810
[38] Rapaport D C 2004 The Art of Molecular Dynamics Simulation (Cambridge: Cambridge University Press) pp60-62
[39] Tzel E, Ihle T, Kroll D M 2006 Phys. Rev. E 74 056702
[40] Bricard A, Caussin J B, Desreumaux N, Dauchot O, Bartolo D 2013 Nature 503 95
[41] Nguyen N H, Klotsa D, Engel M, Glotzer S C 2014 Phys. Rev. Lett. 112 075701
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