Simulation on the Dynamic Process of Formation of Particle Cluster by Generalized Exponential Model†

doi:10.7503/cjcu20180323

Abstract

Abstract:

The generalized exponential model was used to describe the interaction between soft colloidal particles. The dynamic process of structure formation and transformation was investigated by molecular dynamics simulations. The characteristics of the structural transformation and the influence of thermodynamicpath on the final formed structure of cluster crystal were studied for two thermodynamic paths, isothermal compression and equidensity cooling, respectively. Compared with Monte Carlo simulation results, the structure transitionin molecular dynamics simulation has obvious hysteresis on changing density, which is due to a high free energy barrier between fcc2 and fcc3 structures. In addition, the phase structure under the same temperature and pressure is not exactly same through different thermodynamic paths.It is concluded that the dynamic formation process has a great influence on phase structure.

Key words: Soft particle cluster crystal, Molecular dynamics simulation, Generalized exponential model function, Face-centered cubic, Body-centered cubic

CLC Number:

O631

TrendMD:

MA Lan,RONG Jingjing,ZHU Youliang,HUANG Yineng,SUN Zhaoyan. Simulation on the Dynamic Process of Formation of Particle Cluster by Generalized Exponential Model^†[J]. Chem. J. Chinese Universities, 2019, 40(1): 195.

Figures/Tables 8

Fig.1 Thermodynamic processpaths of isothermal compression and equidensity cooling on GEM4 phase diagram

Fig.2 Simulation snapshot of fcc2 of GEM-4 system at ρ=1

Fig.3 Cluster size(A) and Q4(a) and Q6(b)(B) vs. densitiesInset of (A): a-CAN analysis by OVITO.

Fig.4 Snapshots at different densities(A) ρ=0.2; (B) ρ=0.4; (C) ρ=1.1; (D) ρ=1.5.

Fig.5 Cluster size(A) and Q4(a) and Q6(b)(B) vs. densitiesInset of (A): a-CAN analysis by OVITO.

Fig.6 Cluster size(A) and Q4(a) and Q6(b)(B) vs. temperaturesInset of (A): a-CAN analysis by OVITO.

Fig.7 Snapshots at different temperatures(A) T=0.9; (B) T=0.09; (C) T=0.06; (D) T=0.01.

Fig.8 Cluster size(A) and Q4(a) and Q6(b)(B) vs. temperaturesInset of (A): is a-CAN analysis by OVITO.

References 31

[1]	Young D. A., Alder B. J., J. Chem. Phys.,1979, 70(1), 473—481
[2]	Coslovich D., Strauss L., Kahl G., Soft　Matter,2011, 7(5), 2127—2137
[3]	Lascaris E., Malescio G., Buldyrev S. V., Stanley H. E., Phys. Rev.　E,2010, 81(3), 031201
[4]	Likos C. N., Lang A., Watzlawek M., Löwen H., Phys. Rev.　E,2001, 63(3), 031206
[5]	Miller W. L., Cacciuto A., Soft　Matter,2011, 7(16), 7552—7559
[6]	Moreno A. J., Likos C. N., Phys. Rev.　Lett.,2007, 99(10), 107801
[7]	Zhang K., Charbonneau P., Mladek B. M., Phys. Rev.　Lett.,2010, 105(24), 245701
[8]	Klein W., Gould H., Ramos R. A., Clejan I., Mel'cuk A. I., Physica　A,1994, 205(4), 738—746
[9]	Bernabei M., Bacova P., Moreno A. J., Narros A., Likos C. N., Soft　Matter,2013, 9(4), 1287—1300
[10]	Lenz D. A., Blaak R., Likos C. N., Mladek B. M., Phys. Rev.　Lett.,2012, 109(22), 228301
[11]	Sciortino F., Zaccarelli E., Nature2013, 493(7430), 30—31
[12]	Ikeda A., Miyazaki K., Phys. Rev.Lett.,2011, 106(1), 015701
[13]	Lang A., Likos C. N., Watzlawek M., Löwen H., J. Phys.: Condens.　Matter,2000, 12(24), 5087—5108
[14]	Likos C. N., Soft　Matter, 2006, 2(6), 478—498
[15]	Malescio G., J. Phys.: Condens. Matter, 2007, 19(7), 073101
[16]	Prestipino S., Saija F., Giaquinta P. V., Phys. Rev. E,2005, 71(5), 050102
[17]	Slimani M. Z., Bacova P., Bernabei M., Narros A., Likos C. N., Moreno A. J., ACS Macro. Lett.,2014, 3(7), 611—616
[18]	Bianca M. M., Patrick C., Christos N. L., Daan F., Gerhard K., J. Phys.: Condens. Matter,2008, 20(49), 494245
[19]	Likos C. N., Mladek B. M., Gottwald D., Kahl G., J. Chem. Phys.,2007, 126(22), 224502
[20]	Miyazaki R., Kawasaki T., Miyazaki K., Phys. Rev.　Lett.,2016, 117(16), 165701
[21]	Mladek B. M., Charbonneau P., Frenkel D., Phys. Rev. Lett.,2007, 99(23), 235702
[22]	Mladek B. M., Gottwald D., Kahl G., Neumann M., Likos C. N., Phys. Rev.　Lett.,2006, 96(4), 045701
[23]	Allen M.P., Tildesley D. J., J. Computer Simulation of Liquids, Oxford University Press, Oxford, 1987
[24]	Frenkel D., Smit B., Understanding Molecular Simulation: from Algorithms to Applications, Academic Press, San Diego, 2002
[25]	Zhu Y. L., Liu H., Li Z. W., Qian H. J., Milano G., Lu Z. Y., J. Comput. Chem.,2013, 34(25), 2197—2211
[26]	Alexander S., Modell. Simul. Mater. Sci. Eng., 2012, 20(4), 045021
[27]	Lechner W., Dellago C., J. Chem. Phys.,2008, 129(11), 114707
[28]	Pàmies J. C., Cacciuto A., Frenkel D., J. Chem. Phys.,2009, 131(15), 159903
[29]	Stillinger F. H., J. Chem. Phys., 1976, 65(10), 3968—3974
[30]	Tim N., Christos N. L., J. Phys.: Condens. Matter,2011, 23(23), 234112
[31]	Marta M. S., Arash N., Gerhard K., J. Phys.: Condens. Matter,2013, 25(19), 195101