Polymorphic crystals selected in the nucleation stage
1 School of Mathematics and Physics, University of Science and Technology Beijing - Beijing 100083, China
2 Institute of Nuclear Physics and Chemistry, China Academy of Engineering Physics - Mianyang 621900, China
Received: 22 April 2014
Accepted: 28 July 2014
Molecular dynamics simulations are used to explore the atomic mechanism of formation of polymorphic crystals. Cooling the Lennard-Jones systems, we observe that the system almost always evolves into a polymorphic crystal with either fivefold-symmetric stacking faults or single-direction stacking faults. The detailed analysis reveals that such an evolution depends on the configuration of fcc/hcp concomitance in the nucleation stage. A defect-induced model is then introduced to illustrate these two evolution routes. Through calculating the formation energies of the defective critical nuclei, we find that the polymorphic crystals seem to be determined by their critical nuclei, in which the relatively lower formation energy ensures the preponderance of the fivefold-symmetric cluster. Before the nucleation, we observe that thermal fluctuations prefer hcp-like particles over fcc-like ones while in the nucleation and growth stage this preference reverses. Notably, an extended step rule of Ostwald is seemingly suitable to characterise the growth process because of the temporary hcp layers appearing among fcc layers in the growth stage. Although the crystalline cluster with single-direction stacking faults has higher growth rate and structural order than its competitor, the component (fcc and hcp) proportion of the final crystals is almost always constant regardless of the polymorphic type. Our finding renews the understanding of the polymorphism of crystals, and possibly draws more attention of people intending to control the polymorphic structures through nucleation.
PACS: 64.70.D- – Solid-liquid transitions / 83.10.Rs – Computer simulation of molecular and particle dynamics / 61.72.J- – Point defects and defect clusters
© EPLA, 2014