Structural evolution dynamics in fusion of sumanenes and corannulenes: defects formation and self-healing mechanism. Issue 2 (26th March 2018)

• Record Type: Journal Article
• Authors: Sorkin, Anastassia; Su, Haibin
• Is Part Of: Nano futures. Volume 2:Issue 2(2018)
• Publication Date: 2018-03-26
• Subjects: sumanene -- corannulene -- graphene -- edges -- defects -- grain boundaries; Nanoscience -- Periodicals; 620.5
• DOI: 10.1088/2399-1984/aab423
• Languages: English
• ISSNs: 2399-1984

Abstract

Abstract: The fusion processes of structures consisting of various combinations between sumanene and corannulene, leading to the formation of graphene nanoribbons (GNRs) under heating are simulated by density-functional-based tight-binding molecular dynamics. Distinct stages are unraveled in the course of GNR formation. Firstly, the carbon fragments coalescence into highly strained framework. Secondly, structural reconstruction invokes breaking most strained bonds to form a GNR structure containing numerous defects. Lastly, defects are remedied by the delicate 'edge-facilitated self-healing' process through two synergized edge-related effects: elevated mobility of defects and promoted structure reconstructions owing to the remarkable dynamics associated with edges. Importantly, detailed dynamics in the course of forming GNRs with defects and grain boundaries simulated in this work is valuable to provide better understanding at the atomistic scale of defect formation as well as self-healing in the context of the sp 2 carbon network. In particular, edges play important roles in not only generating Stone–Wales (SW), 5-8-5 types of defects, 8-5-5-8 and pentagon–heptagon grain boundaries. In addition, our simulations predict the existence of one novel defect, coined as the Inverse SW defect, which is to be confirmed in future experimental studies. This study of dynamic structural evolution reveals that edges are prone to intrinsic and extrinsic modifications such as atomic-scale defects, structural distortions and inhomogeneity.