Automated Generation of Zigzag Carbon Nanotube Models Containing Haeckelite Defects

Abstract

AbstractCarbon nanotubes, CNTs, are a valuable material with applications in areas such as electronics, mechanics, optics and biomedicine, where they have great potential in the diagnosis and treatment of cancer, due to their ease of functionalization and their size that allows them traverse biological membranes and anchor on cancerous tumors. Regular CNTs have six-membered rings. According to their ordering or chirality, armchair, chiral and zigzag CNTs are known, with different properties. There are also CNTs that contain four-, five-, seven- and eight-membered rings called defects such as bumpy, haeckelite (Hk), and Stone- Wales (SW) defects. Defects modify the properties of CNTs. For example, zigzag CNTs with bumpy defects exhibit stronger interactions with the anticancer drug doxorubicin, DOX, than regular CNTs, facilitating drug transport to tumors. Designing defective CNTs as drug delivery systems would benefit from calculating DOX-CNT binding energies for CNTs of different chirality and with different defects placed at different positions, in an artificial intelligence approach. Such a systematic study requires the automated generation of defective CNTs. That is the goal of this work focusing now on zigzag CNTs with Hk defects. It starts from the step-by-step generation of the regular nanotube, leaving the positions where the defect will be inserted marked. Then a pair of carbon atoms is inserted and the corresponding bonds are completed, which ends with a quick optimization to visualize the nanotube structure. For this, a tcl script was developed with outputs compatible with many calculation methods and with possibilities of extension to other systems.KeywordsDefectsCarbon nanotubesGeneration software