Formation of Amorphous Carbon Multi-Walled Nanotubes from Random Initial Configurations

Amorphous carbon nanotubes (a-CNT) with up to four walls and sizes ranging from 200 to 3200 atoms have been simulated, starting from initial random configurations and using the Gaussian Approximation Potential. The important variables (like density, height, and diameter) required to successfully simulate a-CNTs were predicted with the machine learning random forest technique. The width of the a-CNT models ranged between 0.55-2 nm with an average inter-wall spacing of 0.31 nm. The topological defects in a-CNTs were analyzed and new defect configurations were observed. The electronic density of states and localization in these phases were discussed and delocalized electrons in the pi subspace were identified as an important factor for inter-layer cohesion. Spatial projection of the electronic conductivity favors axial transport along connecting hexagons, while non-hexagonal parts of the network either hinder or bifurcate the electronic transport. A vibrational density of states was calculated and is potentially an experimentally comparable fingerprint of the material. The appearance of a low-frequency radial breathing mode was discussed and the thermal conductivity at 300 K was estimated using the Green-Kubo formula.

Automated summary

The important variables of amorphous carbon nanotubes (a-CNT) with up to four walls and sizes ranging from 200 to 3200 atoms were successfully predicted using machine learning random forest technique. The topological defects and electronic properties of these a-CNTs were analyzed. The vibrational density of states and thermal conductivity at 300 K were calculated.