CVD growth of carbon nanostructures from zirconia: mechanisms and a method for enhancing yield.

By excluding metals from synthesis, growth of carbon nanostructures via unreduced oxide nanoparticle catalysts offers wide technological potential. We report new observations of the mechanisms underlying chemical vapor deposition (CVD) growth of fibrous carbon nanostructures from zirconia nanoparticles. Transmission electron microscope (TEM) observation reveals distinct differences in morphological features of carbon nanotubes and nanofibers (CNTs and CNFs) grown from zirconia nanoparticle catalysts versus typical oxide-supported metal nanoparticle catalysts. Nanofibers borne from zirconia lack an observable graphitic cage consistently found with nanotube-bearing metal nanoparticle catalysts. We observe two distinct growth modalities for zirconia: (1) turbostratic CNTs 2-3 times smaller in diameter than the nanoparticle localized at a nanoparticle corner, and (2) nonhollow CNFs with approximately the same diameter as the nanoparticle. Unlike metal nanoparticle catalysts, zirconia-based growth should proceed via surface-bound kinetics, and we propose a growth model where initiation occurs at nanoparticle corners. Utilizing these mechanistic insights, we further demonstrate that preannealing of zirconia nanoparticles with a solid-state amorphous carbon substrate enhances growth yield.This material is based upon work supported by the National Science Foundation under Grant No. 1007793 and was also supported by Airbus group, Boeing, Embraer, Lockheed Martin, Saab AB, Hexcel, and TohoTenax through MIT’s Nano- Engineered Composite aerospace STructures (NECST) Consortium. This research was supported (in part) by the U.S. Army Research Office under Contract W911NF-13-D-0001. This work was performed in part at the Center for Nanoscale Systems (CNS), a member of the National Nanotechnology Infrastructure Network (NNIN), which is supported by the National Science Foundation under NSF Award No. ECS-0335765. CNS is part of Harvard University. This work was carried out in part through the use of MIT Microsystems Technology Laboratories. Stephan Hofmann acknowledges funding from EPSRC under grant EP/H047565/1. Piran Kidambi acknowledges the Lindemann Trust Fellowship.This is the final published version. It first appeared at http://pubs.acs.org/doi/abs/10.1021/ja509872y