Optimized CVD Production of CNT-Based Nanohybrids by Taguchi Robust Design
Taguchi's robust design method is for the first time employed to optimize many aspects of the production of nanohybrids based on C nanotubes by iron-catalyzed chemical vapor deposition in i-C4H10 + H2 atmosphere. By analyzing the outcomes of the catalytic process in terms of selectivity, carbon yield, purity and crystalline arrangement of the hybrid-forming nanotubes, the influence is ranked of the following parameters: synthesis temperature (500–700 °C), support material (alumina, magnesia or sodium-exchanged montmorillonite), calcination- (450–750 °C) and reduction-(500–700 °C) temperatures of the 15 wt% Fe-catalyst. In the experiments initially performed for this purpose, the growth process had, on average, scarce selectivity (2 in a scale 1-5) and poor yield (130 wt%); carbonaceous deposits exhibited unsatisfactory graphitization degree (Raman D/G intensity ratio > 1.5) and contained large amounts of metal impurities (14 wt%) and amorphous carbon (5 wt%). The indications emerging from Taguchi approach to the process optimization are critically examined. The experimental conditions chosen for carrying out test experiments allow achieving excellent selectivity (5) or large yield (760 wt%), hybrids with well-graphitized nanotubes (D/G intensity ratio < 0.6), nearly free of metallic (0.3 wt%) or amorphous (0.4 wt%) inclusions, with consequent possibility of satisfying the different requisites that the specific application to be addressed may require.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
Document Type: Research Article
Publication date: 01 March 2012
More about this publication?
- Journal for Nanoscience and Nanotechnology (JNN) is an international and multidisciplinary peer-reviewed journal with a wide-ranging coverage, consolidating research activities in all areas of nanoscience and nanotechnology into a single and unique reference source. JNN is the first cross-disciplinary journal to publish original full research articles, rapid communications of important new scientific and technological findings, timely state-of-the-art reviews with author's photo and short biography, and current research news encompassing the fundamental and applied research in all disciplines of science, engineering and medicine.
- Editorial Board
- Information for Authors
- Subscribe to this Title
- Terms & Conditions
- Ingenta Connect is not responsible for the content or availability of external websites