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Ultralow Feeding Gas Flow Guiding Growth of Large-Scale Horizontally Aligned Single-Walled Carbon Nanotube Arrays
Abstract
On the basis of the rational analysis about the fluidic property of the system, an ultralow gas flow chemical vapor deposition (CVD) strategy was designed to prepare large-scale horizontally aligned ultralong single-walled carbon nanotube (SWNT) arrays. SWNT arrays could be well obtained under extremely low feeding flow of 1.5 sccm in a 1 in. quartz tube reactor. It was confirmed that the tubes grew floatingly and could cross microtrenches or climb over micro-obstacles in ultraslow gas flow. SWNTs arrays also could be formed no matter the substrate was placed vertically or upside down. The growth mechanism was discussed. Both the buoyancy effect induced by gas temperature/density difference and gas flow stability played dominant roles. More attractively, simultaneous batch-scale preparation of SWNT arrays was realized by the ultralow gas flow strategy. This new strategy turns to be more abstemious, efficient, promising, and flexible compared with the high gas flow rate fast-heating CVD processes.
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Cited by
Recent Progress on the Growth Mechanism of Carbon Nanotubes: A Review
Tessonnier, J., & Su, D. S. (2011) · ChemSusChem · doi:10.1002/cssc.201100175 · Cited by 431
Substrate‐Wide Confined Shear Alignment of Carbon Nanotubes for Thin Film Transistors
Jinkins, K. R., Chan, J., Jacobberger, R. M., Berson, A., & Arnold, M. S. (2019) · Advanced Electronic Materials · doi:10.1002/aelm.201800593 · Cited by 45
Metadata
- Authors
- Jin, Z., Chu, H., Wang, J., Hong, J., Tan, W., & Li, Y.
- Venue
- Nano Letters
- Publisher
- American Chemical Society (ACS)
- Published
- 2007-06-08
- Volume
- 7
- Issue
- 7
- Pages
- 2073-2079
- ISSN
- 1530-6984 (ISSN-L)
- 1530-6992
- OpenAlex
- W2127905811
- Cited by
- 222
- References
- 0
- FWCI
- 10.24
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
