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Order-of-Magnitude Increase in Carbon Nanotube Yield Based on Modeling Transient Diffusion and Outgassing of Water From Reactor Walls.

Authors :
Tomaraei, Golnaz
Abdulhafez, Moataz
Bedewy, Mostafa
Source :
Journal of Manufacturing Science & Engineering. Apr2024, Vol. 146 Issue 4, p1-11. 11p.
Publication Year :
2024

Abstract

While reactor wall preconditioning was previously shown to influence the yield in chemical vapor deposition (CVD), especially for the growth of carbon nanotubes (CNTs), it was limited to studying accumulating carbonaceous deposits over a number of runs. However, the effects of temperature and duration as the reactor walls are exposed to hot humidity for extended periods between growth runs were not previously studied systematically. Here, we combine experimental measurements with a mathematical model to elucidate how the thermochemical history of reactor walls impacts growth yield, especially knowing that only a specific range of humidity promotes growth. Importantly, we demonstrate a one-order-of-magnitude higher CNT yield by increasing the interim, i.e., the time between runs. We explain the results based on previously unexplored process sensitivity to trace amounts of oxygen-containing species in the reactor. In particular, we model the effect of small amounts of water vapor being desorbed from reactor walls during growth. Our results reveal the outgassing dynamics and show the underlying mechanism of generating growth-promoting molecules. By installing a humidity sensor in our custom-designed multizone rapid thermal CVD reactor, we are able to uniquely correlate the amount of moisture within the reactor to real-time measurements of growth kinetics, as well as ex situ characterization of CNT alignment and atomic defects. Our findings enable a scientifically grounded approach toward both boosting growth yield and improving its consistency by reducing run-to-run variations. Accordingly, engineered dynamics recipes with added preprocessing steps can be envisioned to leverage this phenomenon for improving manufacturing process scalability and robustness. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10871357
Volume :
146
Issue :
4
Database :
Academic Search Index
Journal :
Journal of Manufacturing Science & Engineering
Publication Type :
Academic Journal
Accession number :
176792918
Full Text :
https://doi.org/10.1115/1.4063965