Advisor(s)

Sagar Kamarthi

Contributor(s)

Abe Zeid, Yung Joon Jung

Date of Award

2011

Date Accepted

12-2011

Degree Grantor

Northeastern University

Degree Level

Ph.D.

Degree Name

Doctor of Philosophy

Department or Academic Unit

College of Engineering, Department of Mechanical and Industrial Engineering

Keywords

industrial engineering, artificial intelligence, nanotechnology, artificial neural network, carbon nanotube, chemical vapor deposition, design of experiment, vertically aligned

Disciplines

Engineering | Industrial Engineering | Mechanical Engineering

Abstract

Science and engineering communities have given the synthesis of vertically aligned single walled carbon nanotubes (VA-SWNTs) considerable attention due to their attractive physical properties, unique morphology, and better potential for building advanced devices than those with asymmetric and entwined carbon nanotubes (CNTs). Chemical vapor deposition (CVD) is one of several viable methods for growing VA-SWNTs, which is well known for its economic viability and good yield of VA-SWNTs. Utilizing Co catalyst (0.5 ~ 1 nm thick) supported on an Al/SiO2 multilayer substrate and a hydrocarbon feedstock, VA-SWNTs are grown in excess of a millimeter height.

To control the CVD process to selectively produce tall VA-SWNTs, one has to use the right combination of process inputs such as gas flow rate, chamber temperature, and chamber pressure. This dissertation investigates their main effects and interactions on VA-SWNT yield and length by conducting design of experiments and analysis on the metamodel of the CVD process. The artificial neural network (ANN) based metamodel was constructed using the experimental data.

The interactions among control variables and response surface plots show that pressure and temperature are the most significant CVD process control variables to selectively produce VA-SWNTs. In addition, the analysis confirms that higher temperature and higher pressure will result in a better yield of VA-SWNTs. In contrast, the analysis points out that the flow rate and the pressure are the most statistically significant factors that influence the length of VA-SWNTs. The response surface graphs indicate that higher flow with lower pressure will consistently yield tall VA-SWNTs. We found that gas flow rate is the most significant of the control variables and only the optimum value of the gas flow rate can ensure the growth of tall VA-SWNTs. We also found that the interaction of gas flow rate with chamber temperature and pressure is extremely important to ensure the quality of VA-SWNTs. This observation indicates that dynamic pressure of the fluid in the chamber affects the quality of VA-SWNTs grown on the substrate. We have also found out that flow rate less than 150 sccm and a growth time of 20 minutes are suitable for the repeatability of medium length VA-SWNTs. Outcomes of this investigation are beneficial for moving the CVD process closer to producing VA-SWNTs on large mass-produced scale.

Document Type

Dissertation

Rights Information

copyright 2011

Rights Holder

Hatem Mansour Abuhimd



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