Empirical modeling of micromechanical bending process of vertically aligned carbon nanotube forest using response surface methodology
Micromechanical bending (M2B) is a newly developed micro patterning technique applied for vertically aligned carbon nanotubes (VACNTs) array, commonly known as CNT forest. This process is required to realize the various use of CNT forest in Micro-Electromechanical Systems (MEMS). There are variou...
Main Authors: | , , , |
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Format: | Article |
Language: | English English English |
Published: |
Taylor & Francis
2017
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Subjects: | |
Online Access: | http://irep.iium.edu.my/57542/ http://irep.iium.edu.my/57542/ http://irep.iium.edu.my/57542/ http://irep.iium.edu.my/57542/1/Published%20Version.pdf http://irep.iium.edu.my/57542/7/57542-Empirical%20modeling%20of%20micromechanical%20bending%20process_SCOPUS.pdf http://irep.iium.edu.my/57542/13/57542_Empirical%20modeling%20of%20micromechanical%20bending_WOS.pdf |
Summary: | Micromechanical bending (M2B) is a newly developed micro patterning
technique applied for vertically aligned carbon nanotubes (VACNTs) array, commonly
known as CNT forest. This process is required to realize the various use of CNT forest
in Micro-Electromechanical Systems (MEMS). There are various parameters involved
in M2B process that controls the surface roughness of the processed structure of
the CNT forest. However, there is no mathematical model available, yet that could
predict the influence of these parameters on the surface roughness of the patterned
CNT forest. In this paper, an empirical approach has been used to predict the
surface roughness for the micromechanical bending (M2B) processed CNT forest. At
first, several experiments were conducted by varying different process parameters
such as tool rotational speed, lateral speed and a step size of the bend. Best optimized
process parameters were identified at 2,000 rpm tool rotational speed, 1 mm/
min lateral speed and 1 μm step size that produced a minimum surface roughness
of Ra = 15 nm. Finally, a response surface methodology (RSM) based mathematical
model was developed and validated with reasonable accuracy to understand the
impact of different parameters on the M2B process. |
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