TY - JOUR
T1 - Vertically Aligned Carbon Nanotubes Capacitive Sensors
AU - Reddy, Siva K.
AU - Gendelis, Itay
AU - Ya'Akobovitz, Assaf
N1 - Funding Information:
Manuscript received November 20, 2018; revised February 7, 2019; accepted February 9, 2019. Date of publication February 13, 2019; date of current version May 16, 2019. This work was supported by the Israeli Ministry of Science and Technology under Grant 53253. The associate editor coordinating the review of this paper and approving it for publication was Prof. Bhaskar Choubey. (Corresponding author: Assaf Ya’akobovitz.) The authors are with the Department of Mechanical Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel (e-mail: assafyaa@bgu.ac.il). Digital Object Identifier 10.1109/JSEN.2019.2899060
Publisher Copyright:
© 2001-2012 IEEE.
PY - 2019/6/15
Y1 - 2019/6/15
N2 - Capacitive sensors are key components in a wide range of sensing applications, such as gas detectors and safety systems. While the mainstream silicon sensors demonstrated good performances, vertically aligned carbon nanotubes (VA-CNTs) outperform them and, therefore, are an attractive candidate material for capacitive applications owing to their extremely high surface area. Specifically, their top (crust) layer is characterized by a porous and dense morphology that further enhances the capacitive area and, consequently, induces an electrostatic fringe field and an enhancement of the capacitance. In this paper, we study how the porosity of VA-CNTs determines their electrostatic behavior. We observed that the porous surface of the crust layer generates a significant enhancement of the capacitance comparing to parallel plate capacitors. The rough surface of the crust layer results in amplification of the VA-CNT effective capacitor area, which further increases with the electrostatic gap. As-grown VA-CNTs with lower porosity demonstrate higher capacitance; however, densified samples and samples reinforced with conductive nano-particles did not show an enhancement of the capacitance, due to a significant change in their CNT formation. Thus, this paper emphasizes the influence of the morphological structure of VA-CNTs on their capacitance and enriches the material library that can be used for capacitive sensing.
AB - Capacitive sensors are key components in a wide range of sensing applications, such as gas detectors and safety systems. While the mainstream silicon sensors demonstrated good performances, vertically aligned carbon nanotubes (VA-CNTs) outperform them and, therefore, are an attractive candidate material for capacitive applications owing to their extremely high surface area. Specifically, their top (crust) layer is characterized by a porous and dense morphology that further enhances the capacitive area and, consequently, induces an electrostatic fringe field and an enhancement of the capacitance. In this paper, we study how the porosity of VA-CNTs determines their electrostatic behavior. We observed that the porous surface of the crust layer generates a significant enhancement of the capacitance comparing to parallel plate capacitors. The rough surface of the crust layer results in amplification of the VA-CNT effective capacitor area, which further increases with the electrostatic gap. As-grown VA-CNTs with lower porosity demonstrate higher capacitance; however, densified samples and samples reinforced with conductive nano-particles did not show an enhancement of the capacitance, due to a significant change in their CNT formation. Thus, this paper emphasizes the influence of the morphological structure of VA-CNTs on their capacitance and enriches the material library that can be used for capacitive sensing.
KW - V-shaped MEMS devices
KW - temperature sensors
KW - thermal MEMS
UR - http://www.scopus.com/inward/record.url?scp=85065861751&partnerID=8YFLogxK
U2 - 10.1109/JSEN.2019.2899060
DO - 10.1109/JSEN.2019.2899060
M3 - Article
AN - SCOPUS:85065861751
VL - 19
SP - 4375
EP - 4380
JO - IEEE Sensors Journal
JF - IEEE Sensors Journal
SN - 1530-437X
IS - 12
M1 - 8641333
ER -