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Design and fabrication of single-walled carbon nanonet flexible strain sensors.

Huang YT, Huang SC, Hsu CC, Chao RM, Vu TK - Sensors (Basel) (2012)

Bottom Line: All of the micro-fabrication was compatible with the standard IC process.Experimental results indicated that the gauge factor of the proposed strain sensor was larger than 4.5, approximately 2.0 times greater than those of commercial gauges.The results also demonstrated that the gauge factor is small when the growth time of SWCNNs is lengthier, and the gauge factor is large when the line width of the serpentine pattern of SWCNNs is small.

View Article: PubMed Central - PubMed

Affiliation: Department of Mechanical Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung 80778, Taiwan. yating3133@yahoo.com.tw

ABSTRACT
This study presents a novel flexible strain sensor for real-time strain sensing. The material for strain sensing is single-walled carbon nanonets, grown using the alcohol catalytic chemical vapor deposition method, that were encapsulated between two layers of Parylene-C, with a polyimide layer as the sensing surface. All of the micro-fabrication was compatible with the standard IC process. Experimental results indicated that the gauge factor of the proposed strain sensor was larger than 4.5, approximately 2.0 times greater than those of commercial gauges. The results also demonstrated that the gauge factor is small when the growth time of SWCNNs is lengthier, and the gauge factor is large when the line width of the serpentine pattern of SWCNNs is small.

No MeSH data available.


Related in: MedlinePlus

ACCVD equipment diagram [22].
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f3-sensors-12-03269: ACCVD equipment diagram [22].

Mentions: In this study, the sensing material of the sensor, that is, single-walled carbon nanonets, which were grown using alcohol catalytic chemical vapor deposition equipment (ACCVD, as shown in Figure 3), was provided by National Nano Device Laboratories (NDL, Taiwan). The entire process is shown in Figure 4.


Design and fabrication of single-walled carbon nanonet flexible strain sensors.

Huang YT, Huang SC, Hsu CC, Chao RM, Vu TK - Sensors (Basel) (2012)

ACCVD equipment diagram [22].
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3376622&req=5

f3-sensors-12-03269: ACCVD equipment diagram [22].
Mentions: In this study, the sensing material of the sensor, that is, single-walled carbon nanonets, which were grown using alcohol catalytic chemical vapor deposition equipment (ACCVD, as shown in Figure 3), was provided by National Nano Device Laboratories (NDL, Taiwan). The entire process is shown in Figure 4.

Bottom Line: All of the micro-fabrication was compatible with the standard IC process.Experimental results indicated that the gauge factor of the proposed strain sensor was larger than 4.5, approximately 2.0 times greater than those of commercial gauges.The results also demonstrated that the gauge factor is small when the growth time of SWCNNs is lengthier, and the gauge factor is large when the line width of the serpentine pattern of SWCNNs is small.

View Article: PubMed Central - PubMed

Affiliation: Department of Mechanical Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung 80778, Taiwan. yating3133@yahoo.com.tw

ABSTRACT
This study presents a novel flexible strain sensor for real-time strain sensing. The material for strain sensing is single-walled carbon nanonets, grown using the alcohol catalytic chemical vapor deposition method, that were encapsulated between two layers of Parylene-C, with a polyimide layer as the sensing surface. All of the micro-fabrication was compatible with the standard IC process. Experimental results indicated that the gauge factor of the proposed strain sensor was larger than 4.5, approximately 2.0 times greater than those of commercial gauges. The results also demonstrated that the gauge factor is small when the growth time of SWCNNs is lengthier, and the gauge factor is large when the line width of the serpentine pattern of SWCNNs is small.

No MeSH data available.


Related in: MedlinePlus