Detecting the electrical conductivity of single walled carbon nano-tubes by a DFM detection system
文献类型:期刊论文
作者 | Zhao ZX(赵增旭)![]() ![]() ![]() ![]() |
刊名 | Science China Technological Sciences
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出版日期 | 2014 |
卷号 | 57期号:1页码:49-54 |
关键词 | Differentiation (calculus) Technology |
ISSN号 | 1674-7321 |
产权排序 | 1 |
通讯作者 | 田孝军 |
中文摘要 | Rare SWCNT materials contain both metallic SWCNT (m-SWCNT) and semi-conducting SWCNT(s-SWCNT). Since m-SWCNT and s-SWCNT have very different applications, it is necessary to differentiate them so as to further separate them for more efficient CNT utilization. To achieve this goal, the authors established a dielectric force microscope (DFM) detection system to differentiate s-SWCNT from m-SWCNT, based on different 2ω force decided by SWCNT's conductivity under AC electric field. The experimental results showed that s-SWCNT can be clearly differentiated from m-SWCNT. The statistics analysis shows that the detected number proportion of s-SWCNT to m-SWCNT matches the well-known proportion 2:1 in the normally prepared CNT materials. The above results strongly verified the effectiveness of the detection system. |
类目[WOS] | Engineering, Multidisciplinary ; Materials Science, Multidisciplinary |
研究领域[WOS] | Engineering ; Materials Science |
关键词[WOS] | NANOTUBES ; FABRICATION ; SENSORS |
收录类别 | SCI ; EI |
语种 | 英语 |
WOS记录号 | WOS:000329310200010 |
源URL | [http://ir.sia.cn/handle/173321/14723] ![]() |
专题 | 沈阳自动化研究所_机器人学研究室 |
推荐引用方式 GB/T 7714 | Zhao ZX,Tian XJ,Liu J,et al. Detecting the electrical conductivity of single walled carbon nano-tubes by a DFM detection system[J]. Science China Technological Sciences,2014,57(1):49-54. |
APA | Zhao ZX,Tian XJ,Liu J,Dong ZL,&Wang YC.(2014).Detecting the electrical conductivity of single walled carbon nano-tubes by a DFM detection system.Science China Technological Sciences,57(1),49-54. |
MLA | Zhao ZX,et al."Detecting the electrical conductivity of single walled carbon nano-tubes by a DFM detection system".Science China Technological Sciences 57.1(2014):49-54. |
入库方式: OAI收割
来源:沈阳自动化研究所
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