To automatically estimate the surface area coverage of carbon nanotubes on thin film transistors with image analysis : Bachelor’s degree project report
This report discuss the developement of a MATLAB-based tool for the analysis ofsurface area coverage of carbon nanotube networks from atomic force microscopyimages. The tool was compared with a manual method and the conclusion was that ithas, at least, the same accuracy as the manual mehtod, and it...
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ndltd-UPSALLA1-oai-DiVA.org-uu-1571682013-01-08T13:50:38ZTo automatically estimate the surface area coverage of carbon nanotubes on thin film transistors with image analysis : Bachelor’s degree project reportengNoring, MartinUppsala universitet, Institutionen för teknikvetenskaper2011image analysisthin film transistorTFTcarbon nanotubeCNTEngineering physicsTeknisk fysikThis report discuss the developement of a MATLAB-based tool for the analysis ofsurface area coverage of carbon nanotube networks from atomic force microscopyimages. The tool was compared with a manual method and the conclusion was that ithas, at least, the same accuracy as the manual mehtod, and it needs much less time forthe analysis. The tool couldn’t analyze images of carbon nanotube networks if theimages were to noisy or the networks to dense. The tool can help in the research ofthin-film transistors with carbon nanotube networks as the semiconducting channelmaterial. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-157168TVE ; 11031application/pdfinfo:eu-repo/semantics/openAccess |
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image analysis thin film transistor TFT carbon nanotube CNT Engineering physics Teknisk fysik |
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image analysis thin film transistor TFT carbon nanotube CNT Engineering physics Teknisk fysik Noring, Martin To automatically estimate the surface area coverage of carbon nanotubes on thin film transistors with image analysis : Bachelor’s degree project report |
description |
This report discuss the developement of a MATLAB-based tool for the analysis ofsurface area coverage of carbon nanotube networks from atomic force microscopyimages. The tool was compared with a manual method and the conclusion was that ithas, at least, the same accuracy as the manual mehtod, and it needs much less time forthe analysis. The tool couldn’t analyze images of carbon nanotube networks if theimages were to noisy or the networks to dense. The tool can help in the research ofthin-film transistors with carbon nanotube networks as the semiconducting channelmaterial. |
author |
Noring, Martin |
author_facet |
Noring, Martin |
author_sort |
Noring, Martin |
title |
To automatically estimate the surface area coverage of carbon nanotubes on thin film transistors with image analysis : Bachelor’s degree project report |
title_short |
To automatically estimate the surface area coverage of carbon nanotubes on thin film transistors with image analysis : Bachelor’s degree project report |
title_full |
To automatically estimate the surface area coverage of carbon nanotubes on thin film transistors with image analysis : Bachelor’s degree project report |
title_fullStr |
To automatically estimate the surface area coverage of carbon nanotubes on thin film transistors with image analysis : Bachelor’s degree project report |
title_full_unstemmed |
To automatically estimate the surface area coverage of carbon nanotubes on thin film transistors with image analysis : Bachelor’s degree project report |
title_sort |
to automatically estimate the surface area coverage of carbon nanotubes on thin film transistors with image analysis : bachelor’s degree project report |
publisher |
Uppsala universitet, Institutionen för teknikvetenskaper |
publishDate |
2011 |
url |
http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-157168 |
work_keys_str_mv |
AT noringmartin toautomaticallyestimatethesurfaceareacoverageofcarbonnanotubesonthinfilmtransistorswithimageanalysisbachelorsdegreeprojectreport |
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1716530533684477952 |