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    Longitudinal patent analysis for nanoscale science and engineering: Country, institution and technology field

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    Author
    Huang, Zan
    Chen, Hsinchun
    Yip, Alan
    Ng, Gavin
    Guo, Fei
    Chen, Zhi-Kai
    Roco, Mihail C.
    Issue Date
    2003
    Submitted date
    2004-08-16
    Keywords
    Artificial Intelligence
    Knowledge Management
    Local subject classification
    National Science Digital Library
    NSDL
    Artificial Intelligence lab
    AI lab
    Nanoscale science and engineering
    
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    Show full item record
    Citation
    Longitudinal patent analysis for nanoscale science and engineering: Country, institution and technology field 2003, 5:333-363 Journal of Nanoparticle Research
    Publisher
    Kluwer
    Journal
    Journal of Nanoparticle Research
    Description
    Artificial Intelligence Lab, Department of MIS, University of Arizona
    URI
    http://hdl.handle.net/10150/105834
    Abstract
    Nanoscale science and engineering (NSE) and related areas have seen rapid growth in recent years. The speed and scope of development in the field have made it essential for researchers to be informed on the progress across different laboratories, companies, industries and countries. In this project, we experimented with several analysis and visualization techniques on NSE-related United States patent documents to support various knowledge tasks. This paper presents results on the basic analysis of nanotechnology patents between 1976 and 2002, content map analysis and citation network analysis. The data have been obtained on individual countries, institutions and technology fields. The top 10 countries with the largest number of nanotechnology patents are the United States, Japan, France, the United Kingdom, Taiwan, Korea, the Netherlands, Switzerland, Italy and Australia. The fastest growth in the last 5 years has been in chemical and pharmaceutical fields, followed by semiconductor devices. The results demonstrate potential of information-based discovery and visualization technologies to capture knowledge regarding nanotechnology performance, transfer of knowledge and trends of development through analyzing the patent documents.
    Type
    Journal Article (Paginated)
    Language
    en
    Collections
    DLIST

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