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    A multistage, semi-automated procedure for analyzing the morphology of nanoparticles

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    Type
    Article
    Authors
    Park, Chiwoo
    Huang, Jianhua Z.
    Huitink, David
    Kundu, Subrata
    Mallick, Bani K.
    Liang, Hong
    Ding, Yu
    KAUST Grant Number
    KUS-CI-016-04
    Date
    2012-07
    Permanent link to this record
    http://hdl.handle.net/10754/597328
    
    Metadata
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    Abstract
    This article presents a multistage, semi-automated procedure that can expedite the morphology analysis of nanoparticles. Material scientists have long conjectured that the morphology of nanoparticles has a profound impact on the properties of the hosting material, but a bottleneck is the lack of a reliable and automated morphology analysis of the particles based on their image measurements. This article attempts to fill in this critical void. One particular challenge in nanomorphology analysis is how to analyze the overlapped nanoparticles, a problem not well addressed by the existing methods but effectively tackled by the method proposed in this article. This method entails multiple stages of operations, executed sequentially, and is considered semi-automated due to the inclusion of a semi-supervised clustering step. The proposed method is applied to several images of nanoparticles, producing the needed statistical characterization of their morphology. © 2012 "IIE".
    Citation
    Park C, Huang JZ, Huitink D, Kundu S, Mallick BK, et al. (2012) A multistage, semi-automated procedure for analyzing the morphology of nanoparticles. IIE Transactions 44: 507–522. Available: http://dx.doi.org/10.1080/0740817x.2011.587867.
    Sponsors
    The authors would like to acknowledge the generous support from their sponsors. Ding and Park were partially supported by NSF grants CMMI-0348150 and CMMI-1000088; Huang was partially supported by NSF grants DMS-0606580, and DMS-0907170; Ding, Park, Mallick, and Liang were partially supported by Texas Norman Hackerman Advanced Research Program grant 010366-0024-2007; Huang, Kundu, and Mallick were partially supported by King Abdullah University of Science and Technology award KUS-CI-016-04.
    Publisher
    Informa UK Limited
    Journal
    IIE Transactions
    DOI
    10.1080/0740817x.2011.587867
    ae974a485f413a2113503eed53cd6c53
    10.1080/0740817x.2011.587867
    Scopus Count
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