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

Handle URI:
http://hdl.handle.net/10754/597328
Title:
A multistage, semi-automated procedure for analyzing the morphology of nanoparticles
Authors:
Park, Chiwoo; Huang, Jianhua Z.; Huitink, David; Kundu, Subrata; Mallick, Bani K.; Liang, Hong; Ding, Yu
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.
Publisher:
Informa UK Limited
Journal:
IIE Transactions
KAUST Grant Number:
KUS-CI-016-04
Issue Date:
Jul-2012
DOI:
10.1080/0740817x.2011.587867
Type:
Article
ISSN:
0740-817X; 1545-8830
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.
Appears in Collections:
Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorPark, Chiwooen
dc.contributor.authorHuang, Jianhua Z.en
dc.contributor.authorHuitink, Daviden
dc.contributor.authorKundu, Subrataen
dc.contributor.authorMallick, Bani K.en
dc.contributor.authorLiang, Hongen
dc.contributor.authorDing, Yuen
dc.date.accessioned2016-02-25T12:30:47Zen
dc.date.available2016-02-25T12:30:47Zen
dc.date.issued2012-07en
dc.identifier.citationPark 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.en
dc.identifier.issn0740-817Xen
dc.identifier.issn1545-8830en
dc.identifier.doi10.1080/0740817x.2011.587867en
dc.identifier.urihttp://hdl.handle.net/10754/597328en
dc.description.abstractThis 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".en
dc.description.sponsorshipThe 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.en
dc.publisherInforma UK Limiteden
dc.subjectmachine learningen
dc.subjectmorphology analysisen
dc.subjectNano imagingen
dc.subjectnanoparticle overlappingen
dc.subjectshape analysisen
dc.titleA multistage, semi-automated procedure for analyzing the morphology of nanoparticlesen
dc.typeArticleen
dc.identifier.journalIIE Transactionsen
dc.contributor.institutionTexas A and M University, College Station, United Statesen
kaust.grant.numberKUS-CI-016-04en
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