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dc.contributor.authorJang, Han Gyeol-
dc.contributor.authorJo, Jun Young-
dc.contributor.author박형범-
dc.contributor.author정용채-
dc.contributor.author최용석-
dc.contributor.authorSungmin Jung-
dc.contributor.author이도창-
dc.contributor.author김재우-
dc.date.accessioned2024-01-12T02:45:27Z-
dc.date.available2024-01-12T02:45:27Z-
dc.date.created2023-09-13-
dc.date.issued2023-08-13-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/76400-
dc.description.abstractSpiropyran (SP) mechanophores are attracting attention as next-generation smart materials that can self-diagnose stress or strain thanks to their capacity for stress visualization with superior sensitivity. However, at present, to achieve the self-reporting functionality, it is considered essential that SP is chemically bonded to a host matrix, which has greatly limited its application. In this paper, mechano-responsive SP beads that can render a material self-reporting by means of simple physical mixing are presented. The synthesis of SP beads is achieved in a microemulsifying needle via dispersion polymerization, and their application to various polymers and aluminum through blending or surface coating methods is reported. The self-reporting property of the specimen, evaluated by in situ measurements of color and full-field fluorescence during deformation, allows both homogeneous and spatially heterogeneous stress distributions to be successfully visualized; the experimental measurements are in good agreement with the finite element simulations. It is also observed that the mechano-response of SP beads is highly dependent on the stiffness of the matrix. The surface-coating method is demonstrated to possess great advantages in terms of applicability, sensitivity, and scalability, facilitating accurate self-diagnosis of the onset and propagation of damage in real time, even under complex stress conditions.-
dc.languageEnglish-
dc.publisherAmerican Chemical Society-
dc.titleMechano-responsive spiropyran microbeads: Facile fabrication strategy for self-reporting materials-
dc.typeConference-
dc.description.journalClass1-
dc.identifier.bibliographicCitation2023 ACS Fall meeting (Harnessing the Power of Data)-
dc.citation.title2023 ACS Fall meeting (Harnessing the Power of Data)-
dc.citation.conferencePlaceUS-
dc.citation.conferencePlaceMoscone Center 747 Howard St, San Francisco, CA-
dc.citation.conferenceDate2023-08-13-
dc.relation.isPartOfDivision of Polymeric Materials Science and Engineering-
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KIST Conference Paper > 2023
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