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dc.contributor.authorCHOI, YENA-
dc.contributor.authorCHOI, JINKANG-
dc.contributor.authorKIM, WONSIK-
dc.contributor.authorSON, CHANG YUN-
dc.contributor.authorLee, Minjae-
dc.contributor.authorKIM, YOUNGKI-
dc.date.accessioned2023-02-20T00:48:42Z-
dc.date.available2023-02-20T00:48:42Z-
dc.date.created2023-02-18-
dc.date.issued2022-04-06-
dc.identifier.urihttps://oasis.postech.ac.kr/handle/2014.oak/115277-
dc.description.abstractSensitive and selective detection of salmonella that causes food-borne diseases is necessary for food safety and prevention of pathogenic infection. However, previous methods require laborious and time consuming process. Here, we offer simple approach to realize rapid detection of food poisoning bacteria (salmonella) by integrating extraordinary sensitivity of liquid crystals (LCs) and selectivity of organic ionics (OIs). Specifically, self-assembled OI at the aqueous interface of LC film cause vertical LC ordering. Under the incubation of LC in the aqueous solution with tryptone, however, we observe the formation and growth of birefringent domains after ~1.5 hours. Surprisingly, we observe the presence of salmonella to facilitate the formation of domains, which is dependent on salmonella population. We demonstrated the OI-LC system enables rapid detection of target bacteria within 20 min without any complex procedure. This work was supported by NRF-2021R1A4A1030944 & 2021R1A2C2095010-
dc.languageKorean-
dc.publisher한국고분자학회-
dc.relation.isPartOf한국고분자학회 춘계학술대회-
dc.titleDesign of Self-Reporting Liquid Crystals for Food Poisoning Bacteria-
dc.typeConference-
dc.type.rimsCONF-
dc.identifier.bibliographicCitation한국고분자학회 춘계학술대회-
dc.citation.conferenceDate2022-04-06-
dc.citation.conferencePlaceKO-
dc.citation.conferencePlace대전컨벤션센터-
dc.citation.title한국고분자학회 춘계학술대회-
dc.contributor.affiliatedAuthorCHOI, YENA-
dc.contributor.affiliatedAuthorCHOI, JINKANG-
dc.contributor.affiliatedAuthorKIM, WONSIK-
dc.contributor.affiliatedAuthorSON, CHANG YUN-
dc.contributor.affiliatedAuthorKIM, YOUNGKI-
dc.description.journalClass2-
dc.description.journalClass2-

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