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dc.contributor.authorMoon, Hi Gyu-
dc.contributor.authorJung, Youngmo-
dc.contributor.authorJun, Dukwoo-
dc.contributor.authorPark, Ji Hyun-
dc.contributor.authorChang, Young Wook-
dc.contributor.authorPark, Hyung-Ho-
dc.contributor.authorKang, Chong-Yun-
dc.contributor.authorKim, Chulki-
dc.contributor.authorKaner, Richard B.-
dc.date.accessioned2024-01-19T23:30:42Z-
dc.date.available2024-01-19T23:30:42Z-
dc.date.created2021-09-03-
dc.date.issued2018-03-
dc.identifier.issn2379-3694-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/121680-
dc.description.abstractHollow-structured nanomaterials are presented as an outstanding sensing platform because of their unique combination of high porosity in both the micro- and nanoscale, their biocompatibility, and flexible template applicability. Herein, we introduce a bacterial skeleton method allowing for cost-effective fabrication with nanoscale precision. As a proof-of-concept, we fabricated a hollow SnO2 hemipill network (HSHN) and a hollow Pt-functionalized SnO2 hemipill network (HPN). A superior detecting capability of HPN toward acetone, a diabetes biomarker, was demonstrated at low concentration (200 ppb) under high humidity (RH 80%). The detection limit reaches 3.6 ppb, a level satisfying the minimum requirement for diabetes breath diagnosis. High selectivity of the HPN sensor against C6H6, C7H8, CO, and NO vapors is demonstrated using principal component analysis (PCA), suggesting new applications of HPN for human-activity monitoring and a personal healthcare tool for diagnosing diabetes. The skeleton method can be further employed to mimic nanostructures of biomaterials with unique functionality for broad applications.-
dc.languageEnglish-
dc.publisherAMER CHEMICAL SOC-
dc.subjectGAS-SENSING PROPERTIES-
dc.subjectEXHALED-BREATH-
dc.subjectOXIDE NANOSTRUCTURES-
dc.subjectSELECTIVE DETECTION-
dc.subjectWO3 NANOFIBERS-
dc.subjectLUNG-CANCER-
dc.subjectSENSORS-
dc.subjectNANOPARTICLES-
dc.subjectACETONE-
dc.subjectCO-
dc.titleHollow Pt-Functionalized SnO2 Hemipill Network Formation Using a Bacterial Skeleton for the Noninvasive Diagnosis of Diabetes-
dc.typeArticle-
dc.identifier.doi10.1021/acssensors.7b00955-
dc.description.journalClass1-
dc.identifier.bibliographicCitationACS Sensors, v.3, no.3, pp.661 - 669-
dc.citation.titleACS Sensors-
dc.citation.volume3-
dc.citation.number3-
dc.citation.startPage661-
dc.citation.endPage669-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.identifier.wosid000428608400019-
dc.identifier.scopusid2-s2.0-85044434841-
dc.relation.journalWebOfScienceCategoryChemistry, Multidisciplinary-
dc.relation.journalWebOfScienceCategoryChemistry, Analytical-
dc.relation.journalWebOfScienceCategoryNanoscience & Nanotechnology-
dc.relation.journalResearchAreaChemistry-
dc.relation.journalResearchAreaScience & Technology - Other Topics-
dc.type.docTypeArticle-
dc.subject.keywordPlusGAS-SENSING PROPERTIES-
dc.subject.keywordPlusEXHALED-BREATH-
dc.subject.keywordPlusOXIDE NANOSTRUCTURES-
dc.subject.keywordPlusSELECTIVE DETECTION-
dc.subject.keywordPlusWO3 NANOFIBERS-
dc.subject.keywordPlusLUNG-CANCER-
dc.subject.keywordPlusSENSORS-
dc.subject.keywordPlusNANOPARTICLES-
dc.subject.keywordPlusACETONE-
dc.subject.keywordPlusCO-
dc.subject.keywordAuthorhollow SnO2 nanostructures-
dc.subject.keywordAuthorbacterial skeleton-
dc.subject.keywordAuthorchemiresisitve sensor-
dc.subject.keywordAuthorexhaled breath analyzer-
dc.subject.keywordAuthordiabetes-
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