DC Field | Value | Language |
---|---|---|
dc.contributor.author | Hwang, Charles S. H. | ko |
dc.contributor.author | Lee, Sangyeon | ko |
dc.contributor.author | Lee, Sejin | ko |
dc.contributor.author | Kim, Hanjin | ko |
dc.contributor.author | Kang, Taejoon | ko |
dc.contributor.author | Lee, Doheon | ko |
dc.contributor.author | Jeong, Ki-Hun | ko |
dc.date.accessioned | 2022-12-15T08:00:44Z | - |
dc.date.available | 2022-12-15T08:00:44Z | - |
dc.date.created | 2022-11-28 | - |
dc.date.created | 2022-11-28 | - |
dc.date.created | 2022-11-28 | - |
dc.date.issued | 2022-11 | - |
dc.identifier.citation | ACS APPLIED MATERIALS & INTERFACES, v.14, no.49, pp.54550 - 54557 | - |
dc.identifier.issn | 1944-8244 | - |
dc.identifier.uri | http://hdl.handle.net/10203/303060 | - |
dc.description.abstract | Human respiratory aerosols contain diverse potential biomarkers for early disease diagnosis. Here, we report the direct and label-free detection of SARS-CoV-2 in respiratory aerosols using a highly adsorptive Au-TiO2 nanocomposite SERS face mask and an ablation-assisted autoencoder. The Au-TiO2 SERS face mask continuously preconcentrates and efficiently captures the oronasal aerosols, which substantially enhances the SERS signal intensities by 47% compared to simple Au nanoislands. The ultrasensitive Au-TiO2 nanocomposites also demonstrate the successful detection of SARS-CoV-2 spike proteins in artificial respiratory aerosols at a 100 pM concentration level. The deep learning-based autoencoder, followed by the partial ablation of nondiscriminant SERS features of spike proteins, allows a quantitative assay of the 101-104 pfu/mL SARS-CoV-2 lysates (comparable to 19-29 PCR cyclic threshold from COVID-19 patients) in aerosols with an accuracy of over 98%. The Au-TiO2 SERS face mask provides a platform for breath biopsy for the detection of various biomarkers in respiratory aerosols. © 2022 The Authors. Published by American Chemical Society. | - |
dc.language | English | - |
dc.publisher | AMER CHEMICAL SOC | - |
dc.title | Highly Adsorptive Au-TiO2 Nanocomposites for the SERS Face Mask Allow the Machine-Learning-Based Quantitative Assay of SARS-CoV-2 in Artificial Breath Aerosols | - |
dc.type | Article | - |
dc.identifier.wosid | 000892070800001 | - |
dc.identifier.scopusid | 2-s2.0-85143531163 | - |
dc.type.rims | ART | - |
dc.citation.volume | 14 | - |
dc.citation.issue | 49 | - |
dc.citation.beginningpage | 54550 | - |
dc.citation.endingpage | 54557 | - |
dc.citation.publicationname | ACS APPLIED MATERIALS & INTERFACES | - |
dc.identifier.doi | 10.1021/acsami.2c16446 | - |
dc.contributor.localauthor | Lee, Doheon | - |
dc.contributor.localauthor | Jeong, Ki-Hun | - |
dc.contributor.nonIdAuthor | Lee, Sejin | - |
dc.contributor.nonIdAuthor | Kang, Taejoon | - |
dc.description.isOpenAccess | N | - |
dc.type.journalArticle | Article; Early Access | - |
dc.subject.keywordAuthor | SARS-CoV-2 | - |
dc.subject.keywordAuthor | surface-enhanced Raman spectroscopy | - |
dc.subject.keywordAuthor | breath biopsy | - |
dc.subject.keywordAuthor | machine-learning | - |
dc.subject.keywordAuthor | plasmonics | - |
dc.subject.keywordAuthor | nanocomposite | - |
dc.subject.keywordPlus | ENHANCED RAMAN-SPECTROSCOPY | - |
dc.subject.keywordPlus | VOLATILE ORGANIC-COMPOUNDS | - |
dc.subject.keywordPlus | FINGERPRINT | - |
dc.subject.keywordPlus | BIOMARKERS | - |
dc.subject.keywordPlus | DISEASE | - |
dc.subject.keywordPlus | SCENT | - |
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