SNU CBE

Computational Method‐Based Optimization of Carbon Nanotube Thin‐Film Immunosensor for Rapid Detection of SARS‐CoV‐2 Virus

2021 · Small Science

저자

Su Yeong Kim, Jeong‐Chan Lee, Giwan Seo, Jun Hee Woo, Min Ho Lee, 남재욱 (Jaewook Nam), Joo Yong Sim, Hyung‐Ryong Kim, Edmond Changkyun Park, Steve Park

연구주제

Electrochemical sensors and biosensors

NTIS 과학기술표준분류

가장 가까운 분류(보건의료 > 의료기기)가 화학·화공 범위 밖이다. 배정 근거: 지원 과제·키워드 근거가 없어 AI가 논문 제목·초록을 읽고 고른 분류.

AI 연구 키워드·방법

carbon nanotube thin film immunosensor sars cov 2 detection

computational optimization

키워드 (OpenAlex)

carbon nanotube films immunosensor COVID-19 detection COVID-19 diagnosis nucleocapsid protein point-of-care testing biosensor sensitivity rapid virus detection

초록

The recent global spread of COVID‐19 stresses the importance of developing diagnostic testing that is rapid and does not require specialized laboratories. In this regard, nanomaterial thin‐film‐based immunosensors fabricated via solution processing are promising, potentially due to their mass manufacturability, on‐site detection, and high sensitivity that enable direct detection of virus without the need for molecular amplification. However, thus far, thin‐film‐based biosensors have been fabricated without properly analyzing how the thin‐film properties are correlated with the biosensor performance, limiting the understanding of property−performance relationships and the optimization process. Herein, the correlations between various thin‐film properties and the sensitivity of carbon nanotube thin‐film‐based immunosensors are systematically analyzed, through which optimal sensitivity is a…

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NTIS 성과DB(2020–24)에서 DOI 매칭 없음

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