SNU CBE

High‐Precision Multiplex Chemical Sensors with Pattern‐Recognition Capability via a Letter Printing‐Inspired Transfer Method

2026 · Small

저자

Yoon Ho Lee, Hyun Woo Song, Kyung Min Lee, Minsung Kim, Cheol Hee Park, Su Hye Jeong, Sang Kyu Kwak, 오준학 (Joon Hak Oh)

연구주제

Advanced Chemical Sensor Technologies · Graphene research and applications · Gas Sensing Nanomaterials and Sensors

NTIS 과학기술표준분류

가장 가까운 분류(에너지/자원 > 신재생에너지 > 태양광)가 화학·화공 범위 밖이다. 배정 근거: AI 키워드가 잡은 NTIS 과제의 분류.

AI 연구 키워드·방법

chemical sensor array graphene field effect transistor 전사 인쇄

pattern recognition

키워드 (OpenAlex)

graphene field-effect transistors transfer printing letterpress printing sensor arrays pattern recognition artificial neural network classification volatile organic compounds interfacial adhesion

초록

Graphene-based chemical sensors offer high sensitivity owing to exceptional charge transport and a large surface-to-volume ratio, yet reliable discrimination across diverse analytes remains challenging. In this study, a letterpress-inspired, one-step transfer-printing strategy integrated with pattern-recognition analysis is proposed to implement multiplexed chemical sensor arrays based on graphene field-effect transistors (GFETs). By tuning interfacial adhesion between functional materials and a polymer stamp, accurate and area-selective functionalization with sub-10 µm feature sizes is achieved, thereby enabling simultaneous multifunctionalization of graphene. The resulting 3 × 3 GFET sensor arrays, comprising both functionalized and pristine channels, generate distinct sensing response patterns to representative volatile organic compounds, including chlorobenzene, toluene, and methanol…

이 논문을 지원한 국가R&D 과제 (NTIS 성과)

NTIS 성과DB(2020–24)에서 DOI 매칭 없음

인접 그래프

노드 hover = 이웃 강조 · 1회 클릭 = 고정 · 고정된 노드 다시 클릭 = 페이지 이동

이 문서와 연결된 페이지

교수 1

오준학

연구주제 1

Advanced Chemical Sensor Technologies

키워드 1

전사 인쇄