有機薄膜軟性電子氣體感測在非侵入性檢測上之研發---有機薄膜電晶體生物分子固定化技術與高選擇性氣體感測之研發(總計畫及子計畫一)(I)

Abstract

有機薄膜電晶體(OTFTs)可被大面積製造、具低成本、可拋棄式的優點，非常適合用來開發非 侵入式醫療診斷感測產品或於環境監測上之應用。本計劃將研發有機薄膜電晶體上生物分子固定 化技術及建構具有不同官能基之自我組織分子材料組織分子層(SAM)。我們將針對主動層之沉積條 件、表面形貌與聚合物官能基之調控，開發新型氣體感測元件，並變化固定生物分子類別，探討 其感測之選擇性及專一性，以實現具高靈敏度、高選擇性之軟性電子氣體感測陣列。同時開發新 型連續性薄膜沉積設備，使同一腔體可使用兩種鍍膜方法，沉積小分子有機薄膜或聚合物薄膜， 以達到製程可以在不破真空的狀態下，連續完成，並變化電晶體結構，以達可靠的感測指標並提 升感測靈敏度。非侵入式氣體感測於生物醫學之應用，將先以監控肝硬化病情為研究方向。血氨 在肺行氣體交換時會部分擴散至呼氣中，量測呼氣中的氨濃度可以推估病人血氨的濃度，為肝硬 化病病情指標。肝硬化的病人多為在家休養，故很需要在家輔助檢測的儀器。實驗結果將和本計 畫建立的氣味偵測資料庫比對、並與氣相層析分析結果交叉分析。最後也將搭配現有的生物資訊 技術做machine learning 以更進一步推展本計劃的氣味偵測系統做複雜性氣體的偵測與判讀。

Organic thin-film transistors (OTFTs) possess great potentials in realizing large size, low-cost, one-time-use, and yet non-invasive sensors for medical and environmental applications. Development of such highly selective, sensitive and flexible gas sensor array will direct the core course for this project, in which it comprises the development of various self-assembled monolayer (SAM) materials and immobilized biomolecules techniques. In addition, the effects of gas sensing mechanism and selectivity due to the OTFTs active layers will be particularly addressed in our efforts by various active layer materials, deposition process conditions, surface morphology, and functional group modification of polymeric conjugated materials. Furthermore, this study will also undertake the vacuum deposition equipment integration which enables the continuous process for thin film deposition. For the biomedical application of the gas sensor, this research will be targeted on cirrhosis clinical diagnosis. The ammonia presence in patient’s breath is one of cirrhosis clinical symptoms. This is due to blood ammonia diffused during respiration. The exhaled ammonia concentration can be detected as the measurement of blood ammonia concentration. As a result, the medical personnel can monitor the progress of cirrhosis according the breath ammonia reading. During the course of study, the patients’ breath samples will be provided by collaboration with China Medical University Hospital. The database will be established and compared with the results of gas chromatography. Finally, we will apply machine learning and the current methods of bioinformatics in order to extent the applications on complex gases detection and precise reading. The future goal is to fabricate the home care ammonia gas detector for cirrhosis patients.