研究生: |
周育瑋 Yu-Wei Chou |
---|---|
論文名稱: |
聚合物修飾奈米金殼之表面電漿共振氣體感測陣列的最佳化研究 Optimization for Localized Surface Plasmon Resonance Vapor Sensor Array Using Polymer Coated Gold Nanoshells |
指導教授: |
呂家榮
Lu, Chia-Jung |
學位類別: |
碩士 Master |
系所名稱: |
化學系 Department of Chemistry |
論文出版年: | 2012 |
畢業學年度: | 100 |
語文別: | 中文 |
論文頁數: | 67 |
中文關鍵詞: | 局部表面電漿共振 、奈米粒子 、有機揮發性氣體感測器 |
英文關鍵詞: | LSPR, nanoparticle, VOC sensor |
論文種類: | 學術論文 |
相關次數: | 點閱:226 下載:15 |
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本研究研發出一組局部表面電漿共振(localized surface plasmon resonance, LSPR)感測器陣列,藉由在奈米金殼粒子表面修飾具有不同官能基的聚合物來增強對於有機揮發性氣體(volatile organic compounds, VOCs)的化學選擇性。從即時光譜觀測LSPR變化的結果,可以得知經過表面修飾後的感測器對八種有機氣體均具有選擇性,此外仍能保有快速反應的特性,對不同氣體濃度進行偵測時也能獲得良好的線性關係。
為找出具有最佳氣體鑑別度的感測器陣列組合,本研究使用五種計算方法進行判斷,分別為:最大距離法、變異數法、最大面積法、F檢定(F-test)、Wilcoxon-Wilcox檢定(Wilcoxon-Wilcox test)。其中,由變異數法指出使用DB-1、PIB、PECH三種感測器的組合鑑別度較佳,而最大距離法與最大面積法則是以PEG、PIB、PECH的感測器組合鑑別度較佳;F檢定得出具有較佳鑑別度的組合分別為{PEG, PIB}、{PEG, PECH}、{PMMA, PECH}這三種,至於Wilcoxon-Wilcox檢定則為PEG、PIB與PEG、PECH這二種組合。經由上述判斷的過程,有助於從大量的感測數據中快速篩選出具有最佳鑑別度的感測器組合。
This research uses gold nanoshells as the localized surface plasmon resonance (LSPR) sensors that were surface-modified with various polymer thin films to provide chemical selectivity for detecting volatile organic compounds (VOCs). The changes of LSPR spectrum were measured by real-time UV-visible spectrum. Distinguishable patterns of the tested organic vapors with different functional groups were generated by one unmodified and seven surface-modified gold nanoshell LSPR sensors. The polymer modification altered the surface chemical affinity without increasing the response time.
In order to find out the sensor set which would obtain the best recognition rate, five analytical methods were introduced: maximum distance, sum of variance, maximum area, F-test, and Wilcoxon-Wilcox test. The sum of variance method indicated that the {DB-1, PIB, PECH} sensor set had a better result, whereas the maximum distance and maximum area method showed the higher efficiency of the {PEG, PIB, PECH} sensor set. The result of F-test represented that {PEG, PIB}, {PEG, PECH}, and {PMMA, PECH} would be the possible sets, while Wilcoxon-Wilcox test indicated that {PEG, PIB} and {PEG, PECH} were the sets with significant differences. According to these analytical methods, the sensor set with obvious patterns would be easy to figure out from large amounts of sensing data without time-consuming.
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