Detection and identification of VOCs in their vapor phase is essential for safety and quality assessment. In this work, a novel platform of a paper-based polydiacetylene (PDA) colorimetric sensor array is prepared from eight diacetylene monomers, six of which are amphiphilic and the other two are bolaamphiphilic. To fabricate the sensors, monomers are coated onto a filter paper surface using the drop-casting technique and converted to PDAs by UV irradiation. The PDA sensors show solvent induced irreversible color transition upon exposure to VOC vapors. When combined into a sensing array, the color change pattern as measured by RGB values and statistically analyzed by principal component analysis (PCA) is capable of distinguishing 18 distinct VOCs in the vapor phase. The PCA score and loading plots also allow the reduction of the sensing elements in the array from eight to three PDAs that are capable of classifying 18 VOCs. Utilizing an array containing only two PDAs, various types of automotive fuels including gasoline, gasohol and diesel are successfully classified.

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A series of diacetylene lipids carrying primary amine, secondary amine or ammonium head groups are prepared and converted to blue polydiacetylene (PDA) sols by UV irradiation. The blue to pink colorimetric transition of polymerized diacetylenes in the presence of anionic surfactants such as sodium dodecanoate (SDC), sodium docecyl sulphate (SDS), and sodium dodecyl benzene sulphate (SDBS) are observed by the naked eye at the micromolar concentration level while there is no change with cationic surfactants and little response with nonionic surfactants. An identification of common anionic surfactants can be accomplished based on a combination of the colorimetric pattern of structurally diverse PDAs using the principal component analysis technique. Moreover, PDA was successfully fabricated on filter paper and the colorimetric response of PDA embedded on the paper was investigated which allowed the direct colorimetric detection of anionic surfactants.

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