Liu Chuanjun, Shang Liang, Yoshioka Hiro-Taka, Chen Bin, Hayashi Kenshi
Graduate School of Information Science and Electrical Engineering, Kyushu University, 744, Motooka, Nishi-ku, Fukuoka 819-0395, Japan; Research Laboratory, U.S.E. Co., Ltd., 22-10 Ebisu 4-Chome Shibuya-ku, Tokyo 150-0013, Japan.
Graduate School of Information Science and Electrical Engineering, Kyushu University, 744, Motooka, Nishi-ku, Fukuoka 819-0395, Japan.
Anal Chim Acta. 2018 Jun 20;1010:1-10. doi: 10.1016/j.aca.2018.01.004. Epub 2018 Jan 30.
The detection and discrimination of volatile carboxylic acid components, which are the main contributors to human body odor, have a wide range of potential applications. Here, a quartz crystal microbalance (QCM) sensor array based on molecularly imprinted polymer (MIP) nanobeads is developed for highly sensitive and selective sensing of typical carboxylic acid vapors, namely: propionic acid (PA), hexanoic acid (HA) and octanoic acid (OA). The MIP nanobeads were prepared by precipitation polymerization with methacrylic acid (MAA) as a functional monomer, trimethylolproane trimethacrylate (TRIM) as a crosslinker, and carboxylic acids (PA, HA and OA) as the template molecules. The precipitation polymerization resulted in nano-sized (150-200 nm) polymer beads with a regular shape. The polymerization conditions were optimized to give a functional monomer, crosslinker, and template ratio of 1:1:2. We investigated the imprinting effect using both QCM and GC/MS measurements comparing vapor absorption characteristics between the imprinted and non-imprinted (NIP) nanobeads. A four-channel QCM sensory array based on the NIP and the three types of MIP nanobeads was fabricated for sensing the three types of carboxylic acid vapor at concentrations on the ppm level. The output of the sensor array was analyzed by both a non-supervised method (principle component analysis: PCA) and supervised method (linear discrimination analysis: LDA). LDA showed a better discrimination ability than PCA. A 96%-classification rate was achieved by applying leave-one-out cross-validation to the LDA model. The high sensitivity and selectivity of the sensor array was attributed to the imprinting effect of the nano-sized polymer beads. The developed MIP nanobeads, together with other types of MIPs, show promise as materials for artificial receptors in vapor and odorant sensing.
挥发性羧酸成分是人体气味的主要来源，对其进行检测和鉴别具有广泛的潜在应用。在此，开发了一种基于分子印迹聚合物（MIP）纳米珠的石英晶体微天平（QCM）传感器阵列，用于对典型羧酸蒸气，即丙酸（PA）、己酸（HA）和辛酸（OA）进行高灵敏度和高选择性传感。以甲基丙烯酸（MAA）为功能单体、三羟甲基丙烷三甲基丙烯酸酯（TRIM）为交联剂、羧酸（PA、HA和OA）为模板分子，通过沉淀聚合法制备了MIP纳米珠。沉淀聚合得到了尺寸为纳米级（150 - 200 nm）、形状规则的聚合物珠。优化聚合条件，使功能单体、交联剂和模板的比例为1:1:2。我们使用QCM和GC/MS测量方法研究了印迹效果，比较了印迹和非印迹（NIP）纳米珠之间的蒸气吸收特性。基于NIP和三种类型的MIP纳米珠制备了一个四通道QCM传感阵列，用于检测ppm级浓度的三种羧酸蒸气。通过非监督方法（主成分分析：PCA）和监督方法（线性判别分析：LDA）对传感器阵列的输出进行分析。LDA显示出比PCA更好的判别能力。通过对LDA模型应用留一法交叉验证，实现了96%的分类率。传感器阵列的高灵敏度和高选择性归因于纳米级聚合物珠的印迹效果。所开发的MIP纳米珠与其他类型的MIP一起，有望成为用于蒸气和气味传感的人工受体材料。
