کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
744392 1462084 2015 17 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Polyacrylic acid polymer and aldehydes template molecule based MIPs coated QCM sensors for detection of pattern aldehydes in body odor
موضوعات مرتبط
مهندسی و علوم پایه شیمی شیمی آنالیزی یا شیمی تجزیه
پیش نمایش صفحه اول مقاله
Polyacrylic acid polymer and aldehydes template molecule based MIPs coated QCM sensors for detection of pattern aldehydes in body odor
چکیده انگلیسی

Molecularly imprinted polymers (MIPs) have been prepared using the polyacrylic acid (PAA) as host polymer and hexanal, heptanal, and nonanal as pattern molecules. MIPs were employed as selective coating layer of quartz crystal microbalance (QCM) sensors. Hexanal, heptanal, and nonanal were opted as target chemicals after gas chromatography–mass spectrometer (GC–MS) characterization of body odor samples. Transient and static responses of four QCM sensors (three coated with MIPs and one with non-MIP) to target aldehydes in singly, binary and tertiary mixtures, and water at distinct concentrations have been measured. Transient responses were analyzed to compute the response time (ton), and recovery time (toff) of sensors. This result average values of ton ≈ 5 s and toff ≈ 10 s to typical concentrations of target odors. The sensitivity and baseline drift of sensors were also calculated using their static response. The heptanal template molecule based MIP coated QCM exhibit improved sensitivity, reproducibility and faster response, than the rest two MIPs, and non-MIP coated QCMs. Static sensors response matrices were further processed with principal component analysis (PCA) for qualitative (visual) discrimination and support vector machine (SVM) classifier for quantitative recognition (in %) of target aldehydes: in singly, binary and tertiary mixtures. Aldehydes odor was effectively identified in principal component (PC) space. Maximum recognition rate of 89% has been achieved for three classes of binary odors, and 79% for the combination of single, binary and tertiary odor classes in 3-fold cross-validation of SVM classifier.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Sensors and Actuators B: Chemical - Volume 206, January 2015, Pages 471–487
نویسندگان
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