A quick responding quartz crystal microbalance sensor array based on molecular imprinted polyacrylic acids coating for selective identification of aldehydes in body odor

• Published in: Talanta (Oxford) 2015-03, Vol.134, p.105-119
• Main Authors: Jha, Sunil K., Hayashi, Kenshi
• Format: Article
• Language: English
• Subjects: Acrylic Resins - chemistry; Aldehydes; Aldehydes - analysis; Body odor; Caproates - chemistry; Caprylates - chemistry; Dynamics; Female; Hexanoic acid; Humans; Male; Microbalances; MIP; Molecular Imprinting; Octanoic acid; Odorants - analysis; Odors; Pattern recognition; Principal Component Analysis; Propionates - chemistry; QCM sensor; Quartz Crystal Microbalance Techniques; Sensor arrays; Support Vector Machine; Support vector machines
• ISSN: 0039-9140; 1873-3573
• DOI: 10.1016/j.talanta.2014.09.049

In present work, a novel quartz crystal microbalance (QCM) sensor array has been developed for prompt identification of primary aldehydes in human body odor. Molecularly imprinted polymers (MIP) are prepared using the polyacrylic acid (PAA) polymer matrix and three organic acids (propenoic acid, hexanoic acid and octanoic acid) as template molecules, and utilized as QCM surface coating layer. The performance of MIP films is characterized by 4-element QCM sensor array (three coated with MIP layers and one with pure PAA for reference) dynamic and static responses to target aldehydes: hexanal, heptanal, and nonanal in single, binary, and tertiary mixtures at distinct concentrations. The target aldehydes were selected subsequent to characterization of body odor samples with solid phase-micro extraction gas chromatography mass spectrometer (SPME-GC–MS). The hexanoic acid and octanoic acid imprinted PAA exhibit fast response, and better sensitivity, selectivity and reproducibility than the propenoic acid, and non-imprinted PAA in array. The response time and recovery time for hexanoic acid imprinted PAA are obtained as 5s and 12s respectively to typical concentrations of binary and tertiary mixtures of aldehydes using the static response. Dynamic sensor array response matrix has been processed with principal component analysis (PCA) for visual, and support vector machine (SVM) classifier for quantitative identification of target odors. Aldehyde odors were identified successfully in principal component (PC) space. SVM classifier results maximum recognition rate 79% for three classes of binary odors and 83% including single, binary, and tertiary odor classes in 3-fold cross validation. [Display omitted] •Organic acids as template molecule and polyacrylic acid based MIPs were developed.•MIPs coated QCM sensors exhibit fast, and reproducible response to aldehyde odor.•Target aldehydes were selected with GC–MS characterization of body odor samples.•PCA and SVM classifiers identify aldehydes effectively by sensors response analysis.