TY - JOUR
T1 - Polyacrylic acid polymer and aldehydes template molecule based MIPs coated QCM sensors for detection of pattern aldehydes in body odor
AU - Jha, Sunil K.
AU - Hayashi, Kenshi
N1 - Funding Information:
This research work was supported by Grant-in-Aid for JSPS fellows 24.02367 and partly supported by JSPS KAKENHI Grant Number 25420409 . The author S.K.J. gratefully acknowledges all lab colleagues, Dr. C. Liu, and Mrs. Anju Sunil Jha for their contribution and support during the study.
Funding Information:
Sunil K. Jha received his B.Sc. and M.Sc. in Physics from Udai Pratap Autonomous College, Varanasi affiliated to V.B.S. Purvanchal University, Jaunpur, India, in 2003 and 2005 and Ph.D. in Physics from Banaras Hindu University, Varanasi, India in 2012. He is currently postdoctoral research fellow sponsored by the Japan Society for the Promotion of Science (JSPS) for pursuing research at the Organic Electronic Device Lab, Department of Electronics, Kyushu University (Japan). His present research interests include sensor array signal processing, multivariate data analysis, data fusion and human body odor analysis.
Publisher Copyright:
© 2014 Elsevier B.V. All rights reserved.
PY - 2015/1
Y1 - 2015/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84908031924&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84908031924&partnerID=8YFLogxK
U2 - 10.1016/j.snb.2014.09.102
DO - 10.1016/j.snb.2014.09.102
M3 - Article
AN - SCOPUS:84908031924
SN - 0925-4005
VL - 206
SP - 471
EP - 487
JO - Sensors and Actuators, B: Chemical
JF - Sensors and Actuators, B: Chemical
ER -