An e-nose made of carbon nanotube based quantum resistive sensors for the detection of eighteen polar/nonpolar VOC biomarkers of lung cancer

Abstract

A room temperature operating electronic nose (e-nose) has been developed by the assembly of conductive polymer nanocomposite (CPC) quantum resistive sensors (QRS). The fabrication of QRS by spray layer by layer (sLbL) of CPC solutions allowed us to obtain transducers with reproducible initial properties that could be easily tailored by adjusting either the number of sprayed layers and/or the solution composition. The selectivity of QRS was varied by changing the chemical nature of the polymer matrix in which carbon nanotubes (CNTs) were dispersed in solution, i.e., poly(carbonate) (PC), poly(caprolactone) (PCL), poly(lactic acid) (PLA), poly(styrene) (PS), and poly(methyl methacrylate) (PMMA). The e-nose was then successfully used to detect several volatile organic compounds (VOCs) selected among lung cancer biomarkers: a first set of seven polar vapours (water, ethanol, methanol, acetone, propanol, isopropanol, and 2-butanone), and another set of eleven less and nonpolar vapours (chloroform, toluene, benzene, styrene, cyclohexane, o-xylene, n-propane, n-decane, 1,2,4-trimethyl benzene, isoprene, and 1-hexene). The discrimination ability of the e-nose evaluated after a 3D principal component analysis (PCA) pattern recognition treatment was proved to be very good. Moreover, the quantitativity of the transducers' chemo-resistive responses was well fitted with the Langmuir–Henry-Clustering (LHC) model for both acetone and toluene vapours in a wide range of concentrations. The QRS developed in this study appear to be very good candidates to design low cost e-noses for the anticipated diagnosis of lung cancer by VOC analysis in breath, with ppm level sensitivity (tested down to 2.5 parts per million), short response time (a couple of seconds), low consumption, and a large signal to noise ratio (SNR ≥ 10).