Colorimetric artificial nose for identification of breath volatile organic compounds of patients with lung cancer

Abstract

A novel and highly sensitive colorimetric sensor array was developed for the detection and identification of breath volatile organic compounds(VOCs) of patients with lung cancer. Employing dimeric metalloporphyrins, metallosalphen complexes, and chemically responsive dyes as the sensing elements, the developed sensor array of artificial nose shows a unique pattern of colorific changes upon its exposure to eight less-reactive VOCs and their mixture gas at a concentration of 735 nmol/L within 3 min. Potential of quantitative analysis of VOCs samples was proved. A good linear relationship of 490–3675 nmol/L was obtained for benzene vapor with a detection limit of 49 nmol/L(S/N=3). Data analysis was carried out by Hierarchical cluster analysis(HCA) and principal component analysis(PCA). Each category of breath VOCs clusters together in the PCA score plot. No errors in classification by HCA were observed in 45 trials. Additionaly, the colorimetric sensor array showed good reproducibility under the cyclic sensing experiments. These results demonstrate that the developed colorimetric artificial nose system is an excellent sensing platform for the identification and quantitative analysis of breath VOCs of patients with lung cancer.