Detection of ammonia based on a novel fluorescent artificial nose and pattern recognition

Özet

A simple and rapid fluorescent sensor array for identification and quantification of different concentrations(ppb level) of ammonia was proposed in this paper. Employing porphyrin, porphyrin derivativeand chemically responsive dyes as the sensing elements, the developed sensor array of artificial noseshowed a unique pattern of fluorescence changes upon its exposure to ammonia for just 4 min. And theeigenvalues from raw fluorescence spectra were analyzed by means of pattern recognition algorithm,including hierarchical cluster analysis (HCA), principal component analysis (PCA) and back-propagationneural network (BPNN). The results showed that HCA and PCA, which were used to assess the feasibilityand effectiveness of discrimination of fluorescent sensor array, revealed a distinct separation betweensamples. BPNN were used for automatically classifying and predicting concentration of ammonia, and theaccuracy was 97.55% while the relative standard deviation (RSD) was up to 3.67% for real samples. Itindicates the fluorescent artificial nose system is a rapid and feasible sensing platform for the identificationand quantitative analysis of gases, and also shows the possibilities in the field of environmentalgas detection and environmental gas monitoring.