Simple and rapid differentiation of toxic gases using a quartz crystal microbalance sensor array coupled with principal component analysis

https://doi.org/10.1016/j.sna.2017.05.039Get rights and content

Highlights

  • GO-based and N-substituted pyrrole derivative-based coated QCM sensors combined with PCA for differentiating toxic gases.

  • An array of only three QCM sensors simplifies its construction, reducing the cost of sensors and simplifying data statistic analysis.

  • A good qualitative differentiation of the major target toxic gas from a mixture of gases was obtained.

  • The differentiation rate was closely related to the concentrations of the toxic gas.

Abstract

A novel quartz crystal microbalance (QCM) sensor array was fabricated for differentiating three toxic gases (NH3, CO and NO2) from their tertiary mixtures. The QCM sensor array composed of three QCM sensors that were constructed using graphene oxide (GO)-based and N-substituted pyrrole derivative-based films. The response frequency changes of a QCM sensor array were recorded upon exposing to each target toxic gas with varying concentrations and the obtained data were analyzed by principal component analysis (PCA) in order to differentiate the target toxic gas under testing condition of tertiary mixing of toxic gases. The results of this work show promising prospects for the use of a low-cost, easy to use and rapid method for differentiating the target toxic gas in the presence of a mixture of gases.

Introduction

A very sensitive detection is required to monitor toxic gases such as NH3, NO2 and CO gas because these toxic gases are known to be extremely harmful to the human body and the environment. In general, a cross-sensitivity effect usually occurs to sense toxic gases using a semiconductor metal oxide sensor. NH3 gas is a reducing gas (electron-donating) and NO2 is an oxidizing gas (electron-withdrawing) so that as sensing NH3 may be interfered with NO2 in a real-world gas mixture. Therefore, developing a selective sensing technique is crucial for sensing toxic gas in mixed gas system. Graphene oxide (GO) was produced by oxidized graphite among the strongest oxidation conditions [1]. GO contains a large number of reactive oxygen functional groups, including carboxyl, epoxy and hydroxyl groups decorated at the carbon sheets, rendering it a good precursor in the functionalization of graphene [1], [2]. Moreover, reduced graphene oxide (RGO) can be produced by chemical or thermal reduction of GO, enhancing the electrical conductivity of the RGO [3], [4]. Therefore, GO and RGO have been used to detect various chemical species, such as NO2, NH3, H2 and CO2 [5], [6], [7], [8], [9], [10]. However, the major drawback of the GO- and RGO-based material is that it had bad selectivity for gas-sensing. The β-cyclodextrin (β-CD) is cyclic oligosaccharides that are composed of seven glucose units, which are toroidal in shape with a hydrophobic inner cavity and a hydrophilic exterior. This unique structure can be used to selectively bind many kinds of organic, inorganic and biological molecules into their cavities via the host-guest interaction [11], [12]. Therefore, β-CD was used to functionalize the surface of the GO for sensing various compounds, such as diethylstilbestrol, dopamine and imidacloprid [12], [13], [14].

Polypyrrole (PPy) is one of the conducting polymers have been intensively studied because its advantages of strong mechanical, good electrical properties and good environmental stability [15]. Moreover, N-substituted pyrrole derivatives have attracted considerable attention because they have a wide range of pharmacological and biological activities [15]. Therefore, PPy and N-substituted pyrrole derivatives have been applied in sensor devices [16], [17]. However, GO-based and PPy-based sensing-materials both had the poor selectivity for simultaneously sensing NH3 and NO2 gases.

Quartz-crystal microbalance (QCM) is a low-cost, very mass-sensitive and stable gravimetric chemical sensor that can measure a mass changes on nanogram scale [18]. Therefore, many sensitive material deposited on QCM were used to detect various gas molecules [19], [20]. Upon exposure to gaseous medium, adsorbed on the surface of the QCM, inducing a frequency decrease proportional to adsorbed mass, according to the Sauerbrey’s equation as follows [21]:Δf=(2.3×106fo2A)Δmwhere Δf (Hz) is the frequency changes of the piezoelectric crystal, fo (MHz) is the basic frequency of the unloaded piezoelectric crystal, A (cm2) is the surface area of the electrode, and Δm (g) is the change in mass on the surface of the crystal. Principal component analysis (PCA) is a pattern recognition technique effectively and widely used to analyze, classify and decrease the dimensionality of a data set. Thus, a new coordinate base is obtained from the original data matrix by PCA, forming new principal components. PCA is also a powerful graphic visualization of classification widely used in the gas-sensing applications [22], [23]. Therefore, QCM sensor arrays coupled with PCA have been used to discriminate various samples, such as olive oil samples [24], [25], chocolate samples [26], aldehydes in body odor [27] and organic acids in body odor [28]. According to our knowledge, no attempt has been made to fabricate a QCM sensor array that was based on GO-based and N-substituted pyrrole derivative-based sensing materials coupled with PCA for classifying toxic gases to differentiate toxic gases. The selective analysis of the toxic gases is a main challenge in the industrial safety field for in-situ monitoring the working environment to protect the safety of worker. In this work, a QCM sensor array composed of three QCM sensors that were made of GO, β-CD-functionalized GO (β-CD-GO) and Au nanoparticles (Au NPs)/N-substituted pyrrole derivative composite films were fabricated. The response of QCM sensor array was measured to NH3, NO2 and CO toxic gases, in singly and their tertiary mixtures with varying gas concentrations. The QCM sensor array response matrix was analyzed with PCA for tertiary mixed gases classification. This method is based on a controlled modulation of the single gas concentrations, producing an output signal of single toxic gas, analyzing the output signals by the PCA yields as the output features of this process and the clustering of these features can be used to differentiate major gas in presence of tertiary mixing of toxic gases.

Section snippets

Materials

Graphene oxide (GO; 5 g/L, UniRegion Bio-Tech) were used without further purification. β-CD functionalized GO (β-CD-GO) was prepared using the method in our literature [29]. Mixing GO with β-CD (20 mL, 80 mg/L), then, the mixture was added to ammonia water and hydrazine hydrate with strong stirring for 10 min, finally, the resultant solution was stirred under a water bath at 60 °C for 4 h. 1-(4-Nitrophenyl)-2,5-dimethyl-1H-pyrrole was prepared according to our previous study [17] by a well-known

Response of QCM sensors to single toxic gas

Fig. 3 plots the response (frequency shift) of three QCM sensors to single gas at different concentrations. The average sensors response to NH3 gas at concentrations from 1000 to 5000 ppm (Fig. 3(a)) was higher than that of CO gas at concentrations from 1500 to 7500 ppm (Fig. 3(b)) and NH2 gas at concentrations from 10 to 50 ppm (Fig. 3(c)). Additionally, the average sensors response to CO gas was higher than that of NO2 gas. These results were thought to arise from the two main phenomena. First,

Conclusions

A novel sensor array only three QCM sensors that were constructed using GO, β-CD-GO and Au NPs/N-substituted pyrrole derivative composite films was combined with the PCA to successfully differentiate major composition of the mixture of toxic gases. A modulation of the sensors input was performed by modulation of the toxic gas concentrations and then the modulated output signals were analyzed using the PCA, which allowed the response frequency changes information on the signal to be extracted

Pi-Guey Su is currently a professor in Department of Chemistry at Chinese Culture University. He received his BS degree from Soochow University in Chemistry in 1993 and PhD degree in chemistry from National Tsing Hua University in 1998. He worked as a researcher in Industrial Technology Research Institute, Taiwan, from 1998 to 2002. He joined as an assistant professor in the General Education Center, Chungchou Institute of Technology from 2003 to 2005. He worked as an assistant professor in

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Pi-Guey Su is currently a professor in Department of Chemistry at Chinese Culture University. He received his BS degree from Soochow University in Chemistry in 1993 and PhD degree in chemistry from National Tsing Hua University in 1998. He worked as a researcher in Industrial Technology Research Institute, Taiwan, from 1998 to 2002. He joined as an assistant professor in the General Education Center, Chungchou Institute of Technology from 2003 to 2005. He worked as an assistant professor in Department of Chemistry at Chinese Culture University from 2005 to 2007. He worked as an associate professor in Department of Chemistry at Chinese Culture University from 2007 to 2010. His fields of interests are chemical sensors, gas and humidity sensing materials and humidity standard technology.

Tsao-Yun Chuang received a BS degree in Chemistry from Chinese Culture University in 2014. He entered the MS course of Chemistry at Chinese Culture University in 2014. His main areas of interest are gas-sensing materials and QCM sensor technique.

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