Development of a Simple Cataluminescence Sensor System for Detecting and Discriminating Volatile Organic Compounds at Different Concentrations

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1 pubs.acs.org/ac Development of a Simple Cataluminescence Sensor System for Detecting and Discriminating Volatile Organic Compounds at Different Concentrations Runkun Zhang, Xiaoan Cao,* Yonghui Liu, and Xiangyang Chang Environmental Science and Engineering Institute, Guangzhou University, , Guangzhou, China *S Supporting Information Downloaded via on March 17, 2019 at 03:05:53 (UTC). See for options on how to legitimately share published articles. ABSTRACT: The detection and identification of volatile organic compounds (VOCs) is one of the most serious subjects in the field of chemical sensing, but it remains an enormous challenge. Usually, during the sensing of gases involved in chemical reactions, the residual gas of that reaction (including undecomposed analytes and reaction products) are considered waste gases and released into the air. Here, a novel cataluminescence (CTL) sensing method based on detection of the luminescent intensities of both the analyte (I A ) and its products (I R ) was developed and used to identify VOCs at different concentrations. After the analyte gas passed through the first sensing material, the product gas was treated as a new reactant and passed through the second sensing material (which could be the same as or different from the first material). The luminescent signals of I A and I R were recorded over a short period of time using one photomultiplier. We found the ratio of I A to I R (I A /I R ) to be a unique characteristic of a given analyte within a wide range of concentrations. To illustrate the new method, 11 kinds of organic gases were successfully identified using I A /I R values. The most distinct feature of this method is that it allows the user to obtain many more luminescent signals from the sensing materials than common methods. It does so by allowing different flow channels of the analyte gas. This simple method here was used to discriminate different species, homologous series, and isomers in different concentrations. This method could be applied to chemical sensing arrays to increase the discrimination ability or decrease the number of sensing units required. Exposure to VOCs may cause serious effects, such as a wide range of sensory irritation and acute or chronic diseases. 1 The toxicities inherent in these compounds derived from various specific chemical reactivities can affect many different systems within living organisms. 2,3 Worse, accidental releases of harmful gases have caused major accidents all over the world. All of these issues have created an urgent need for simple methods of detecting VOCs in real time, not only from a security perspective but also industrial chemical workplaces. Sensor technology provides a versatile approach to chemical analysis. During the past several decades, intensive research has been done to develop the bioinspired artificial olfactory systems, known as electronic noses or artificial noses. These mechanisms involve a set of partially selective chemical sensors in conjunction with pattern recognition techniques for the discrimination and quantification of both simple and complex gas mixtures. 4 6 Upon exposure to analytes, the chemical sensors generated response patterns characteristic of those analytes. The response patterns were used to train a pattern recognition program, and unknown analytes were detected upon subsequent exposure. To date, many types of electronic noses have been used in the measurement of various gases, and many dissolved chemical species have been reported using measures, such as sensor arrays based on amperometric, 7 electrochemical, 8 optical, 9 11 and chromic properties 12 and surface acoustic waves. 13 However, there are several important practical issues, such as ways to decrease the number of sensors required to diminish the need for frequent calibration and improve reproducibility. 14 The most intractable problem is that the response patterns of signals from different individual sensors are not always similar across different concentrations, rendering signal processing complicated and difficult to settle. 15 Zellers et al. demonstrated that the ability to recognize a gas from the sensor array response pattern decreases with decreasing gas concentration. 16 It is very important to discriminate gaseous species in different concentrations (or amounts), especially when the gas concentration changes during measurement. In addition, multiple sensing units are not beneficial to the stability of the instrument. Alterations in the characteristics of the sensors unit over time can affect the final recognition results. In this way, a sensor system that uses as few sensing units as possible is extraordinarily needed. We recently developed a novel method for identifying compounds by luminescent response profiles on a CTL-based sensor. 17 The sensing process of this method was conducted in a close reaction cell, allowing the reactants and intermediates to Received: January 20, 2013 Accepted: March 13, 2013 Published: March 13, American Chemical Society 3802

2 become oxidized over the catalyst. This allowed the production of luminescent response profiles, which exhibited multiple peaks and characteristics of analytes. Unlike the traditional CTL-based sensor approach, in which the sensing process was conducted in an airstream flow reaction cell, the exhaust gas was released directly into the atmosphere. Therefore the CTL reaction was very fast and the emission period was relatively transitory which led to a CTL response profile that usually only has a single peak. 17 The multipeaked luminescent response profiles of gases mentioned above varied by concentration, which limits the application of this method. This phenomenon inspired the design of a powerful CTL sensor for discriminating gases that could be used to extract useful information from exhaust gas. In the present work, an ingenious system based on the use of exhaust gas was created for the detection and discrimination of VOCs in the environment. As shown in Figure 1, the gas sensor Figure 1. Simultaneous detection of I A and I R. was made of nanoparticles, which were sintered onto two cylindrical ceramic heaters (inner diameter = 4 mm, length = 8 cm, Ningbo Electric Iron Factory, Ningbo, China) to form a catalyst layer about 0.3 mm thick. Nano-MgO and SrCO 3 were used as sensing materials. The two ceramic heaters containing the sensing material were placed in two quartz tubes (diameter = 1 cm, length = 10 cm) to produce the sensor system. The analyte was delivered by the air carrier gas (supplied by a pump, Beijing Zhongxing Huili Co. Ltd., Beijing, China), which flowed through the first sensing element surface. The analyte was immediately oxidized. The CTL signal (I A, peak intensity) was measured using the photomultiplier in the BPCL Ultra Weak Chemiluminescence Analyzer (Institute of Biophysics, Academia Sinica, Beijing, China). The exhaust gas of the analyte from the first quartz tube was introduced into the second quartz tube to continue oxidization for producing secondary CTL signal (I R, peak intensity). The two quartz tubes were connected by a polytetrafluoroethylene (PTFE) tube (20 m 0.4 mm 0.3 mm), which was about 20 m in length, ensuring that the two signal peaks would not overlap. In the first experiment, nano-mgo was sintered on the two ceramic heaters (here called the Mgo-MgO sensor system). Different concentrations of four kinds of alcohols and aldehydes were examined to demonstrate the ability of this method to discriminate compounds with similar structures. The responses of the CTL intensity detected by this system are shown in Figure 2. The I A /I R values of different analytes are diverse and differentiable. For example, the I A /I R for methyl alcohol is 2.47 (I A is stronger than I R ), and 1.00 for ethanol (I A is equal to the I R ), and 0.85 for acetaldehyde (I A is weaker than I R ). The I A /I R ratio can be used to identify these compounds. I A /I R remained constant for a given gas under a given set of reaction conditions, independent of concentration within a wide range. This allows the researcher to discriminate various compounds at different concentrations. The next experiment involved replacing the second MgO with SrCO 3 (MgO-SrCO 3 system). The value of I A /I R was also characteristic of these alcohols and aldehydes (Figure S1, Supporting Information). To further increase the ability of this method to distinguish between different gases, we studied the influence of different combinations of materials on the I A /I R values of analytes with varied chemical functionality. MgO and SrCO 3 were used to construct different sensing systems (MgO-MgO, MgO-SrCO 3, SrCO 3 -MgO, and SrCO 3 -SrCO 3 ) and a total of 11 kinds of compounds, including alkane (cyclohexane and n-hexane), ketone (acetone), lipid (ethyl acetate and vinyl acetate), organic acid (acetic acid), ether (ether, butyl ether, and tetrahydrofuran), and its derivatives (2-ethoxyethanol, ethylene glycol monomethyl ether, EGME for short) were examined. As illustrated in Figure 3, the same sensing system exhibited different properties upon exposure to different vapors. In the SrCO 3 -MgO system, the highest value of I A /I R was 7.59 for acetone. The medium value was 4.16 for butyl ether, and the lowest value was 2.43 for ethyl acetate. Similarly, the values of I A /I R on different sensing elements could differ for the same vapor. For example, with the MgO-MgO, MgO-SrCO 3, SrCO 3 - MgO, and SrCO 3 -SrCO 3 systems, the values of I A /I R for n- hexane were found to be 1.47, 0.73, 4.12, and 1.71, respectively, but the values for cyclohexane were 4.57, 0.22, 2.84, and 3.53, respectively (Table S3, Supporting Information). These facts mean that the value of I A /I R is not only affected by the kind of nanoparticle used but also by the sequence of nanoparticles. The ability of the system to identify the analytes was greatly increased by the use of the 4-group value of I A /I R instead of the 1-group value of I A /I R. By reversing the flow direction of the analyte gas, we obtained 4 group values of I A /I R from the two sensing materials in the A-B system. The signals from A-A and B-B combinations were obtained by reversing the flow direction of the exhaust gas after the analyte gas passed through A or B. The signals from A- B and B-A in combination were found by reversing the flow direction of the analyte gas. In this way, n (n 2) kinds of sensing materials have A n 2 + n = n 2 groups of I A /I R (A n 2 here refers to the arbitrary permutation of two kinds of materials chosen from n different kinds of materials), while only n CTL signals for common method without making use of exhaust gas. It demonstrates that this method offers multidimensional information useful in the discrimination of analytes and that it may be suitable for the development of limited multichannel sensor arrays that can be used to detect and recognize both simple and complex gas mixtures. This sensor system can also be used to quantify a given analyte by its CTL emission intensity. Two peaks were detected in the CTL response profile using this system, and the intensities of both peaks showed linear relationships with analyte concentration. The MgO-MgO sensor system was used 3803

3 Figure 2. CTL intensity for alcohols and aldehydes as detected by the MgO-MgO sensor system (working temperature, 250 C; detection wavelength, 400 nm; airflow rate, 280 ml min 1 ). to detect alcohols, and the calibration curves between the intensity of I A (or I R ) and absolute concentration are shown in Figure 4. We can usually choose one calibration curve for quantitative analysis (usually the more sensitive one). In some cases, using two calibration curves can improve the reliability of the quantitative results. The limit of detection (LOD) of the new method depends on both I A and I R, and the intensities of both must be strong enough to allow detection. The weaker of the two is always the limiting factor. In other words, LOD depends on the standard curve with the gentler slope. This is discussed in the Supporting Information. To explore the response mechanism of the analyte in this sensor system, the exhaust gases produced by the catalytic oxidation of ethanol on the surface of the nano-mgo from the first and the second sensing materials were detected by gas chromatography. Results are shown in Figure 5. Ethanol was oxidized to ethylene and acetaldehyde on both the first and second MgO surfaces. Compared to the first MgO, no new products were detected from the second MgO. Only the amounts of products were different. These results indicate that undecomposed reactant and reaction products from the exhaust gases can be further oxidized to generate CTL signals. The exhaust gas from the CTL reaction can be used to extract useful information. Because different analyte and its reaction products have different structural characteristics, the CTLs luminescent efficiencies and reaction rates were found to differ on the same sensing material, causing different I A /I R ratios for different analytes. 10,18 The theoretical express of I A /I R is given in the Supporting Information. We investigated the influences of working temperature, detection wavelength, airflow rate, and humidity on intensity of 3804

4 Figure 3. Value of I A /I R for 11 kinds of compounds detected by the MgO-MgO, MgO-SrCO 3, SrCO 3 -MgO, SrCO 3 -SrCO 3 sensor system with an average of three parallel measurements (working temperature, 250 C; detection wavelength, 400 nm; airflow rate, 280 ml min 1 ; amount of each gas, 3.9 μg). CTL and on I A /I R. The results showed that humidity has little effect on the function of the present sensor system, which is also in accordance with previous reports. 10,18 Details are given in the Supporting Information. CONCLUSION In conclusion, the exhaust gas produced by the CTL reaction provides a great deal of information that can be used in sensing analysis. On the basis of this idea, we developed an ingenious system for continuous measurement of the CTL signals of analyte and its products. Qualitative analysis was conducted facilely using the I A /I R ratio and quantitatively analyzed using CTL intensity. The advantages of this proposed method are that it uses only a simple sensor system and a simple method to discriminate a wide range of species and that the differentiability remains the same across a wide concentration range. The I A /I R value is affected by the sequence of nanoparticles. Figure 5. GC chromatogram from the catalytic oxidation of ethanol on the first and second MgO surfaces. This provides researchers with a new way to extract multidimensional information from limited sensing elements. We consider this simple sensor system a first step in the development of sensor arrays for gas mixture recognition through chemometrics. Further work in this direction is under way in our lab. ASSOCIATED CONTENT *S Supporting Information Additional information as noted in text. This material is available free of charge via the Internet at AUTHOR INFORMATION Corresponding Author *Phone: Fax: caoxiaoan2003@yahoo.com.cn. Notes The authors declare no competing financial interest. Figure 4. Calibration curve between I A (or I R ) intensity and concentration detected using the MgO-MgO sensor system (working temperature, 250 C; detection wavelength, 400 nm; airflow rate, 280 ml min 1 ). 3805

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