Research Article Determining the Optimum Exposure and Recovery Periods for Efficient Operation of a QCM Based Elemental Mercury Vapor Sensor

Sensors Volume 215, Article ID 727432, 7 pages http://dx.doi.org/1.1155/215/727432 Research Article Determining the Optimum Exposure and Recovery Periods for Efficient Operation of a QCM Based Elemental Mercury Vapor Sensor K. M. Mohibul Kabir, 1 Samuel J. Ippolito, 1,2 Glenn I. Matthews, 2 S. Bee Abd Hamid, 3 Ylias M. Sabri, 1 and Suresh K. Bhargava 1 1 Centre for Advanced Materials & Industrial Chemistry (CAMIC), School of Applied Sciences, RMIT University, Melbourne, VIC 31, Australia 2 School of Electrical and Computer Engineering, RMIT University, Melbourne, VIC 31, Australia 3 Nanotechnology & Catalysis Research Center (NANOCAT), Institute of Postgraduate Studies (IPS), University of Malaya, 3rd Floor, Block A, 563 Kuala Lumpur, Malaysia Correspondence should be addressed to Ylias M. Sabri; ylias.sabri@rmit.edu.au and Suresh K. Bhargava; suresh.bhargava@rmit.edu.au Received 6 May 215; Revised 16 July 215; Accepted 21 July 215 Academic Editor: Nick Chaniotakis Copyright 215 K. M. Mohibul Kabir et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In recent years, mass based transducers such as quartz crystal microbalance (QCM) have gained huge interest as potential sensors for online detection of elemental mercury (Hg ) vapor from anthropogenic sources due to their high portability and robust nature enabling them to withstand harsh industrial environments. In this study, we determined the optimal Hg exposure and recovery times of a QCM based sensor for ensuring its efficient operation while monitoring low concentrations of Hg vapor (<4 ppb v ). The developed sensor was based on an AT-cut quartz substrate and utilized two gold (Au) films on either side of the substrate which functions as the electrodes and selective layer simultaneously. Given the temporal response mechanisms associated with mass based mercury sensors, the experiments involved the variation of Hg vapor exposure periods while keeping the recovery time constant following each exposure and vice versa. The results indicated that an optimum exposure and recovery periods of 3 and 9 minutes, respectively, can be utilized to acquire the highest response magnitudes and recovery rate towards a certain concentration of Hg vapor whilst keeping the time it takes to report an accurate reading by the sensor to a minimum level as required in real-world applications. 1. Introduction The rapid growth of industrialization in the last century has increased the emission of toxic metal species such as elemental mercury in the atmosphere [1 7]. It is of high importance to control the emission of these metal species from common industrial sources in order to reduce the advert effect they are having on the environment as well as human health. Recently, new and more stringent rules have been introduced by government and environmental bodies worldwide to limit the amount of mercury emitted from industrial processes. For example, the average daily mercury emission from cement kilns in Germany is proposed to be limited to 3.5 ppb v [8]. In order to comply with these regulations, efficient removal technologies need to be implemented on targeted industry sites. Furthermore, in order to evaluate the efficiency of these removal technologies, highly accurate and sensitive online mercury vapor sensor is required. In recent years, it has been shown that the mass based transducer such as quartz crystal microbalance (QCM) possesses several major advantages over other commonly used elemental mercury (Hg ) vapor measurement techniques, which are typically based on atomic absorption spectroscopy (AAS) and atomic fluorescence spectrometry (AFS), and

2 Sensors so forth [9 2]. The QCM based Hg vapor sensors were found to be highly portable and selective and they do not require sample pretreatment which make them highly suitable for online monitoring of Hg vapor within industrial applications [1]. Moreover, the design and the selective layer of QCM based sensors can be altered to achieve even higher sensitivity and selectivity towards low concentrations of Hg vapor. We recently reported that a QCM sensor based on gold nanospikes [21] can detect Hg vapor concentrations down to 2.5 ppb v, which is lower than the threshold mercury exposure limit of 5.6 ppb v set by world health organization [22].Duetotheirpotentialtobeusedasonlineorhand-held sensors, it is very important to study QCM based Hg vapor sensors extensively in order to achieve the best performance for Hg vapor detection. The schematic of a typical QCM based gas sensor is shown in Figure 1. The sensor is usually fabricated by depositing two electrodes on both sides of a suitable piezoelectric substrate (i.e., AT cut quartz). A bulk acoustic wave is generated upon the application of an electric potential on one of the electrodes [23 26]. The sensing film can be deposited on the electrode or the electrodes themselves can be made of a material which is selective to target analytes. Crystallographic characteristics and the thickness of the substrate and the electrodes determine the resonant frequency (f ) of the sensor. Any perturbation on the sensing film (which typically occurs through mass loading of targeted analytes on the sensing film) results in a shift of the resonant frequency (f ) of the sensor. This shift in f is highly dependent on the amount of analyte that interacts with the sensing film and can be related by the Sauerbrey equation (1) [27]: Δf = 2f 2 Δm, (1) A ρμ where Δf represents the shift in the resonant frequency, Δm isthechangeinthemassofthesensingsurface,a is the active area of the QCM electrodes, and ρ and μ are the crystal density and shear modulus of the piezoelectric crystal, respectively. It can be observed from (1) that the shift in f increases as the mass loading on the sensing film increases, which indicates that the shift in f is proportional to the concentration of the species being detected. In the current study, we focused on the Hg vapor detection application of a QCM based sensor. Therefore, extensive experimental and analytical approach was taken to determine the optimum exposure and recovery period to be used in order to efficiently monitor low concentration of Hg vapor using QCM based sensors. 2. Experimental 2.1. Sensor Fabrication and Quality Factor Determination. TheQCMbasedsensorwasfabricatedonanATcutquartz substrate having a diameter and thickness of 7.5 mm and 166 μm, respectively. 1 nm of Au layer on a 1 nm Titanium (Ti) adhesion layer was deposited on both sides of the quartz substrate to function as electrodes as well as the sensing Analytes Piezoelectric substrate Electrodes with sensing film Figure 1: Schematic diagram of a typical QCM based gas sensor. layer simultaneously. The deposition was performed using a Balzers e-beam (BAK 6) evaporator operating at 22 C. Both of the electrodes were circular shaped which were patterned by using a shadow mask. The diameter of the electrodes was 4.5 mm. A photograph of the fabricated sensor is shown in Figure 2. A network analyzer (Agilent E51A) was used to measure the frequency response and determine the quality factor of the fabricated sensor. Figure 2 shows the frequency response of the sensor at 2 khz span around the center frequency (9.9999 MHz). The quality factor of the sensor can be calculated using [28] energy stored Q=ω power loss, (2) where ω=2πf. The quality factor of the fabricated sensor wascalculatedas641(i.e.,>25), indicating the sensor is suitable for gas phase analysis. 2.2. Mercury Testing Setup. The Hg vapor concentration used in different experiments of this study was 365 ppb v. This particular concentration of Hg vapor was generated by setting the temperature of a NIST certified permeation tube (VICI) to 8 C. The Hg delivery system was also calibrated on site using a potassium permanganate (KMnO 4 ) trapping method. This involved capturing the generated Hg vapor steam within a train of impingers containing H 2 SO 4 /KMnO 4 and analyzing the solution by inductively coupled mass spectroscopy (ICP-MS) afterwards. This was done in order to ensure the concentration of Hg vapor was correct. The chamber which housed the QCM sensor had volume of 1 ml and was made of Teflon and stainless steel. The sensor recovery was a one-step process involving the exposure of the sensor toward dry nitrogen (N 2 ). A constant flowrateof2sccmandanoperatingtemperatureof3 C were maintained throughout the whole study. The operating temperature of the sensor chamber was kept constant using an active PID controller. Temperature fluctuations within ±.5 C were observed; however, this did not affect the sensing

Sensors 3 Au electrode 3 Q = 641 9.9999 MHz 4 Quartz substrate Magnitude (db) 5 3 db 6 9.99823 MHz 9.99979MHz Electrical Connection 7 9.998 9.999 1. Frequency (MHz) Figure 2: Photograph of the developed QCM based sensor and network analyzer response of the sensor at 2 khz span around the center frequency. Hg exposure Dry N 2 6 12 18 24 3 Time (min) Response (Hz) 5 1 6 12 18 24 3 Time (min) Figure 3: Structure of the test performed to determine the optimum Hg exposure time; sensor s dynamic response during the full test. Each exposure/recovery event s cycle was repeated 3 times before the next event started. result due to the high temperature stability of AT-cut quartz. A Maxtek RQCM was used for oscillation as well as to monitor resonant frequency of the sensor. 3. Results and Discussion 3.1. Optimum Hg Vapor Exposure Time. The performance of the developed Hg vapor sensor for different exposure times was investigated by exposing the sensor towards 365 ppb v of Hg vapor for a range of exposure period ranging from 1 to 12 minutes whilst keeping the recovery period constant at 6 minutes. The structure of the full test is shown in Figure 3. ItcanbeseenthataftereveryHg vapor exposure period dry N 2 was flushed to the sensor for a period of 6 minutes. This process was performed in order to desorb the Hg vapor molecules from the Au surface and thus allow the sensor to recover to its baseline frequency. Figure 3 shows the dynamic response of the sensor for the entire test. It can be observed that the Hg exposure resulted in a negative shift in the resonant frequency while the sensor was observed to return it to its baseline frequency during the recovery time. Figure 4 shows the sensor s response toward Hg vapor concentration of 365 ppb v foranexposuretimeof3and 12 minutes while the recovery period was kept constant at 6 minutes. The pulses shown were extracted from a set of continuous pulses which were measured using a fixed exposure and recovery time for at least 3 cycles. This was done in order to obtain stable performance of the sensors in the finalcycle.itcanbeobservedfromfigure 4 that the sensor response profile between the two exposure periods is different when considering the first 3-minute exposure period. This was mainly due to the different initial state between the two conditions presented (i.e., see Figure 3). This can be further justified from Figures 4 and 4(c). That is, it can be observed from Figure 4 that the last pulse of 3-minute exposure and 6-minute recovery period cycles has the same adsorption response profile as the first pulse of 4-minute exposure and 6-minute recovery period cycle due to the same initial state of the sensor. This is further confirmed in Figure 4(c) where it can be observed that the last pulse of 9- minute exposure and 6-minute recovery period responds similarly as 12-minute exposure and 6-minute recovery period. Figure 4(d) shows the response magnitudes of the

4 Sensors 5 Sensor response (Hz) 1 Sensor response (Hz) 1 15 2 2 1 2 3 Time (hrs) 3 min exposure-6 min recovery 12 min exposure-6 min recovery 25..4.8 1.2 1.6 Time (hrs) 3 min exposure-6 min recovery 4 min exposure-6 min recovery 24 5 Sensor response (Hz) 1 15 2 Response magnitude (Hz) 21 18 25 15 1 2 3 Time (hrs) 9 min exposure-6 min recovery 12 min exposure-6 min recovery (c) 3 6 9 12 Exposure time (min) (d) Figure 4: Sensor s dynamic response toward Hg vapor concentration of 365 ppb v exposed for 3 and 12 minutes; 3 and 4 minutes; and (c) 9 minutes and 12 minutes, all having a constant recovery time of 6 minutes. (d) Sensor s response magnitude towards 365 ppb v of Hg exposed for 1 to 12 minutes with a recovery time of 6 minutes. sensortowardthesamehg vapor concentration (365 ppb v ) for different exposure periods ranging from 1 to 12 minutes and a constant recovery period of 6 minutes. The response magnitudes of the last pulses for each Hg vapor exposure and recovery cycle were considered for analysis. The final pulse of each cycle was chosen as it allowed for the sensor to reach stability thereby resulting in desorption of the adsorbed Hg molecules from the Au surface and thus reducing the impact of a preceding pulse on the characterization of the following Hg exposure cycle. It can be observed from Figure 4(d) that the sensor s response magnitude increased rapidly when the Hg vapor exposure time was increased up to 3 minutes. However, it can also be observed that the sensor s response magnitudes did not vary significantly when the Hg vapor

Sensors 5 Hg exposure Dry N 2 6 12 18 Response (Hz) 2 4 6 12 18 Time (min) Time (min) Figure 5: Structure of the test performed to determine the optimum Hg recovery time; sensor s dynamic response during the full test. Each exposure/recovery event s cycle was repeated 3 times before the next event started. 5 7 min recovery 9 min recovery 12 min recovery 18 Sensor response (Hz) 1 15 Response magnitude (Hz) 15 2 3 min exposure 12..5 1. 1.5 2. Time (hrs) 3 6 9 12 15 Recovery time (min) Adsorption magnitude Desorption magnitude Figure 6: Sensor s dynamic response towards 365 ppb v of Hg vapor exposed for 3 minutes with desorption time of 7, 9, and 12 minutes and sensor s adsorption and desorption magnitude towards 3 minutes of Hg vapor exposure while the desorption period was varied between 1 and 12 minutes. The response magnitudes of the final cycle of each event are plotted. exposure time was increased beyond 3 minutes. This observation indicates that the processes of Hg-Au amalgamation and diffusion of Hg atoms into the Au surface are relatively high up to a period of 3 minutes; however, they are reduced significantly beyond the exposure period of 3 minutes due to the Au surface reaching saturation. Therefore, no significant increase in response magnitudes was observed when the Hg vapor was exposed for more than 3 minutes. The initial Hg sorption kinetics (Figure 4) isalsoobservedtohave changed(slowed)attheexposuretimeof12minutesdue to the higher content of the mercury that was already on the surface from the preceding two cycles of the same pulse (i.e., having 12-minute exposure and 6-minute recovery periods). 3.2. Optimum Hg Vapor Recovery Time. In order to determine the optimum recovery time of the QCM based Hg sensor, the sensor was exposed towards Hg vapor concentration of 365 ppb v for a period of 3 minutes while the recovery periodwasvariedwithinarangeof1to9minutes.aperiod of 3 minutes was chosen as the Hg vapor exposure time as it was determined to be the optimum time from the previous test (Section 3.1) at which the saturated response magnitude was achieved at a low turnaround time. The test structure for determining optimum recovery period for QCM based Hg vapor sensor is shown in Figure 5. The dynamic response of the sensor throughout the test can be observed from Figure 5. Itcanbeobservedthat each exposure and recovery cycle was repeated 3 times before the next cycle started. The sensor s dynamic response for 3 minutes exposure toward Hg vapor concentration of 365 ppb v employing three different recovery periods of 7, 9, and 12 minutes can be seen in Figure 6.Itcanbeobserved that the sensor exhibited a response magnitude of 17.5 Hz when Hg exposure and recovery periods were 3 and 7 minutes, respectively. It can also be observed that the sensor s response magnitude rose to 19 Hz when the recovery period was increased to 9 minutes while keeping the same Hg

6 Sensors vapor exposure period. Interestingly, the sensor s response magnitudes did not vary significantly when the recovery period was further increased to 12 minutes. A clearer view of sensor s adsorption and desorption magnitudes for the different recovery periods ranging from 1 to 12 minutes can be observed from Figure 6. Here, it should be noted that the sensor s desorption magnitudes were taken from the end of the recovery periods. It was interesting to observe that a 23Hz response magnitudewas observed for a 3-minute exposure and 6-minute recovery periods pulse (Figure 4(d)) while in Figure 6 a 18 Hz response was observed for the same exposure and recovery conditions. However, the difference arises from the preceding pulse cycles that were run for each condition. That is, the reduction in response magnitude for recovery period test was observed because the preceding recovery periods (i.e., 5 minutes) were not efficient enough for the sensor to release theadsorbedhg molecules from Au surface as opposed to the longer recovery period (6 minutes) used in all the pulses of the exposure test (Figure 3).Itcanbeseenfrom Figure 6 that the sensor s adsorption and desorption magnitudes increased significantly up to 9 minutes even though the Hg exposure period was kept constant at 3 minutes. It canalsobeobservedfromfigure 6 that while the sensor has high recovery efficiency for most of the recovery times tested the 9-minute recovery period showed to have more than 9% recovery efficiency while exhibiting maximum response magnitude towards Hg vapor. Overall, the results indicate that at least 9 minutes of recovery period is needed to acquire the highest possible response magnitudes as well as the recovery efficiency from the sensor while detecting low concentrations of Hg vapor without jeopardizing sensor s response time. Getting a higher response magnitude and the recovery efficiency is particularly important as it will enable the sensor to have high sensitivity and thereby result in the efficient detection of low concentrations of Hg vapor in industrial processes. 4. Conclusion The Hg vapor sensing performance of a QCM based sensor was investigated for different Hg vapor exposure and recovery periods. The developed sensor was based on an AT-cut quartz substrate containing thin Au-film electrodes on both sides. The sensor was tested towards Hg vapor concentration of 365 ppb v while the Hg vapor exposure and recovery periods were varied between 1 and 12 minutes. The overall results indicate that 3-minute Hg vapor exposure and 9- minute recovery periods can be utilized to achieve the highest response magnitudes and recovery efficiency from the sensor while keeping the turnaround time in a minimum level for real-world applications. Conflict of Interests The authors declare that there is no conflict of interests regarding the publication of this paper. Acknowledgments The authors acknowledge the Microelectronic and Materials Technology Centre (MMTC) at RMIT University for allowing the use of their facilities. Authors also acknowledge the Australian Research Council (ARC) for supporting this project and Samuel J. Ippolito acknowledges the ARC for APDI fellowship (LP12859). References [1] UNEP, Global Mercury Assessment 213: Sources, Emissions, Releases and Environmental Transport, UNEP Chemicals Branch, Geneva, Switzerland, 213. [2]L.B.Chakraborty,A.Qureshi,C.Vadenbo,andS.Hellweg, Anthropogenic mercury flows in india and impacts of emission controls, Environmental Science and Technology, vol. 47, no. 15, pp.815 8113,213. [3] L. D. Hylander and M. Meili, 5 years of mercury production: global annual inventory by region until 2 and associated emissions, Science of the Total Environment, vol. 34, no. 1 3, pp.13 27,23. [4] D. W. Boening, Ecological effects, transport, and fate of mercury: a general review, Chemosphere, vol. 4, no. 12, pp. 1335 1351, 2. [5] S.Liang,C.Zhang,Y.Wang,M.Xu,andW.Liu, Virtualatmospheric mercury emission network in China, Environmental Science and Technology,vol.48,no.5,pp.287 2815,214. [6] D. Jampaiah, K. M. Tur, S. J. Ippolito et al., Structural characterization and catalytic evaluation of transition and rare earth metal doped ceria-based solid solutions for elemental mercury oxidation, RSC Advances,vol.3,no.31,pp.12963 12974,213. [7]C.T.Driscoll,R.P.Mason,H.M.Chan,D.J.Jacob,andN. Pirrone, Mercury as a global pollutant: sources, pathways, and effects, Environmental Science and Technology, vol.47,no.1, pp. 4967 4983, 213. [8] K.M.Kabir,Y.M.Sabri,G.I.Matthews,L.A.Jones,S.J.Ippolito, and S. K. Bhargava, Selective detection of elemental mercury vapor using a surface acoustic wave (SAW) sensor, The Analyst, 215. [9]K.M.Kabir,Y.M.Sabri,G.I.Matthews,S.J.Ippolito,and S. K. Bhargava, Cross sensitivity effects of volatile organic compounds on a SAW-based elemental mercury vapor sensor, Sensors and Actuators B: Chemical,vol.212,pp.235 241,215. [1]Y.M.Sabri,S.J.Ippolito,A.J.Atanacio,V.Bansal,andS. K. Bhargava, Mercury vapor sensor enhancement by nanostructured gold deposited on nickel surfaces using galvanic replacement reactions, Materials Chemistry,vol.22, no.4,pp.21395 2144,212. [11] P. D. Selid, H. Xu, E. M. Collins, M. S. Face-Collins, and J. X. Zhao, Sensing mercury for biomedical and environmental monitoring, Sensors,vol.9,no. 7, pp.5446 5459,29. [12] N. Pirrone, W. Aas, S. Cinnirella et al., Toward the next generation of air quality monitoring: mercury, Atmospheric Environment, vol. 8, pp. 599 611, 213. [13] D. Martín-Yerga, M. B. González-García, and A. Costa-García, Electrochemical determination of mercury: a review, Talanta, vol. 116, pp. 191 114, 213. [14] S. K. Pandey, K.-H. Kim, and R. J. C. Brown, Measurement techniques for mercury species in ambient air, Trends in Analytical Chemistry,vol.3,no.6,pp.899 917,211.

Sensors 7 [15] M. Rex, F. E. Hernandez, and A. D. Campiglia, Pushing the limits of mercury sensors with gold nanorods, Analytical Chemistry,vol.78,no.2,pp.445 451,26. [16] B. Mazzolai, V. Mattoli, V. Raffa et al., A microfabricated physical sensor for atmospheric mercury monitoring, Sensors and Actuators A: Physical,vol.113,no.3,pp.282 287,24. [17] D. P. Ruys, J. F. Andrade, and O. M. Guimarães, Mercury detection in air using a coated piezoelectric sensor, Analytica Chimica Acta,vol.44,no.1,pp.95 1,2. [18]T.Thundat,E.A.Wachter,S.L.Sharp,andR.J.Warmack, Detection of mercury vapor using resonating microcantilevers, Applied Physics Letters,vol.66,pp.1695 1697,1995. [19] E. P. Scheide and J. K. Taylor, Piezoelectric sensor for mercury in air, Environmental Science and Technology, vol. 8, no. 13, pp. 197 199, 1974. [2] K. M. Kabir, Y. M. Sabri, A. E. Kandjani et al., Mercury sorption and desorption on gold: a comparative analysis of surface acoustic wave and quartz crystal microbalance-based sensors, Langmuir,215. [21] Y.M.Sabri,S.J.Ippolito,J.Tardio,V.Bansal,A.P.O Mullane, and S. K. Bhargava, Gold nanospikes based microsensor as a highly accurate mercury emission monitoring system, Scientific Reports, vol. 4, article 6741, 214. [22] T. P. McNicholas, K. Zhao, C. Yang et al., Sensitive detection of elemental mercury vapor by gold-nanoparticle-decorated carbon nanotube sensors, JournalofPhysicalChemistryC, vol. 115, no. 28, pp. 13927 13931, 211. [23] S. K. Vashist and P. Vashist, Recent advances in quartz crystal microbalance-based sensors, Sensors, vol. 211, Article ID 57145, 13 pages, 211. [24] K. Kanazawa and N.-J. Cho, Quartz crystal microbalance as a sensor to characterize macromolecular assembly dynamics, Sensors,vol.29,ArticleID824947,17pages,29. [25] M. Hoummady, A. Campitelli, and W. Wlodarski, Acoustic wave sensors: design, sensing mechanisms and applications, Smart Materials and Structures,vol.6,no.6,pp.647 657,1997. [26] D. Jr. Ballantine, R. M. White, S. J. Martin et al., Acoustic Wave Sensors: Theory, Design, & Physico-Chemical Applications, Academic Press, 1996. [27] G. Sauerbrey, Use of quartz vibration for weighing thin films on a microbalance, Zeitschriftfür Physik,vol.155,pp.26 212, 1959. [28] M. D. Ward and D. A. Buttry, In situ interfacial mass detection with piezoelectric transducers, Science, vol. 249, no. 4972, pp. 1 17, 199.

Rotating Machinery Engineering The Scientific World Journal Distributed Sensor Networks Sensors Control Science and Engineering Advances in Civil Engineering Submit your manuscripts at Electrical and Computer Engineering Robotics VLSI Design Advances in OptoElectronics Navigation and Observation Chemical Engineering Active and Passive Electronic Components Antennas and Propagation Aerospace Engineering Modelling & Simulation in Engineering Shock and Vibration Advances in Acoustics and Vibration