Mercury Detection in Real Industrial Flue Gas Using a

South32 Worsley Alumina Pty Ltd, Perth, Western Australia 6000, Australia. ∥ ProChemistry Consulting, Bunbury, Western Australia, Australia. Ind. En...
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Mercury Detection in Real Industrial Flue Gas Using a Nanostructured Quartz Crystal Microbalance Ylias M. Sabri,† K. M. Mohibul Kabir,† Eric Boom,§ Steven Rosenberg,∥ Samuel J. Ippolito,*,†,‡ and Suresh K. Bhargava*,† †

Centre for Advanced Materials & Industrial Chemistry (CAMIC), School of Science, RMIT University, Melbourne, VIC 3001, Australia ‡ School of Engineering, RMIT University, Melbourne, VIC 3001, Australia § South32 Worsley Alumina Pty Ltd, Perth, Western Australia 6000, Australia ∥ ProChemistry Consulting, Bunbury, Western Australia, Australia ABSTRACT: We present for the first time a nanostructured gold-based microsensor that can successfully detect elemental mercury (Hg0) vapor through a nonspectroscopic means, directly from a real industry effluent gas sample obtained from an alumina refinery. The developed sensor did not require any preconditioning of the sampled industrial gas in order to remove humidity content as is the case for laborious solid sorbent methods (i.e., Appendix K and Method 30B) certified by the United States Environmental Protection Agency (USEPA). The sensor was developed by electrodepositing gold (Au) nanostructures (nanospikes) directly on the electrodes of the humble quartz crystal microbalance (QCM) transducer. Significantly, despite attempting to introduce a memory effect into the sensor in order to replicate real world scenarios during testing, the developed sensor still reported the Hg0 vapor concentrations in the industrial gas to within ±8% of the certified solid sorbent analysis conducted at the time of obtaining the sample from the refinery stream. The developed microsensor technology introduced here can potentially be the first certified solid-state Hg0 vapor monitoring system that can be utilized as part of Hg0 control and removal processes in industry due to its exceptionally low susceptibility to cross-sensitivity, high accuracy, and ability to operate with untreated “real-world” sample gas. very low concentrations of Hg0 vapor (0.64 ng/m3), however fail to accurately measure Hg0 vapor without sample preconditioning when interfering gas species (i.e., humidity (H2O), ammonia (NH3), acetaldehyde (MeCHO), noncondensable gases (i.e., SO2, NO2, H2O, O3), volatile organic compounds (VOCs) such as benzene, toluene, acetone, etc.) are present in the sample,12,13 thus dramatically limiting their applicability to only certain industrial process. For situations where the coexisting gases exist, industries are forced to use other US-EPA approved Hg detection methods which involve laborious sampling methods such as Method 30B, Appendix K, or Ontario Hydro methods. The main disadvantages of the latter methods include the requirement for either employing or outsourcing expert personnel and following predefined sample gas precondition protocols onsite and then undertaking either wet chemical or dry gas analytical processes at an external

1. INTRODUCTION The rapid growth of industrialization has significantly increased the emission of toxic and hazardous metals and their associated compounds into the environment.1−4 Among these elements, mercury (Hg), especially when emitted in its gaseous elemental (Hg0) form, is getting much attention because of its adverse effect on environmental and human health.5−10 Several common industries (i.e., coal fired power plant, cement, alumina refinery, etc.) are responsible for the major portion of Hg0 emitted into the atmosphere and are continuously being pressed by environmental and government bodies to implement efficient Hg removal technologies within their processes.1,3 The effectiveness of implemented Hg removal technologies within an industrial process can be enhanced by employing accurate online Hg detection systems as feedback to the removal technologies.11 However, the lack of such detection technology is a major constraint faced by industries today. Most of the techniques currently approved by United States Environmental Protection Agency (US-EPA) and being used for detection of Hg0 vapor (sometimes as a continuous emission monitor (CEM)) are based on spectroscopy techniques (i.e., AAS, AFS, etc.). These techniques can measure © 2016 American Chemical Society

Received: Revised: Accepted: Published: 7661

April 26, 2016 June 24, 2016 June 27, 2016 June 27, 2016 DOI: 10.1021/acs.iecr.6b01628 Ind. Eng. Chem. Res. 2016, 55, 7661−7668

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Industrial & Engineering Chemistry Research

Figure 1. Schematic representation of (a) electrodeposition process and (b) AuNS-QCM sensor.

selectivity of the sensor. This was a clear indication that these transducers can be developed into a cheap, accurate, and reliable Hg0 detection technology that is suitable for measuring mercury vapor in industrial gas streams where online spectroscopy instrumentation has been deemed unsuitable. In this study, we report for the first time the ability of a Au nanospikes-based QCM sensor (AuNS-QCM) to monitor Hg0 vapor from a “real” industrial effluents sample supplied from the digestion stack of an alumina refinery containing >20%v/v water among all other VOCs and gas species that are derived from a high temperature and pressurized ore digestion process. The results obtained from the developed sensor were also compared to a control Au thin-film based sensor (Au-QCM) which was tested simultaneously with AuNS-QCM. Furthermore, the sensor concentration outputs were compared with results obtained from the contractor that conducted the gas sampling process and preformed an independent analysis (using current US-EPA processes) of the collected sample gas.

offsite laboratory which typically results in a lengthy turnaround time of 2 weeks.14 In recent years, focus has been shifted toward developing mass-based microsensors such as quartz crystal microbalance (QCM) and surface acoustic wave (SAW) sensors,15 which are being considered as viable alternatives to spectroscopic-based Hg0 vapor analyzers due to their small size, portability and potential to be engineered as low maintenance CEMs. In addition, the characteristics of the transducer can be adapted to optimize the sensitivity and selectivity of the sensor toward Hg0 vapor by employing various design considerations (i.e., electrode dimensions, operating frequencies, etc.), deposition of different selective layers (i.e., nanomaterials designed to have high affinity toward the analyte), and operating conditions (i.e., temperatures, pressures, and flow rate conditions that enhance analyte-surface interactions). The most common approach in developing a QCM based Hg0 vapor sensor is to integrate noble metals on the electrodes’ surface. Among various noble metals, gold (Au)16 and silver (Ag)15 based sensitive layers are the most preferred due to their high affinity toward Hg. One of the major advantages of Au is that the film surface as well as Hg0 exposure and recovery times16 can be modified in order to obtain better Hg0 sensing performance. Recently,17 we have shown that the selectivity and the sensitivity of a 10 MHz QCM-based sensor toward Hg0 vapor can be significantly increased by depositing gold (Au) nanostructures (nanospikes) on the electrode surface and operating under simulated industrial conditions (i.e., operating temperature of 101 °C and presence of various interfering gases). The Au nanospikes can also be deposited on the nanosphere monolayer to form close packed Au nanourchins in order to obtain enhanced sensitivity toward Hg0 vapor, as demonstrated in our follow up study.18 Analysis showed that the increase in sensitivity and selectivity of the Au nanospikes-based QCM sensor toward Hg0 vapor was due to not only the increased surface area but also to the formation of atomic scale features on the sensing surface.17 That is, the formation of defect sites on the Au surface is believed to play a major role toward the sensor’s sensitivity as Hg0 atoms tend to favor these sites during the adsorption/ amalgamation process, which also results in the increased

2. EXPERIMENTAL SECTION 2.1. Device Operation and Fabrication. The operating mechanism of a QCM sensor is based on the propagation of bulk acoustic waves16,19,20 into the depth of a piezoelectric substrate such as AT cut quartz. The bulk wave is generated by applying a voltage on each of the two electrodes deposited on the either side of the piezoelectric substrate. The resonant frequency (f 0) of the sensor is dependent on the crystallographic properties and the thickness of the substrate. To detect Hg0 vapor, a selective material (typically Au) is used for patterning one or both of the counter-opposing electrode surfaces. When Hg0 vapor molecules interact with the selective surface deposited on the electrodes, the f 0 of the sensor is changed. The change in the f 0 is caused by the change in thickness and effective mass density of the selective electrodes, which can be expressed by the Sauerbrey equation21 (eq 1), Δf = −

2f0 2 A ρμ

Δm (1)

In this equation, Δf is the resonant frequency shift, Δm represents the mass change on the electrode surface, A 7662

DOI: 10.1021/acs.iecr.6b01628 Ind. Eng. Chem. Res. 2016, 55, 7661−7668

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Industrial & Engineering Chemistry Research

Figure 2. Block diagram for the experimental setup used for Hg0 vapor detection from industrial sample cylinders. It should be noted that the sample cylinder was isolated from the industrial stack and couriered to the sensor laboratory before being connected to the sensor cell setup shown on the right side of the sample cylinder. The tests were conducted ∼2 weeks after the cylinders were filled on site and transported to the laboratory. The industrial setup used on site to sample the gas into the sample cylinders as well as the laboratory setups are separated in the schematic by the dashed line.

±0.1 °C in order to obtain the concentrations of generated Hg0 vapor in a repeatable (±0.05 mg/m3) manner. Prior to the gas entering the sensor chamber, a potassium permanganate (KMnO4) trapping system was utilized to capture the Hg0 vapor. The captured vapor was then analyzed using inductively coupled plasma mass spectroscopy (ICP-MS) to validate the generated Hg0 vapor concentrations. The QCM sensors were placed in a secured cell having ∼100 mL volume (referred to as the sensor chamber) and an Agilent (53131A) frequency counter was used to measure the resonant frequency (M) of the QCMs. The frequency counter possessed a resolution of ±0.1 Hz over an integration period of 4 s. The developed sensors were exposed toward Hg0 vapor for a period of 1 h followed by a dry nitrogen (N2) gas purge for another 1 h period, which allowed the sensor to regenerate in between the Hg0 exposure period. The combined 2 h period (1 h Hg0 exposure and 1 h dry N2 purging) is referred as a “pulse” throughout the entire manuscript. A flow rate of 100 sccm was kept constant during the tests related to calibration curve while a temperature of 105 °C was maintained. The alumina refinery gas sample was collected in three stainless steel cylinders (with PTFE coating on the inside) having a volume of 3.75 L to a pressure of 100 psi at 25 °C. The process gas was also sampled for its mercury content by certified environmental analysis contractors (CEAC) in between each cylinder filling process using the EPA dry sorbent method (i.e., Appendix K and EPA method 30B) following the removal of the 20.1% v/v water content. Each cylinder filling process and CEAC testing took a period of 15− 20 min, therefore the Hg0 vapor concentrations within the sample cylinders was expected to be very similar to that reported by CEAC with only a small difference due to the fluctuating stream condition in the refinery process at the time of the sampling exercise. The sample cylinders were then couriered and arrived at our research laboratory approximately 2 weeks following the sampling procedure. The sample cylinders were heated to 120 °C (using a specially fitted heat

represents the QCM electrodes’ active area, μ and ρ are the shear modulus and crystal density of the piezoelectric substrate, respectively. The Au-QCM was fabricated by depositing 10 nm titanium (Ti) adhesion layer and 100 nm Au sensing layer on both sides of a 166 μm thick quartz (AT-cut) substrate with a diameter of 7.5 mm placed inside a shadow mask that allowed only 4.5 mm diameter electrodes to be formed. The deposition was carried out using the electron beam evaporation method (Balzers ebeam evaporator, BAK 600 operating at 22 °C). The fabricated QCM had a resonant frequency of ∼10 MHz. The full fabrication details of electrodeposited Au nanostructures on the AuNS-QCM can be found elsewhere.17 Briefly, electrodeposition was utilized to modify the as-deposited Au surface of an Au-QCM. A CH Instruments (CHI 760C) electrochemical analyzer was used to perform the electrodeposition process. The deposition cell was designed to obtain a reproducible position of the working (Au-QCM), reference (graphite), and auxiliary (Ag/AgCl 3 M KCl) electrodes as well as having a nitrogen purge inlet. The electrolyte solution used was a mixture of lead(II) acetate trihydrate (0.177 g/L) and hydrogen tetrachloroaurate (III) trihydrate (2.718 g/L) (Sigma-Aldrich, Australia). The deposition was performed for 600 s while the potential was set constant at 0.05 V. The schematic representation of the deposition process is shown in Figure 1. The surface of the AuNS-QCM was characterized using a scanning electron microscopy (SEM) before and after Hg0 vapor detection from industrial gas provided by South32 Worsley Alumina. A Nova nano-SEM, operating at 10 kV, was utilized to perform surface characterization of the AuNS-QCM electrodes. 2.2. Experimental Setup for Hg0 Vapor Testing. Initially, the sensors were tested toward different concentrations of Hg0 vapor ranging from 1.02 to 5.78 mg/m3 in order to obtain the calibration curve. These Hg0 vapor concentrations were generated by using a permeation tube (VICI, TX, USA), for which the temperature of the tube was controlled to within 7663

DOI: 10.1021/acs.iecr.6b01628 Ind. Eng. Chem. Res. 2016, 55, 7661−7668

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Industrial & Engineering Chemistry Research

Figure 3. (a) Dynamic response of the AuNS-QCM sensor for different concentrations of Hg0 vapor ranging from 0.72 to 5.78 mg/m3 while operating at 105 °C. Langmuir curve fit on the (b) sorption and (c) desorption calibration curve of the Au-QCM and AuNS-QCM sensors. These tests were performed prior to testing the first industrial flue sample cylinder.

performance in-between each of the tests. Figure 3a shows the AuNS-QCM sensor’s dynamic response toward various concentrations of Hg0 vapor prior to testing the first sample cylinder. As expected, the sensor’s response magnitude increased with increasing concentration of exposed Hg0 vapor. The calibration curves were then generated using the sensors’ sorption/desorption response magnitudes for each Hg0 vapor concentration tested. Figure 3 panels b and c show the sorption and desorption calibration curves, respectively of both Au-QCM and AuNS-QCM sensors. It can be observed that the calibration curve of each sensor fit well with the Langmuir extension isotherm where the sensors’ sorption and desorption magnitudes can be related to the exposed Hg0 vapor concentration (eq 2). It can also be observed that the AuNSQCM showed up-to 3.5 times higher sorption and desorption magnitudes for each Hg0 vapor concentration tested when compared to the Au-QCM sensor.

jacket) for a period of 100 h prior to any experiments in order to ensure all species were suspended in the gaseous form. Thereafter, the sample cylinder gas (which contained the 20.1% v/v water content reported by CEAC) was tested with the developed QCM-based mercury vapor sensors following a 1:1 dilution of the sampled gas mixture (50 sccm) with dry nitrogen (50 sccm) at a total flow rate of 100 sccm. Specially designed industrial mass flow controller (MFC) was purchased from John Morris Scientific (model no. MKS PR4000B) and used to transfer the industrial gas from the cylinder and into the sensor chamber through heated pipes, gauges, and MFC, which were all maintained at 120 °C using heat tapes and temperature controllers. The desired flow rate settings of the MFC (calibrated with dry N2 gas) that was used to transfer the industrial samples into the sensor cell was determined using the following steps. First the loss in pressure over a 30 min period was determined when the MFC was set at a flow rate of 50 sccm dry N2. Then, the actual flow rate was determined using the ideal gas law on the pressure loss data, so that a 50 sccm equivalent flow rate could be achieved as required by the sample gas. A block diagram of the experimental setup is represented in Figure 2. As can be appreciated from the discussion above, the industrial gas sampling and QCM testing procedures were performed in such a way as to be as closely aligned with potential online system setup where no sample preconditioning is utilized. The experimental setup shown in Figure 2 can easily be implemented on any industrial stack in order to obtain online mercury monitoring apparatus using the nonspectroscopic, transducer-based Hg0 vapor sensor developed in this study.

Δf =

ab[Hg]c (1 + b[Hg]c )

(2)

In this equation, ΔΔf is the QCM response magnitude, [Hg] is exposed Hg0 vapor concentrations, a is the maximum response magnitude the sensor can reach before saturation, b is the range of concentration that can be detected before the sensor reaches saturation, and c is a constant dependent on the material property of the sensitive layer. A total of three cylinders (each sampled on site at the alumina refinery) were tested as delivered, without any pretreatment processes such as removal of humidity content and the organic compounds from the sample or digestion of any sorbents as is usually performed by onsite gas sampling contractors. For example, the independent analysis performed by the CEAC involved removal of the water content, undergoing sorption of the dry gas onto a solid sorbent, and conducting their analysis of the solid sorbent to determine the Hg0 concentration in the refinery stream at their accredited sample gas analysis laboratory. On the delivery of the Teflon lined stainless steel cylinders (approximately 2 weeks after the sampling was performed) the contents of cylinder 1 were exposed to both the Au-QCM and AuNS QCM sensors. However, first the sensors were exposed to three (idle) pulses containing 1.11 mg/m3 of Hg0 vapor balanced in N2 generated by the permeation tube prior to introducing the sample

3. RESULTS AND DISCUSSION 3.1. Sensor Calibration and Sample Cylinders Testing. To obtain the sorption and desorption calibration curves, the developed sensors were exposed toward six different concentrations of Hg0 vapor; 0.72, 1.15, 1.50, 2.28, 3.22, and 5.78 mg/ m3 ± 0.05 mg/m3. An operating temperature of 105 °C was maintained in the sensor cell. The sorption and desorption calibration curves of the Au-QCM and AuNS-QCM were obtained before testing each of the three sample cylinders, in order to ensure the better accuracy of the reported Hg0 vapor concentrations as well as to determine if the sample cylinder gas caused any negative effect on the sensor response 7664

DOI: 10.1021/acs.iecr.6b01628 Ind. Eng. Chem. Res. 2016, 55, 7661−7668

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Figure 4. Au-QCM and AuNS-QCM sensors’ dynamic response toward six pulses of 1.11 mg/m3 Hg0 vapor and a pulse from the (a) first sample cylinder and (b) second sample cylinder in the middle (yellow shaded area) and (c) AuNS-QCM sensor’s dynamic response toward six pulses each of 1.11, 1.50, and 2.28 mg/m3 Hg0 vapor concentration with pulse from third sample cylinder in the middle (yellow shaded area). (d) Sorption and (e) desorption response magnitudes of the AuNS-QCM sensor toward six pulses each of 1.11, 1.50, and 2.28 mg/m3 Hg0 vapor concentration with a pulse from the third sample cylinder in the middle.

m3. Overall the AuNS-QCM sensor was in better agreement with the CEAC data, which was to be expected. However, it should be noted that CEAC data was derived from a sample that underwent gas pretreatment (i.e., water content removal), multistep sampling processes, and offsite analytical procedures before being able to report the Hg0 content 2 weeks later. Additionally, mercury vapor absorption on the new piping and heated MFC rig used to deliver the sample cylinder gas to the sensor chamber may have contributed to the lower value reported by the AuNS-QCM sensor when compared to the CEAC value, as the fresh surfaces inside the system would have absorbed (and have effectively removed) some of the Hg0 from the sample gas. The second sample cylinder was tested using a similar protocol. Figure 4b shows the dynamic response of the QCM based mercury sensors toward seven pulses of where the sample cylinder 2 gas was introduced in the fourth pulse of the 1.11 mg/m3 Hg0 pulse sequence. It was found that the Au-QCM and AuNS-QCM reported a Hg0 vapor concentration of 4.27 and 2.99 mg/m3, respectively, while a Hg0 vapor concentration of 3.18 mg/m3 was reported by CEAC. This was a clear indication that the AuNS-QCM could report Hg0 vapor concentrations in industrial gas sample in a repeatable and accurate manner once the internal plumbing of the system was preconditioned with Hg0 vapor from the first sample cylinder. This was the reason that a large portion of gas from cylinder 1

cylinder gas in the sensor cell (active detection pulse). Figure 4a shows the dynamic response of both sensors toward a sequence of seven pulses in which the middle pulse (highlighted yellow) is from sample cylinder 1 where a 1:1 dilution factor was used (i.e., 50 sccm sample gas added to 50 sccm dry N2). As can be seen from Figure 4a, each sensor was observed to exhibit a response magnitude slightly higher than the response magnitude caused by the surrounding 1.11 mg/m3 Hg0 pulses, thus indicating that cylinder 1 contained a mercury concentration higher than 2.22 mg/m3 once the 1:1 dilution factor is accounted for. From the prior established calibration curves of each sensor it was possible to independently calculate the reported Hg0 vapor concentration from Au-QCM and AuNS-QCM sensors from their respective desorption calibration curves (using eq 1) and compare them with the concentration that was reported by CEAC. The desorption data were used in this study for analysis even though the Hg0 vapor concentration derived from the QCM sorption calibration curves were acceptable. This was due to the observations made in our previous study, which indicated that more accurate reading can be produced when using the desorption data from QCM devices employed for Hg0 vapor sensing applications.17 The Hg0 vapor concentrations in cylinder 1 reported by Au-QCM and AuNS-QCM were 3.32 and 2.37 mg/m3, respectively, whereas the Hg0 vapor concentration in cylinder 1 reported by CEAC was 2.70 mg/ 7665

DOI: 10.1021/acs.iecr.6b01628 Ind. Eng. Chem. Res. 2016, 55, 7661−7668

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Industrial & Engineering Chemistry Research was used to precondition the pipes in the sample delivery rig while most of the gas from cylinder 2 was utilized for analytical experiments to estimate the gas flow constant for the industrial MFC system used to deliver the industrial gas into the chamber cell holding the sensors. The third industrial gas cylinder (cylinder 3) was used to test the AuNS-QCMs under three different testing conditions to determine its memory effect performance. Such a test aims to identify unwanted artifacts between sensing events where the result of the previous sensing event can influence the result of the current sensing event. The testing process involved altering the Hg0 concentration of the three idle sensor pulses surrounding pulses containing the sample cylinder gas in three separate seven pulse tests. The Hg concentrations were selected to be just below the expected sample cylinder concentration, the same as the sample cylinder concentration, and just above the expected sample cylinder concentration that would be present in the sensing chamber after a 1:1 dilution factor was taken into consideration. Therefore, if the sensor did suffer from a memory effect issue, the sensor would report different Hg0 concentration levels for each of the three separate tests even though the sample cylinder gas can be regarded as having a constant Hg0 vapor concentration. Figure 4c shows the overlaid dynamic response curves of the AuNS-QCM from the three tests performed with the third sample gas cylinder. As can be seen, the AuNS-QCM sensor gave approximately the same response profile toward the sample cylinder pulse for all three tests, regardless of the concentration of the surrounding pulses were. A small memory effect can be seen in the green curve where the surrounding pulses contained a Hg0 vapor concentration of 2.28 mg/m3, which is ∼35% higher than the expected concentration of the diluted Hg0 vapor concentration of the sample cylinder gas which was ∼1.5 mg/m3. As can be seen in Figure 4d, a slight decrease in the absorption response magnitude was observed as a result of the higher Hg concentration exposed to the developed AuNS-QCM sensor prior to the sample gas being introduced. Similarly, a slightly larger desorption magnitude was observed relative to the other 2 test sequences where the surrounding pulses had Hg0 vapor concentrations of 1.11 mg/m3, which was less than the 1:1 diluted sample cylinder gas (Figure 4e). Even in a situation where a memory effect was purposely introduced, it was found the AuNS-QCM sensor reported the cylinder Hg0 vapor concentrations (2.92, 3.03, and 3.15 mg/m3 when the surrounding pulses were 1.11, 1.50, and 2.28 mg/m3, respectively) much closer to the CEAC reported concentration (3.18 mg/m3) than when compared to the concentration reported by the control Au-QCM sensor, which reported 4.71, 3.97, and 4.67 mg/m3 when the surrounding pulses were 1.11, 1.50, and 2.28 mg/m3, respectively. It can be seen that the control Au-QCM exhibited up to 48% deviation in reported Hg0 vapor concentration when compared to CEAC reported concentration, whereas the AuNS-QCM sensor showed a maximum deviation of only 8% in reported Hg0 vapor concentration from the one reported by CEAC. The overall Hg0 vapor concentrations reported by both CEAC and the developed AuNS-QCM sensor for all three sample cylinders is summarized in Table 1. The data indicate that the AuNS-QCM sensor is highly accurate in detecting the Hg0 vapor concentration from industrial flue gas and can be used as part of process control, Hg0 vapor removal technology feedback device, and/or environmental emission monitoring system.

Table 1. Concentrations of Sample Cylinders

cylinder 1 cylinder 2 cylinder 3 sequence 1 (1.11 mg/m3) sequence 2 (1.50 mg/m3) sequence 3 (2.28 mg/m3)

Au-ctrl QCM (mg/m3)

Au-NS QCM (mg/m3)

CEAC (mg/m3)

3.32 4.27

2.37 2.99

2.70 3.18

4.71

2.92

3.18

3.97

3.03

4.67

3.15

There were several factors which have helped the developed AuNS-QCM sensor to be selective toward Hg0 vapor in the presence of industrial relevant gases including the higher number defect sites on the sensing surface compared to a AuQCM sensor. As discussed in section 1, Au defect sites are preferred by Hg0 atoms during the adsorption/amalgamation process. Furthermore, gas molecules’ kinetic energy, vapor pressure, and gas−solid collision rates of the interfering gas species increase at relatively higher operating temperatures. However, utilizing 101 °C instead of room temperature in the experiments is thought to be advantageous as the interferent gas species would less likely adsorb on the surface due to the higher kinetic energy that needs to be overcome and the higher vapor pressure (tendency of gas species to stay in the gas phase rather than adsorb on a surface) even though the collision rate is increased with the sensor surface. This phenomena is also true for Hg0; however, the metal has a higher affinity toward Au nanospike structures on the sensor surface than the interferent organic and noncondensable gas species present in the industrial sample gas, which has resulted in the increased selectivity of the sensor. 3.2. Surface Characterization. Figure 5 panels a and b show the SEM images of the AuNS-QCM electrode surface before and after exposure to Hg0 vapor, respectively. It can be observed from Figure 5a that the surface is uniformly covered with Au nanospikes shaped structure having prismatic tapering ends. It was observed that the length of the nanospikes was around 1 μm while having base and tip thickness of ∼50 and ∼10 nm, respectively. As shown in Figure 5b, the Au nanospikes were found to be smoother after repeated exposure toward Hg0 vapor during the sample cylinder tests discussed above. It can be postulated that the heavy diffusion and amalgamation processes involved between Hg0 molecules and the Au nanospikes were responsible for this surface change to occur. From a sensing point of view, it is expected that the developed sensor would be calibrated every three to four weeks depending on the accuracy level expected; however, such calibration sequences (i.e., Figure 4) can easily be programmed and automated with these types of computer-controlled QCMbased sensor systems.

4. CONCLUSIONS A gold nanospikes-based QCM (AuNS-QCM) device was developed and tested for its Hg0 vapor detection performance in sampled industrial gas for the first time. The reported Hg0 vapor concentration from each of the three sample gas cylinders tested was accurate and within the 8% of the concentration reported by CEAC (EPA certified industrial sample gas analysis contractors). A nonmodified, control QCM counterpart with an Au thin film surface failed to report accurate concentrations 7666

DOI: 10.1021/acs.iecr.6b01628 Ind. Eng. Chem. Res. 2016, 55, 7661−7668

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Figure 5. SEM images of the AuNS-QCM sensor’s surface (a) before and (b) after exposure toward Hg0 vapor during the sample cylinder tests. (3) Burger Chakraborty, L.; Qureshi, A.; Vadenbo, C.; Hellweg, S. Anthropogenic mercury flows in India and impacts of emission controls. Environ. Sci. Technol. 2013, 47 (15), 8105−8113. (4) Dobbs, C.; Armanios, C.; McGuiness, L.; Bauer, G.; Ticehurst, P.; Lochore, J.; Irons, R.; Ryan, R.; Adamek, G. Mercury Emissions in the Bayer Process-An Overview. In 7th International Alumina Quality Workshop, Perth, Western Australia, 2005; pp 199−204. (5) US-EPA Mercury Study Report to Congress, Vol. I; United States Environmental Protection Agency: December, 1997. (6) US-EPA Mercury Study Report to Congress, Vol. II; United States Environmental Protection Agency: December, 1997. (7) Dawson, A. J.; Iliopoulou, A.; Gonzalez, S. Elemental mercury toxicity due to aspiration following intentional massive ingestion. Acute Med. 2013, 12 (2), 93−95. (8) Carman, K. B.; Tutkun, E.; Yilmaz, H.; Dilber, C.; Dalkiran, T.; Cakir, B.; Arslantas, D.; Cesaretli, Y.; Aykanat, S. A. Acute mercury poisoning among children in two provinces of Turkey. Eur. J. Pediatr. 2013, 172 (6), 821−827. (9) Syversen, T.; Kaur, P. The toxicology of mercury and its compounds. J. Trace Elem. Med. Biol. 2012, 26 (4), 215−226. (10) Bose-O’Reilly, S.; McCarty, K. M.; Steckling, N.; Lettmeier, B. Mercury Exposure and Children’s Health. Current Problems in Pediatric and Adolescent Health Care 2010, 40 (8), 186−215. (11) Kabir, K. M.; Sabri, Y. M.; Matthews, G. I.; Jones, L. A.; Ippolito, S.; Bhargava, S. K. Selective detection of elemental mercury vapor using a surface acoustic wave (SAW) sensor. Analyst 2015, 140, 5508. (12) Sholupov, S.; Pogarev, S.; Ryzhov, V.; Mashyanov, N.; Stroganov, A. Zeeman atomic absorption spectrometer RA-915+ for direct determination of mercury in air and complex matrix samples. Fuel Process. Technol. 2004, 85 (6), 473−485. (13) Logar, M.; Horvat, M.; Akagi, H.; Pihlar, B. Simultaneous determination of inorganic mercury and methylmercury compounds in natural waters. Anal. Bioanal. Chem. 2002, 374 (6), 1015−1021. (14) Laudal, D. L.; Thompson, J. S.; Pavlish, J. H.; Brickett, L. A.; Chu, P. Use of continuous mercury monitors at coal-fired utilities. Fuel Process. Technol. 2004, 85 (6−7), 501−511. (15) Kabir, K. M. M.; Sabri, Y. M.; Kandjani, A. E.; Ippolito, S. J.; Bhargava, S. K. Development and comparative investigation of Agsensitive layer based SAW and QCM sensors for mercury sensing applications. Analyst 2016, 141 (8), 2463−2473. (16) Kabir, K. M. M.; Ippolito, S. J.; Matthews, G. I.; Abd Hamid, S. B.; Sabri, Y. M.; Bhargava, S. K. Determining the Optimum Exposure and Recovery Periods for Efficient Operation of a QCM Based Elemental Mercury Vapor Sensor. J. Sens. 2015, 2015, 7. (17) Sabri, Y. M.; Ippolito, S. J.; Tardio, J.; Bansal, V.; O’Mullane, A. P.; Bhargava, S. K. Gold nanospikes based microsensor as a highly accurate mercury emission monitoring system. Sci. Rep. 2014, 4, 6741. (18) Sabri, Y. M.; Kandjani, A. E.; Ippolito, S. J.; Bhargava, S. K. Ordered Monolayer Gold Nano-urchin Structures and Their Size Induced Control for High Gas Sensing Performance. Sci. Rep. 2016, 6, 24625.

and produced deviated readings by up-to 70% from the CEAC reported concentrations. SEM characterization indicated that the higher sensitivity and selectivity of the developed nanospike Au-based sensor had resulted from the increased number of Hg0 molecules diffusing through the Au surface. The developed AuNS-QCM sensor possesses several major advantages including (1) no precondition requirement to remove humidity content as is performed by EPA solid sampling methods, (2) low maintenance requirements as the whole calibration, sampling, and testing can be integrated as a computer controlled system, (3) can produce several data points per day as opposed to 1 data point per 2 weeks currently produced to industries using the certified EPA sampling and analysis methods and (4) is a much cheaper method and robust device, whereas the EPA method can cost > $1000 per data point. The data present shows that nanostructured-based sensitive layers for QCM base microsensors are a viable means of measuring mercury vapor within complex industrial gas streams without the need to precondition the sample.

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AUTHOR INFORMATION

Corresponding Authors

*E-mail: [email protected]. *E-mail: [email protected]. Notes

The authors declare no competing financial interest.

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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 S.I. acknowledges the ARC for APDI fellowship (LP100200859). We thank the RMMF (RMIT Microscopy and Microanalysis Facility), for their equipment and expertise. K.M.M.K. acknowledges RMIT’s College of Science, Engineering and Health (SEH) for their financial support through the Higher Degree by Research Publications Grant (HDRPG).

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DOI: 10.1021/acs.iecr.6b01628 Ind. Eng. Chem. Res. 2016, 55, 7661−7668