Electronic Nose for Recognition of Volatile Vapor Mixtures Using a

Jun 25, 2015 - An electronic nose (e-nose) for identification and quantification of volatile organic compounds (VOCs) vapor mixtures was developed usi...
0 downloads 4 Views 3MB Size
Download PDF
Article pubs.acs.org/ac

Electronic Nose for Recognition of Volatile Vapor Mixtures Using a Nanopore-Enhanced Opto-Calorimetric Spectroscopy Inseok Chae,† Dongkyu Lee,*,†,§ Seonghwan Kim,‡ and Thomas Thundat† †

Department of Chemical and Materials Engineering, University of Alberta, Edmonton, Alberta T6G 2V4, Canada Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, Alberta T2N 1N4, Canada § Daegu Research Center for Medical Devices, Korea Institute of Machinery and Materials, Daegu 711-880, Republic of Korea ‡

S Supporting Information *

ABSTRACT: An electronic nose (e-nose) for identification and quantification of volatile organic compounds (VOCs) vapor mixtures was developed using nanoporeenhanced opto-calorimetric spectroscopy. Opto-calorimetric spectroscopy based on specific molecular vibrational transitions in the mid infrared (IR) “molecular fingerprint” regime allows highly selective detection of VOCs vapor mixtures. Nanoporous anodic aluminum oxide (AAO) microcantilevers, fabricated using a two-step anodization and simple photolithography process, were utilized as highly sensitive thermomechanical sensors for opto-calorimetric signal transduction. The AAO microcantilevers were optimized by fine-tuning AAO nanopore diameter in order to enhance their thermomechanical sensitivity as well as their surface area. The thermomechanical sensitivity of a bilayer AAO microcantilever with a 60 nm pore diameter was approximately 1 μm/K, which is far superior to that of a bilayer plain silicon (Si) microcantilever. The adsorbed molecules of VOCs mixtures on the AAO microcantilever were fully recognized and quantified by variations of peak positions and amplitudes in the opto-calorimetric IR spectra as well as by shifts in the resonance frequency of the AAO microcantilever with the adsorbed molecules. Furthermore, identification of complex organic compounds with a real industrial sample was demonstrated by this e-nose system.

D

sensitivity of a bilayer microcantilever has been exploited to generate an infrared (IR) spectrum of adsorbed molecules.12 A ternary mixture of highly energetic organic molecules was successfully recognized and quantified using the optocalorimetric technique with a receptor-free bilayer microcantilever.13 A picogram level of explosive molecules on the microcantilever surface generated enough heat for the microcantilever deflection as IR photons created a molecular vibration and caused distinct IR responses. Unlike conventional spectroscopic techniques, opto-calorimetric spectroscopy based on a microcantilever allows quantitative spectral measurements using a multimodal sensing approach.12−16 Various surface structure modifications such as growing nanowires, nanorods, and nanotubes have been implemented to increase the sensitivity of sensors with large surface area where target molecules are adsorbed.17−19 However, growing nanostructures consistently on sensor surfaces is quite challenging. In contrast to other types of modifications, nanoporous anodic aluminum oxide (AAO) structures have many advantages when they are used as microcantilever sensor substrates. They have higher reproducibility and uniformity than other structures due to the precise dimensions in their nanowells.20 In addition, an opto-calorimetric technique

eveloping an e-nose, that is, an artificial olfactory system to reproduce the human sense of smell, has been of great interest over the past two decades due to its possible applications in various fields such as environmental monitoring,1 medical diagnosis,2 the food industry,3 and controlling petrochemical processes.4 Although the chemical selectivity of an e-nose is an essential requirement for the recognition of molecules in complex vapor mixtures, most research has been primarily focused on enhancing its sensitivity. Recently, several attempts have been made to overcome the low chemical selectivity of an e-nose using a pattern recognition algorithm in a multiarray of sensors with multichemoselective interfaces5.6 However, it has been challenging to find a perfect chemoselective interface or receptor which is highly selective to the target molecules and also prevents nonspecific adsorption of the background molecules. Basically, the chemical interactions between target molecules and chemoselective interfaces are deterred in the presence of other background molecules, resulting in different signal patterns for mixtures.7−10 Microcantilevers have been utilized in transducing surface energy change into mechanical motion when chemical or biological molecules are bound with chemoselective interfaces.11 Even though microcantilevers have demonstrated multiarray sensing capability with mature silicon microfabrication technology, they still have been suffering from chemical selectivity issues, especially for small molecules. To overcome this challenge, the extremely high thermomechanical © 2015 American Chemical Society

Received: March 9, 2015 Accepted: June 23, 2015 Published: June 25, 2015 7125

DOI: 10.1021/acs.analchem.5b00915 Anal. Chem. 2015, 87, 7125−7132

Article

Analytical Chemistry demands flexible microcantilevers in order to achieve high thermomechanical sensitivity.21 Being able to easily control the AAO pore diameter and depth by self-ordering electrochemical anodization enables us to effectively tune the effective Young’s modulus as well as the thermal conductivity of these microcantilevers in order to enhance the thermomechanical sensitivity of the opto-calorimetric system. Moreover, the high surface energy and deep nanowell structure of AAO provide high performance for the vapor phase anayltes.22 We demonstrate the integration of a highly sensitive nanoporous AAO microcantilever and highly selective optocalorimetric technique for detection of VOCs mixtures under humid conditions. Nanoporous AAO microcantilevers were optimized by characterizing the effect of the surface area and physical properties using various pore diameters. This system can recognize and quantify the adsorbed molecules of VOCs vapor mixtures on the AAO microcantilever surface by analyzing variations in the peak position and amplitude of the opto-calorimetric IR spectra as well as variations in the resonance frequency of the microcantilever. Furthermore, we demonstrated detection of organic compounds mixture with a real industrial sample using this e-nose system.

microcantilever structures. The AAO microcantilevers were washed with methanol and deionized water, and dried with N2. Figure 1 shows scanning electron microscopy (SEM) images of the fabricated AAO microcantilevers with various nanopore

Figure 1. Scanning electron microscopy (SEM) images of nanoporous AAO microcantilevers with different lengths ranging from 180 to 810 μm with a 90 μm width (a). The length of 540 μm microcantilever was used in this study (white box). Side-view; 1 μm thickness (b). Topview of AAO microcantilevers with various pore diameters; (c) 35, (d) 50, and (e) 60 nm.

■

diameters. Eight microcantilevers with a width of 90 μm and lengths ranging from 180 to 810 μm are shown in Figure 1a. The microcantilever which has a length of 540 μm (white box) was selected to be used for the VOCs detections. The thickness of the AAO layer with a 60 nm pore diameter was 1 μm, which was confirmed by the side view SEM image in Figure 1b. The top of each microcantilever is open, and the bottom is sealed by an aluminum oxide barrier layer. Figure 1c−e show the top images of the AAO microcantilevers with different pore diameters; 35 (AAO35), 50 (AAO50), and 60 nm (AAO60), respectively. A pore-to-pore distance of the AAO microcantilevers was fixed at 100 nm, and each pore is positioned like a hexagonal honeycomb. When compared with U-shaped nanopore films made with other materials such as TiO2 and Si, the structure of AAO is much more ordered and uniform (see Supplementary Figure S1). The closed side of them was coated with 5 nm of titanium as an adhesion layer and then 50 nm of gold by using an electron beam evaporator. In Situ Gas Flow Setup. Five channels of N2 flow including one diluent line were controlled using digital mass flow controllers (MFCs) from Atovac (Suwon, South Korea). Vapor mixtures of water and three VOCs (acetone, ethanol, and naphtha) were generated by passing dry N2 through four different solutions in each bubbler. The concentration of each vapor was controlled by varying the flow rate of each channel at a total fixed flow rate of 100 mL/min. Opto-Calorimetric Spectroscopy Setup. Schematic of the IR spectroscopy with AAO microcantilever setup used in this study is shown in Figure 2. A gold-coated AAO microcantilever was mounted inside a tilted quartz flow cell, which was connected to the MFCs flow channels. The quartz flow cell was covered with a ZnSe window for IR transmission and placed in the head unit of MultiMode atomic force microscope (Bruker, Santa Barbara, CA). Three different quantum cascade lasers (Daylight Solutions UT-6, UT-8 and MIRcat) were used as high powered IR sources in a wide range of wavenumbers from 1760 to 961 cm−1 (5.68 to 10.4 μm in wavelength). The pulsed IR radiation of 200 kHz with 10% duty cycle from the UT-8 and 100 kHz with 5% duty cycle from the UT-6 and MIRcat were electrically modulated at 20 Hz using a function generator (DS345, Stanford Research

EXPERIMENTAL SECTION Materials. Acetone, ethanol, methanol, perchloric acid, oxalic acid, chromic acid, phosphoric acid, nitric acid, acetic acid, and sulfuric acid were purchased from Sigma-Aldrich (Oakville, ON) and were used as received. Naphtha was purchased from Fisher Scientific (Edmonton, AB). A highpurity aluminum sheet (99.99%) was obtained from Alfa Aesar (Ward Hill, MA). The photoresist (PR) HPR 504 and 354 developer were purchased from VWR (Mississauga, ON) and used for photolithography. Fabrication of Nanoporous AAO Microcantilevers. AAO microcantilevers were fabricated using a two-step anodization and photolithography process. The pure aluminum substrates were cleaned with acetone, ethanol, and deionized water to remove impurities. These substrates were then electropolished in a mixture solution of perchloric acid and ethanol (1:4 by vol %) at 5 °C by 20 V for 5 min. The first anodization was performed in 0.3 M oxalic acid at 15 °C for 8 h applying 40 V followed by wet-etching in a mixture of chromic and phosphoric acids to remove the random pores. Hexagonally well-ordered and straight nanopores were made during the second anodization, performed in the same sequence as the first, but only for 10 min to fabricate the 1 μm thick AAO structures. The pore diameter is increased from 35 to 60 nm in 0.1 M phosphoric acid solution at 30 °C with different lengths of time. A 500 nm thick aluminum was coated on the open side of the AAO films using a thermal evaporation, followed by putting a PR spin coating over them. A UV mask, which has the microcantilever patterns, was placed just above the PR coating layer, and UV light was shone on it for 3 s. By rinsing the AAO substrates in developer for 20 s, the reacted PR with UV light was melted down. The aluminum portion uncovered with PR was removed using a mixture solution of phosphoric acid, nitric acid, acetic acid, and water. The exposed AAO was also etched by dipping it in a phosphoric acid solution for 2 h. The rest of PR and aluminum were removed using acetone and the aluminum etching solution mentioned above. Electrochemical etching was carried out under electropolishing conditions for 3 h to remove the bulk aluminum and produce the suspended 7126

DOI: 10.1021/acs.analchem.5b00915 Anal. Chem. 2015, 87, 7125−7132

Article

Analytical Chemistry

Figure 2. Schematic illustration of a gold-coated nanoporous AAO microcantilever and multichanneled MFCs system for the VOCs vapor detection with opto-calorimetric IR spectroscopy.

Systems, Sunnyvale, CA) and directed to the microcantilever. The opto-calorimetric IR spectra were recorded using the SR850 lock-in amplifier (Stanford Research Systems, Sunnyvale, CA), and the resonance frequency of microcantilevers were measured using the SR760 spectrum analyzer (Stanford Research Systems, Sunnyvale,CA). Thermomechanical Sensitivity Measurements. The thermomechanical sensitivity of the 50 nm gold-coated AAO microcantilevers and that of 50 nm gold-coated plain silicon microcantilevers (Octo500S, Micromotive, Germany) were measured using a microceramic heater where the temperature is regulated by the heat controller (GLTC-PX9, Global Lab, Seoul, Korea) and Labview software. The temperature was cycled between 30 and 50 °C with heating and cooling rates at 2 °C/min and 1.3 °C/min, respectively. The voltage signal change (V) on the position sensitive detector by reflected optical laser light from a microcantilever beam was calibrated to the microcantilever deflection (μm) using a MSA-500 micro system analyzer (Polytec, Irvine, CA). Analysis of a Real Sample from Oil Sands Tailings Pond Water. Oil sands tailings pond water (TPW) was obtained from the Athabasca region in Canada (Syncrude Canada Ltd.). The real industrial sample was bubbled and introduced into the AAO microcantilever sensing system using the in situ gas flow setup. Four different flow ratios of the bubbling line to the diluent line (10 to 40%) were set to make variations in adsorbed mass of vapor mixtures on the AAO microcantilevers. Attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) (Nexus 670 FTIR, Thermo Nicolet, Madison, WI) was performed to acquire IR spectrum of TPW as a reference.

Figure 3. (a) Thermomechanical sensitivity measurements of 50 nm gold-coated nanoporous AAO microcantilevers with 35 (pink), 50 (green), and 60 nm (purple) pore diameter and 50 nm gold-coated plain Si microcantilever (black). (b) The adsorbed mass of acetone on each microcantilever as a function of vapor concentration. The error bars correspond to the standard deviations.

AAO60 was ∼4 times higher than that of the bilayer Si microcantilever. This is attributed to the variations of the effective Young’s modulus and thermal conductivity of the AAO with respect to its pore size. Also, the U-shaped nanoporous AAO structure itself contributes to the thermomechanical sensitivity as the sealed side expands more than the open side when heated.23 The effective Young’s modulus values of AAO microcantilevers were determined to be approximately 63.7 GPa (AAO35), 34.2 GPa (AAO50), and 12.8 GPa (AAO60) from the resonance freuqnecy measurement of each AAO microcantilever (see Supplementary Figure S2a). The decreased effective Young’s modulus with respect to the increased pore diameter contributes to the increase in thermomechanical sensitivity of the bilayer AAO microcantilever. Assuming the nanoporous AAO microcantilever is one unit, the deflection of a gold-coated AAO microcantilever, z, can be found using the following bilayer microcantilever deflection equation21

■

RESULTS AND DISCUSSION Figure 3a shows the thermomechanical sensitivity of the 50 nm gold-coated AAO microcantilevers (540 × 90 × 1 μm3) with different pore diameters and the 50 nm gold-coated plain Si microcantilever (500 × 90 × 1 μm3) for the comparison. The thermomechanical sensitivity of the bilayer AAO microcantilevers is enhanced by increasing the pore diameter -0.32 μm/K for AAO35; 0.67 μm/K for AAO50; and 1.02 μm/K for AAO60, respectively. The thermomechanical sensitivity of 7127

t +t 3 l3 z = − (α1 − α2) 1 2 2 P 4 t 2 K (λ1t1 + λ 2t 2)w

(1)

3 ⎛ t1 ⎞2 ⎛ t1 ⎞ E1 ⎛ t1 ⎞ E ⎛t ⎞ K = 4 + 6⎜ ⎟ + 4⎜ ⎟ + ⎜ ⎟ + 2⎜ 2⎟ E2 ⎝ t 2 ⎠ E1 ⎝ t1 ⎠ ⎝ t2 ⎠ ⎝ t2 ⎠

(2)

DOI: 10.1021/acs.analchem.5b00915 Anal. Chem. 2015, 87, 7125−7132

Article

Analytical Chemistry

Figure 4. Opto-calorimetric IR spectra of (a) acetone, (b) ethanol, and (c) naphtha on AAO60 at various concentrations. (d) Peak amplitudes of the acetone at 1737 cm−1 (red), ethanol at 1072 cm−1 (blue), and naphtha at 1373 cm−1 (green) as a function of vapor concentration and adsorbed mass.

mass than the first mode, was used to determine the mass of adsorbed molecules. The relationship between adsorbed mass and resonance frequency shift can be derived from22

where α is the thermal expansion coefficient, λ is the thermal conductivity, and P is the power which a microcantilever receives. l, t, and w are the length, thickness and width of the microcantilever. Subscripts 1 and 2 indicate the coated and original materials of the microcantilever substrate. For the goldcoated AAO microcantilever, the original material of the microcantilever is AAO and the coated material is gold. K stands for the expression of Young’s modulus (E) and the thickness of the original microcantilever and coating material. The porosity (P) of the AAO microcantilever was calculated using its radius (r) and well-to-well distance (d) to determine its thermal conductivity.24 P=

2 2π ⎛⎜ r ⎞⎟ 3 ⎝d⎠

fi = βi2

1 t 2π 12 l 2

E ρ

(4)

where f i, βi, and ρ are the n-th mode resonance frequency, the n-th mode eigenvalue (here β2 = 4.694), and the apparent density of the AAO microcantilever, respectively. Assuming the vapor molecules are uniformly adsorbed on the microcantilever surface and do not affect the spring constant of the microcantilever, the added mass on the microcantilever, Δm, is determined by the following approximate equation25

(3)

Δm ≈ −2mc

With the determined effective Young’s modulus and calculated porosity, the photothermal deflection sensitivity of AAO microcantilevers were predicted as a function of the gold coating thickness based on the bilayer microcantilever deflection equation (see Supplementary Figure S2b). The optimal thickness of the gold layer to maximize the photothermal deflection sensitivity of AAO60 upon IR absorption was calculated to be in the range of 30−50 nm. The theoretical results from eq 1 for each AAO microcantilever correspond well with the experimental results of thermomechanical sensitivity for the AAO microcantilevers as those with a bigger pore diameter showed higher thermomechanical sensitivity. Therefore, the thermomechanical sensitivity of bilayer AAO microcantilevers can be enhanced by controlling the pore size of AAO. The adsorbed mass of VOCs molecules on microcantilevers was calculated using the resonance frequency shift. Nanoporous AAO microcantilvers have relatively low resonance frequency due to their low effective Young’s modulus. The second mode of resonance frequency, which is more sensitive to an additional

Δfi fi

(5)

where mc is the actual mass of a microcantilever and Δf i is the n-th mode resonance frequency shift. The actual mass of the nanoporous AAO microcantilever, mc, is calculated by considering the density of aluminum oxide and its porosity. Using this equation, the adsorbed mass of vapor molecules is determined. Figure 3b shows the adsorbed mass of acetone molecules on AAO35, AAO50, AAO60, and the plain Si microcantilever at various vapor concentrations. The adsorbed mass of acetone molecules was gradually increased as a function of the vapor concentration. In addition, the adsorbed mass of acetone molecules on each AAO microcantilever is significantly higher than that of the plain Si microcantilever because the surface area of each microcantilever is 26 (AAO35), 37 (AAO50), and 44 (AAO60) times larger than that of the plain Si microcantilever with the same dimensions from a theoretical calculation. The increased surface area offers more adsorption sites for the vapor molecules. Using the same unit dimensions and pore to 7128

DOI: 10.1021/acs.analchem.5b00915 Anal. Chem. 2015, 87, 7125−7132

Article

Analytical Chemistry pore distance, the surface area of AAO microcantilevers is increased linearly with the pore diameter. As we expected, more molecules were adsorbed on the AAO microcantilever surface with a larger pore size because of the increased surface area. The adsorbed mass of ethanol and naptha on nanoporous AAO microcantilevers showed the same trend (see Supplementary Figure S3). The adsorbed mass of each vapor showed some variations due to its different molecular affinity to the AAO surface (see Supplementary Figure S4). Ethanol vapor, which is highly hydrophilic, is adsorbed more on the AAO surface than acetone and naphtha vapors at the same concentration. Figure 4a−c show the characteristic opto-calorimetric spectra of acetone, ethanol, and naptha molecules on the AAO60 at various vapor concentrations. The spectrum of each vapor is compare to conventional FTIR spectrum. The IR peaks appear at 1737 cm−1 (CO stretching) for acetone, 1072 cm−1 (C−O stretching) for ethanol, and 1373 cm−1 (symmetric deformation of CH3 in aliphatic molecules) for naphtha.26−28 The normalized IR peak amplitudes of each vapor were calculated to be 33 (acetone), 11 (ethanol), and 23 mV/ng (naphtha), respectively, indicating that the IR peak amplitudes are directly proportional to the adsorbed mass of VOCs on microcantilever surface, as shown in the inset of Figure 4d. It is also observed that the normalized IR peak amplitude for AAO60 (33 mV/ng) is increased ∼1.7 times compared with AAO50 (19 mv/ng) (see Supplementary Figure S5). The limit of detection (LOD) in terms of the adsorbed mass is estimated to be approximately 8.3 pg for acetone, 30.7 pg for ethanol, and 2.0 pg for naphtha. It was obtained by tracing the intersection of the linear fitting line with IR peak amplitudes and the straight line with signalto-noise ratio (SNR) of 3 at each wavenumber of IR peak. The number of vapor molecules at the LOD is estimated to be ∼1010 molecules on the AAO60. The peak amplitude of each vapor gradually increased in conjunction with the vapor concentration. The relation between the opto-calorimetric IR peak amplitude of each molecule and the vapor concentration is empirically found using the Freundlich adsorption isotherm equation29 x = kp1/ n m

Figure 5. (a) Normalized opto-calorimetric IR spectra of acetone (red), ethanol (blue), and naphtha (green). (b) Normalized optocalorimetric IR spectra of a ternary mixture (black: acetone, ethanol, naphtha) under humid condition and a mathematical fitting based on the linear superposition principle (orange).

reports.26−28 The adsorbed mass of acetone, ethanol, and naphtha on the AAO60 is determined to be 1.1, 3.4, and 1.1 ng at 14.4 × 103, 29.3 × 103, and 53.3 × 103 ppm vapor concentrations, respectively. The normalized IR spectra are obtained by dividing the deflection amplitude by the adsorbed mass. The peaks of the normalized spectrum of acetone are from CO stretching at 1737 cm−1 ; asymmetric CH 3 deformation at 1420 cm−1; symmetric CH3 deformation at 1367 cm−1 and C−C vibrations at 1240−1220 cm−1. The peaks of the normalized IR spectrum in ethanol are from asymmetric CH2 and CH3 bending at approximately 1445 cm−1; O−H bending at 1390 cm−1; symmetric CH2 bending at 1238−1260 cm−1; and C−O stretching at 1072 cm−1. The peaks of the normalized spectrum in naphtha are from CH2 scissors vibration at 1464 cm−1 and symmetric deformation of CH3 in aliphatic molecules at 1373 cm−1. Figure 5b shows the normalized IR spectrum of a ternary vapor mixture in humid condition (black, vapor mixture of three VOCs with water vapor) and a mathematical fitting with a weighted linear superposition of the individual IR spectra (orange). Water vapor molecules (4.6 × 103 ppm, 20% relative humidity) were mixed with the three VOCs vapor mixtures (14.4 × 103 ppm (acetone), 29.3 × 103 ppm (ethanol), 53.3 × 103 ppm (naphtha)) to determine whether or not the humidity degrades the performance of the e-nose system because humidity can be very high in some environmental conditions such as atmosphere, human breath, and industrial process. Although some of the peaks are broad and low due to the variations in the spectrum of each vapor, the unique molecular vibrational peaks are clearly observed in the normalized IR spectrum of the ternary vapor mixture. It clearly shows CO stretching of acetone (1737 cm−1), C−O stretching of ethanol (1072 cm−1), and CH2 vibration and CH3 deformation of naphtha (1464 and 1373 cm−1). Although vapor concentrations of individual components in a flow cell are known, it is difficult to estimate the relative adsorbed mass of individual components on a sensing device from a vapor mixture; however, we could solve this problem by using quatitative IR spectra. The characteristic IR peak positions were used for qualifying selective detection of adsorbed molecules, whereas combining the IR spectrum with the adsorbed mass allows quantitative analysis, as shown in Figure 5a. The adsorbed total mass of the vapor mixtures on

(6)

where x and p are the mass and equilibrium pressure of adsorbate, and m is the mass of adsorbent. k and n are constants decided by the temperature. Using the direct proportionality in IR peak amplitudes of adsorbed molecules and measured mass at different vapor concentrations, the relations between the IR peak amplitudes and vapor concentration were found and plotted as the Freundlich isotherm lines with measured points in Figure 4d. The LOD in terms of vapor concentration of each vapor is 40 ppm (ppm) at 1737 cm−1 (acetone), 100 ppm at 1072 cm−1 (ethanol), and 25 ppm at 1373 cm−1 (naphtha). It was measured by tracing the intersection of the Freundlich isotherm line and the straight line with SNR of 3. The different LOD value of each component is attributed to the difference in IR power intensities at the specific wavenumbers as well as the molecular affinity to the AAO surface. The LOD of VOCs can be improved by enhancing the IR laser power applied and the molecular affinity through a chemical modification on the AAO microcantilever surface. Figure 5a shows the normalized IR spectra of acetone (red), ethanol (blue), and naphtha (green) within a range of 1760 cm−1 to 1000 cm−1. The individual spectrum of each molecule is used separately as a reference, and it coincides with previous 7129

DOI: 10.1021/acs.analchem.5b00915 Anal. Chem. 2015, 87, 7125−7132

Article

Analytical Chemistry

Figure 6. Opto-calorimetric IR spectra of ternary vapor mixtures (acetone, ethanol, naphtha) in humid conditions with the increase of vapor concentrations of (a) acetone, (b) ethanol, and (c) naphtha. (d) Peak amplitudes of acetone at 1737 cm−1 (red), ethanol at 1072 cm−1 (blue), and naphtha at 1373 cm−1 (green) as a function of vapor concentration in the ternary mixtures.

AAO60 in Figure 5b was calculated to be ∼8.74 ng by tracing the resonance frequency shift. The combination of individual IR spectra from Figure 5a with the certain ratios was mathematically fitted (orange) to the IR spectrum of the ternary mixture (black) based on the linear superposition principle, as shown in Figure 5b. The relative adsorbed mass is estimated to be 0.4 (acetone), 1.69 (ethanol), and 0.32 ng (naphtha), respectively. The small variations of the relative adsorbed mass ratio between the single and mixture component may be a result of the competitive adsorption and different molecular affinity of molecules to the AAO surface (see Supplementary Figure S4). The rest of the mass change (6.33 ng) could be attributed to the adsorption of water molecules on the AAO microcantilever surface. Taking these results into consideration, we can conclude that this e-nose system is capable of identifying and quantifying the individual components in vapor mixtures under humid conditions using the individual fingerprints of their IR peaks. The maximum performance of this e-nose system with vapor mixtures is studied by varying the concentration of each vapor. Figure 6a shows the IR spectra of ternary vapor mixtures (acetone:ethanol:naphtha:water = 4.8:18.6:10.6:4.6 × 103 ppm) with increasing the concentrations of acetone vapor from 4.8 to 24.0 × 103 ppm in the same concentration of ethanol, naphtha, and water vapors. The IR spectrum of single acetone vapor (red dot) is presented as a reference in Figure 6a. It is difficult to recognize which molecules adsorb or desorb from the sensor surface with variations of the adsorbed mass, whereas the variations of the IR spectra clearly showed the increase only in the acetone peak areas even in ternary vapor mixtures when the concentration of acetone vapor increased. Small variations in the characteristic IR peaks of other vapors were observed as a result of adsorption equilibrium induced by molecular affinity to the AAO surface. The actual adsorbed mass of each vapor on AAO60 can be estimated by comparing the reference IR spectra of each vapor as previously shown in Figure 5b. The IR spectra

of ternary vapor mixtures with an increasing concentration of ethanol and naphtha vapor (Figure 6b,c) were also analyzed using the same method. The concentration of ethanol and naphtha vapor was increased from 18.6 to 34.6 × 103 ppm and from 10.6 to 96.0 × 103 ppm, respectively, whereas the concentrations of acetone and water vapor were kept constant. Figure 6d shows variations in the IR peak amplitudes of individual components within ternary vapor mixtures while the concentration of one component was increased. It is interesting to note that the LOD of each vapor within the ternary mixture in Figure 6d is similar to that of the LOD of single vapor in Figure 4d. In addition, the maximum performance of this enose system is superior to that of previous sensing systems using the pattern recognition algorithm method. The limit of recognition (LOR) can be estimated to be 1:275 for acetone to ethanol; 1:63 for ethanol to naphtha; and 1:118 for naphtha to acetone in ternary vapor mixtures. The results demonstrated that LOR of this technique shows almost two oders of magnitude greater than that (less than 1:5) of other multiarray sensors.8,9 To prove whether this system can identify complex organic compounds in a real industrial sample, we demonstrated identification of the complex organic compounds in tailings pond water (TPW) from Athabasca oil sands region. Tailings ponds are water storage dams where oil sands producers store the process water after used for bitumen extractions. Mature TPW consists of salts, minerals, fine clays and 1−3 wt % of residual bitumen, comprising multiple organic components such as paraffins, olefins, polycyclic aromatic hydrocarbons, naphthenes, and naphthenic acids, which causes serious problems of environmental pollution.30 The qualitative and quantitative analysis of complex organic compounds in TPW from Athabasca oil sands region was performed with the opto-calorimetric spectroscopy using AAO60. Despites complex orgarnic mixtures with fine clays and minerals in the real industrial sample, only VOCs and water 7130

DOI: 10.1021/acs.analchem.5b00915 Anal. Chem. 2015, 87, 7125−7132

Article

Analytical Chemistry

Figure 7. (a) Opto-calorimetric IR spectra of a TPW with increasing the adsorbed mass on AAO60; 1.3 ng (red), 2.3 ng (green), 3.1 ng (blue), and 4.0 ng (pink). The inset shows the photograph of TPW. (b) Peak amplitudes according to the organic functional groups as a function of adsorbed mass.

complex orgarnic mixtures in the real industial sample of oil sands TPW with nanogram quantities.

vapors in TPW can be evaporated through bubbling in the in situ flow setup. Figure 7a shows the IR spectra of TPW with increasing the adsorbed mass of vapor mixtures on AAO60 from 1.3 to 4.0 ng. The clear IR peaks appear at 1700 cm−1 (CO in carboxilyc acid), 1530 cm−1 (aromatic CC), 1390 cm−1 (O−H bending), 1370 cm−1 (symmetric CH3 deformation), 1240 cm−1 (symmetric CH2 bending), and 1100 cm−1 (C−O stretching).31 These IR peaks are comparable with the reference ATR-FTIR spectrum of TPW (see Supplementary Figure S6). These IR peaks are broader than the peaks of pure samples because TPW contains various organic chains and functional groups. The CO in carboxily acid, C−O stretching, and O−H bending IR peaks confirm that the TPW sample contains a certain amount of naphthenic acids, which represent the main toxic component for aquatic organisms in Athabasca region.32 The aromatic CC, symmetric CH3 deformation, and symmetric CH2 bending are due to the existence of polycyclic aromatic hydrocarbons and paraffins in the bitumen from oil sands. The peak amplitudes were increasing almost linearly as a function of the adsorbed mass, as shown in Figure 7b. Considering these results, the nanopore-enhanced opto-calorimetric spectroscopy is a very promising technique for the analysis of complex vapor mixtures.

■

ASSOCIATED CONTENT

* Supporting Information S

Large-scale SEM images, Young’s modulus, theroretical calculation of photothermal deflection sensitivity, and additional data of VOCs detection with AAO microcantilevers are included. ATR-FTIR spectrum of TPW is also contained. The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.analchem.5b00915.

■

AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Notes

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS This work was supported by the Institute for Oil Sands Innovation (IOSI) at the University of Alberta and the Canada Excellence Research Chairs (CERC) program. D.L also acknowledges partial support from the Korea Institute of Machinery and Materials (KIMM). S.K. also acknowledges the partial support from the Schulich School of Engineering at the University of Calgary.

■

CONCLUSION We have demonstrated the recognition and quantification of individual components in the VOCs mixtures under humid conditions. The highly sensitive and selective detection of VOCs was achieved with nanoporous AAO microcantilevers using opto-calorimetric spectroscopy. The thermomechanical sensitivity of the AAO microcantilever was enhanced by increasing its pore size resulting in lower effective Young’s modulus. AAO nanopores also resulted in an increase in the adsorption of molecules due to the larger surface area. We were able to determine the adsorbed mass of individual components on the AAO microcantilever surface from the specific ternary vapor mixture by analyzing the opto-calorimetric IR spectrum and the resonance frequency shift. This multimode operation offers substantial advantages in ultraselective and quantitative detection to the AAO microcantilever combined optocalorimetric spectroscopy. The selectivity of this technique shows almost 2 orders of magnitude higher than that of other multiarray sensors. Moreover, this system fully recognized

■

REFERENCES

(1) Baby, R.; Cabezas, M.; Walsoe de Reca, E. N. Sens. Actuators, B 2000, 69, 214−218. (2) Gardner, J. W.; Shin, H. W.; Hines, E. L. Sens. Actuators, B 2000, 70, 19−24. (3) Ampuero, S.; Bosset, J. O. Sens. Actuators, B 2003, 94, 1−12. (4) Ngo, K. A.; Lauque, P.; Aguir, K. Sens. Actuators, B 2007, 124, 209−216. (5) Baller, M. K.; Lang, H. P.; Fritz, J.; Gerber, C.; Gimzewski, J. K.; Drechsler, U.; Rothuizen, H.; Despont, M.; Vettiger, P.; Battiston, F. M.; Ramseyer, J. P.; Fornaro, P.; Meyer, E.; Güntherodt, H. J. Ultramicroscopy 2000, 82, 1−9. (6) Arshak, K.; Moore, E.; Lyons, G. M.; Harris, J.; Clifford, S. Sens. Rev. 2004, 24, 181−198. (7) Zellers, E. T.; Han, M. Anal. Chem. 1996, 68, 2409−2418. (8) Hsieh, M. D.; Zellers, E. T. Anal. Chem. 2004, 76, 1885−1895. (9) Jin, C.; Zellers, E. T. Anal. Chem. 2008, 80, 7283−7293. (10) Jin, C. G.; Kurzawski, A.; Hierlemann, A.; Zellers, E. T. Anal. Chem. 2008, 80, 227−236. 7131

DOI: 10.1021/acs.analchem.5b00915 Anal. Chem. 2015, 87, 7125−7132

Article

Analytical Chemistry (11) Lavrik, N. V.; Sepaniak, M. J.; Datskos, P. G. Rev. Sci. Instrum. 2004, 75, 2229. (12) Kim, S.; Lee, D.; Thundat, T. EPJ. Technol. Instrum. 2014, 1, 7. (13) Kim, S.; Lee, D.; Liu, X.; Van Neste, C.; Jeon, S.; Thundat, T. Sci. Rep. 2013, 3, 1111. (14) Lee, D.; Kim, S.; Jeon, S.; Thundat, T. Anal. Chem. 2014, 86, 5077−5082. (15) Lee, D.; Hwang, K. S.; Kim, S.; Thundat, T. Lab Chip 2014, 14, 4659−4664. (16) Lee, D.; Zandieh, O.; Kim, S.; Jeon, S.; Thundat, T. Sens. Actuators, B 2015, 206, 84−89. (17) Yan, H.; Xing, Y.; Hang, Q.; Yu, D.; Wang, Y.; Xu, J.; Xi, Z.; Feng, S. Chem. Phys. Lett. 2000, 323, 224−228. (18) Tak, Y.; Yong, K. J. Phys. Chem. B 2005, 109, 19263−19269. (19) Spitzer, D.; Cottineau, T.; Piazzon, N.; Josset, S.; Schnell, F.; Pronkin, S. N.; Savinova, E. R.; Keller, V. Angew. Chem., Int. Ed. 2012, 51, 5334−5338. (20) Lee, P. S.; Lee, J.; Shin, N.; Lee, K. H.; Lee, D.; Jeon, S.; Choi, D.; Hwang, W.; Park, H. Adv. Mater. 2008, 20, 1732−1737. (21) Barnes, J. R.; Stephenson, R. J.; Woodburn, C. N.; O’Shea, S. J.; Welland, M. E.; Rayment, T.; Gimzewski, J. K.; Gerber, C. Rev. Sci. Instrum. 1994, 65, 3793−3798. (22) Lee, D.; Shin, N.; Lee, K.-H.; Jeon, S. Sens. Actuators, B 2009, 137, 561−565. (23) Lee, D.; Kim, S.; Chae, I.; Jeon, S.; Thundat, T. Appl. Phys. Lett. 2014, 104, 141903. (24) Huang, C. H.; Sun, X. H.; Sun, Y. H. Adv. Mater. Res. 2011, 399−401, 641−645. (25) Naeli, K.; Brand, O. Rev. Sci. Instrum. 2009, 80, 063903. (26) Plyler, E. K. J. Res. Natl. Bur. Stand. 1952, 48, 281−286. (27) Zaki, M. I.; Hasan, M. A.; Pasupulety, L. Langmuir 2001, 17, 768−774. (28) Bagheri, M.; Chae, I.; Lee, D.; Kim, S.; Thundat, T. Sens. Actuators, B 2014, 191, 765−769. (29) Foo, K. Y.; Hameed, B. H. Chem. Eng. J. 2010, 156, 2−10. (30) Ramos-Padrón, E.; Bordenave, S.; Lin, S.; Bhaskar, I. M.; Dong, X.; Sensen, C. W.; Fournier, J.; Voordouw, G.; Gieg, L. M. Environ. Sci. Technol. 2011, 45, 439−446. (31) Shimanouchi, T.; Matsuura, H.; Ogawa, Y.; Harada, I. J. Phys. Chem. Ref. Data 1978, 7, 1323. (32) Herman, D. C.; Fedorak, P. M.; MacKinnon, M. D.; Costerton, J. W. Can. J. Microbiol. 1994, 40, 467−477.

7132

DOI: 10.1021/acs.analchem.5b00915 Anal. Chem. 2015, 87, 7125−7132