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Silica Nanochannel-Based Interferometric Sensor for Selective Detection of Polar and Aromatic Volatile Organic Compounds Yafeng Wang, Qian Yang, Meijiao Zhao, Jianmin Wu, and Bin Su Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.8b01681 • Publication Date (Web): 13 Aug 2018 Downloaded from http://pubs.acs.org on August 16, 2018
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Analytical Chemistry
Silica Nanochannel-Based Interferometric Sensor for Selective Detection of Polar and Aromatic Volatile Organic Compounds Yafeng Wang, Qian Yang, Meijiao Zhao, Jianmin Wu and Bin Su* Institute of Analytical Chemistry, Department of Chemistry, Zhejiang University, Hangzhou 310058, China. *Email:
[email protected] ABSTRACT: Public awareness of the toxicity of volatile organic compounds (VOCs) has led to increased requirements for direct measurement of these substances. This work reports the sensitive detection of VOCs at the ppb level by an interferometric sensor based on the multilayer silica nanochannel membrane (MSNM). The MSNM is fabricated by layer-bylayer stacking of free-standing ultrathin SNM composed of regularly ordered channels with an ultrasmall diameter of about 2.3 nm and an ultrahigh density of about 4 1012 cm2. Light reflected from parallel interfaces of MSNM gives rise to the interferometric pattern with constructive and destructive fringes. The adsorption of VOCs to highly porous MSNM varies the refractive index of MSNM, resulting in the shift of the reflectometric interference spectrum (RIS) and thus yielding highly sensitive responses with a limit of detection (LOD) at the ppb level. Moreover, the sensor selectively responds to polar ethanol and acetone, as well as aromatic benzene, toluene and chlorobenzene, but is insensitive to nonpolar ethane or hexane. The selectivity most likely arises from hydrogen bonding and dipole interaction of VOCs with silica surface.
Volatile organic compounds (VOCs) are substances that tend to evaporate easily at room temperature.1 They are one of the most common air pollutants emitted from building materials, paints, furniture, vehicles, industrial combustion and so on.2-4 Exposure to VOCs would cause acute and chronic health hazards. Major non-carcinogenic hazards include asthma, chronic respiratory lesion, neurological toxicity and multiple organ injury,5 while the carcinogenic ones include liver, kidney, lung, blood (leukaemia and nonHodgkin lymphoma) and biliary tract cancers.6,7 The permissible exposure limits at which no adverse effects are expected for single VOCs are usually at the ppb level.7 However, most of the VOCs could not be sensed by the human olfactory system at this level or even beyond. Therefore, VOCs detectors with high sensitivity, fast response, high selectivity are essentially needed. Modern instrumental techniques, such as GC-MS8-10 and GC-UV,11,12 have been widely employed to detect VOCs. However, these technologies need expensive equipments and time-consuming sample preparation. Vapochromism,1320 surface plasmon resonance (SPR),21 chemiresistor,22-28 electrochemistry29 and reflectometric interference spectroscopy (RIfS)30-33 have been developped in labs for VOCs detection. Among these, RIfS, which is label-free, fast and cost-effective, has attracted more and more attention.34,35 RIfS is based on the optical interference of light reflected from the interfaces of adjacent layers with different refractive indices. Single layer or multilayer membranes are usually used in RIfS. Porous silicon, anodic aluminum oxide and titanium dioxide are the commonly used single layer membrane.33,36 While, for multilayer membrane, photonic crystals (PCs) made from silicon, alumina or other materials are widely applied.37-42 Biomimetic PCs or PCs obtained directly from nature are attracting considerable attention for their unique applications in chemical sensing and biosensing.43-46 For example, Potyrailo et al. have reported that the iridescent scales of the Morpho sulkowskyi butterfly give a different optical response to different individual VOCs, and this
optical response dramatically outperforms that of existing nano-engineered photonic sensors.47 However, the limit of detection (LOD) at the ppm level or higher for the sensors mentioned above are usually achieved. This work describes the fabrication of interferometric sensor based on silica nanochannel membrane (SNM) for the detection of VOCs at the ppb level. In comparison with aforementioned nanoporous membranes, the SNM consists of straight channels with an uniform size of 2.3 nm in diameter and an ultrahigh density of 4 1012 cm2, which is at least two orders of magnitude larger.48 Moreover, silica surface offers more adsorption sites than well-studied porous silicon.49 So the adsorption of VOCs to highly porous SNM will alter its refractive index and thus lead to the red-shift of reflectometric interference spectrum (RIS, as exemplified in Figure 1). Herein multilayer SNM (MSNM) was prepared using the layer-by-layer stacking approach to increase the effective optical thickness (EOT) and adsorptive volume. The adsorption of VOCs to MSNM, as studied by monitoring the light inteferometric response, yields selective detection of polar VOCs (e.g., ethanol and acetone) and aromatic compounds (such as benzene, toluene and chlorobenzene) at the ppb level.
Figure 1. Schematic illustration of VOCs detection by MSNMbased interferometry.
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EXPERIMENTAL SECTION Chemicals and Reagents. All chemicals and reagents were analytical grade or higher and used as received without further purification. Indium tin oxide (ITO) coated glass was purchased from Zhuhai Kaivo Optoelectronic Technology Co., Ltd. Concentrated ammonia aqueous solution (25 wt%), tetraethoxysilane (TEOS), cetyltrimethylammonium bromide (CTAB), poly(methyl methacrylate) (PMMA, Mw = 996000) and hexaammineruthenium(III) chloride ([Ru(NH3)6]Cl3, 98%) were purchased from Sigma. Potassium hexacyanoferrate(III) (K3[Fe(CN)6]) was obtained from Aladdin. Ultrahigh purity nitrogen gas containing 100 ppm VOCs was purchased from Hangzhou jingong special gas Co., Ltd. All aqueous solutions were prepared with ultrapure water (18.2 M cm). Fabrication of SNM. SNM fabricated on ITO coated glass was prepared by the Stöber-solution growth approach.50 In brief, the ITO coated glass was first cleaned under ultrasonication in 1 M NaOH ethanol solution, acetone, ethanol and ultrapure water for 20 min sequentially. Then, the ITO coated glass was immersed in the solution consisting of TEOS (80 µL), CTAB (0.16 g), ammonia aqueous solution (10 µL), ultrapure water (30 mL) and ethanol (70 mL). The SNM was grown at 60 °C for 6 - 48 h. Finally, the ITO coated glass was rinsed with deionized water and aged overnight at 100 °C. The CTAB micelles in the silica nanochannels were removed by immersing the SNM/ITO in 0.1 M HCl ethanol solution under magnetic stirring for 15 min. Fabrication of MSNM. Single-crystalline p-type silicon wafer [polished on the (100) face] was immersed in piranha water (7:3 v/v solution of concentrated sulfuric acid and 30% hydrogen peroxide) at 85 °C for 4 h. The silicon wafer was tailored into square with an area of 1.5 cm 1.5 cm. SNM with growth time of 24 h was used to prepare MSNM. The SNM was transferred from ITO coated glass to silicon wafer using the approach reported previously.51 Typically, a drop of PMMA solution was spin-coated on the SNM/ITO at 2000 rpm for 30 s. After solvent evaporation at room temperature, the spin-coated SNM/ITO was baked at 115 °C for 15 min and then immersed in 2 M HCl aqueous solution at room temperature overnight to etch the ITO layer. The obtained free-standing PMMA/SNM was cleaned by immersing in ultrapure water for three times, which could be fished out by silicon wafer or SNM/ITO. The membrane was dried at room temperature for 1 h, followed by heating at 100 °C for another 2 h. Finally, the PMMA layer was removed by immersing in acetone for 6 h. By repeating the operations mentioned above, MSNM with certain number of layers can be prepared. MSNM Characterization. Scanning electron microscopy (SEM) images were obtained on a SU8010 field-emission scanning electron microscope at 5 kV. Transmission electron microscopy (TEM) images were obtained on a HT7700 transmission electron microscope. Samples for TEM measurements were fabricated by scraping SNM from ITO coated glass. As-prepared small pieces of SNM were dispersed by ultrasonic in ethanol and dropped on a holey carbon-coated copper grid for TEM observation. Cyclic voltammetry (CV) characterization of MSNM on ITO coated glass were performed on a CHI 660D electrochemical workstation (CH Instrument, Shanghai) and a traditional three-electrode configuration was used. Namely, MSNM modified ITO coated glass (1 cm 1 cm), Ag/AgCl electrode (saturated KCl) and platinum wire served as the
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working electrode, reference electrode and counter electrode, respectively. Vapor Sensing Experiment. The vapor sensing experiment was performed using MSNM with 3 layers (MSNM-3) prepared on silicon wafer. Mass-flow controller was used to dilute the VOCs to a certain concentration. As seen in Figure S1, 100 ppm VOCs diluted with ultrapure nitrogen gas was connected to a 100 cm3 min1 mass flow controller. Ultrapure nitrogen gas (99.999%) was used as the carrier gas and regulated by two 1600 cm3 min1 mass-flow controllers and a 100 cm3 min1 mass-flow controller. All the gases were mixed sufficiently and controlled at 60 cm3 min1 before delivery to the test chamber. RIS was obtained with an Ocean Optics QEpro CCD spectrometer. Light from a tungsten-deuterium lamp (Hangzhou SPL Photonics Co., Ltd) was focused on the MSNM-3 with a spot size of about 2-3 mm2 at the normal angle (Figure S2). The spectrum was referenced to a silicon wafer ((100) oriented). MSNM-3 was heated at 100 °C for 1 h before vapor sensing experiment to remove water and residual VOCs in silica nanochannels. The spectrum was recorded in the wavelength range from 200 nm to 1000 nm. The vapor sensing was carried out at room temperature (20 1) °C.
RESULTS AND DISCUSSION The SNM was initially prepared by the stöber-solution growth approach on the ITO coated glass.50 As seen from the SEM image in Figure 2a, Layer 1 refers to the SNM with a thickness of ca. 100 nm (Note that the thickness can be varied from several tens of nanometers to 150 nm by increasing the growth time, see Figure S3). The TEM image (see Figure 2b) confirms that the SNM has a thickness of about 100 nm and consists of straight nanochannels. Topview TEM images shown in Figure 2c-d reveal an orderly hexagonal packing of pores over a large domain with a pretty uniform diameter of ca. 2.3 nm. The pore density estimated from Figure 2d is about 4 1012 cm2. The SNM is highly porous with a surface area as high as 834 m2 g1, which is particularly advantageous for the adsorption and detection of VOCs.50 As reported recently,51 the SNM can be exfoliated from the ITO coated glass by chemical etching under the support of PMMA to obtain free-standing SNM. The free-standing SNM can be subsequently transferred to another substrate, such as another piece of SNM-coated ITO glass or silicon wafer. By simply repeating the etching-transfer operation, we obtained the MSNM with its thickness modulated by the number of layers (as illustrated in Figure 2e). Figure 2f-h display the cross-sectional SEM images of MSNM consisting of 1, 2 and 3 layers on silicon wafers, in which interfaces between two adjacent layers can be clearly seen. Thanks to the Si-O chemical bonding formation at each boundary, the MSNM is pretty compact and stable. Although the superposition of multiple SNM layers may partially block nanochannels, the mass transport of small molecules is not influenced too much (confirmed by CV, seen Figure S4). In other words, the permeability of MSNM to small molecules does not vary remarkably, due to the ultrahigh pore density of SNM. Figure 3a-c display the RIS of MSNM consisting of 1 to 3 layers of SNM. Note that silicon wafer instead of ITO coated glass was used as the substrate in order to get rid of the interferometric signal generated by the ITO layer. Clearly, light reflected by MSNM gives rise to the reflectometric interference pattern with constructive and
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Figure 2. (a) Cross-sectional SEM image showing a single layer of SNM grown on the ITO electrode. (b, c) TEM images of SNM illustrating its cross-section and top topography. (d) Magnified image of (c) with the scale bar of 10 nm. The bright spots in (d) are the silica pores with an average diameter of 2.3 nm. (e) Illustration of PMMA-assisted transfer method for the fabrication of MSNM. (f-h) Cross-sectional SEM images of MSNM consisting of 1, 2 and 3 layers of SNM prepared on silicon wafers, respectively. The scale bars in all images are 100 nm except that in (d).
destructive fringes. Furthermore, the number of peaks increases with the number of layers. The corresponding insets show that the color of MSNM also varies with the number of layers, appearing gray, blue, purple, respectively. This trend is in agreement with light reflectance by nanoporous membranes at different thickness.
Figure 3. Reflectometric interference spectra of MSNM on silicon wafers consisting of (a) 1, (b) 2 and (c) 3 layers of SNM. The insets show the photographs of MSNM.
According to the Fabry-Pérot interference theory, the wavelength at the peak positions has a relationship with the membrane thickness,52 (1) m 2nL where m is an integer corresponding to the spectral order of the fringe, λ the light wavelength, n the average refractive index of MSNM and L the thickness of MSNM. According to eq 1, the thicker the MSNM is, the more values could be assigned to m. A thick MSNM composed of more layers exhibited a very complicated spectrum, in which multiple peaks could be observed (e.g., 4 peaks for MSNM-3). The value of EOT (2nL) could be obtained from RIS. The peaks in RIS correspond to the consecutive values of m in eq 1 and the position (λ) of each peak in RIS could be directly obtained. Since the value of m for each peak in RIS was an integer, the values of m for all peaks could be calculated by dividing the relevant λ of different peaks. Finally, the EOT of MSNM can be calculated from eq 1. The change of EOT of MSNM can be in situ monitored by recording the shift of RIS. To obtain a larger shift and a relative simple RIS,
MSNM-3 was used in the vapor sensing experiment. The peak in the visible region (m = 2) was used to calculate EOT (assuming thus calculated EOT amounts to the average EOT of MSNM). The thickness of MSNM-3 is about 303.3 5.2 nm. The experimental setup for the detection of VOCs is shown in Figures S1 and S2. The variation of EOT generated upon exposing MSNM-3 to different VOCs was directly measured. Figure S5 displays the RIS of MSNM-3 for different VOCs at various concentrations. Apparently, the spectrum shifts with the increased concentration of VOCs. As shown in Figure 4, an immediate increase of EOT was observed for aromatic benzene, toluene and chlorobenzene (Figure 4a-c), as well as polar ethanol and acetone (Figure 4d-e). Moreover, it obviously increased with increasing the VOCs concentration from 5.7 to 100 ppm. We speculate that the variation of EOT arises from the selective adsorption of VOCs to nanochannels of MSNM-3 via hydrogen bonding.53,54 The silica surface is occupied by a high density of silanol groups, which are able to form hydrogen bonding with -electrons of aromatic compounds55 or with the hydroxyl/carbonyl group of ethanol/acetone. In addition, the adsorption may also benefit from the dipole interaction.53 As seen in Figure 4f, no obvious change of EOT was observed for nonpolar ethane. While only a small change of EOT for weak polar n-hexane (see physicochemical parameters in Table S1) was observed. MSNM has fast response time to different VOCs, as well as good repeatability (Table S2). The effect of humidity to the sensor was shown in Figure S6, the change of EOT was relatively large when relative humidity (RH) was bigger than 40%, resulting from the adsorption of water molecules and condensation of water molecules in the nanochannels of MSNM. Therefore, the detected gas should be dried at high humidity or when water was contained before delivery of samples to the sensor.
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Figure 4. Response curves of MSNM-3 to different concentrations of (a) benzene, (b) toluene, (c) chlorobenzene, (d) ethanol, (e) acetone, (f) ethane and n-hexane. The relative concentration (ppm) is marked on the top of each response plateau.
The adsorption of VOCs can be considered by a surface reaction model,56 in which the surface adsorption site (S) and adsorbate (P) are regarded as reactants to form surface complex (SP), k S P k1 SP 2 (2) The kinetic equation can be expressed as, d k1[P][S] k1[P] k2 (3) dt where [S], [P] and Г express the surface density of adsorption sites (monolayer adsorption capacity, mol m2), the pressure of VOCs (pa) and the surface coverage of SP (mol m2), respectively. k1 and k2 denote the adsorption rate constant (pa1 s1) and desorption rate constant (s1). At equilibrium, Г and [P] can be correlated by the Langmuir isotherm,57 b[P] (4) [S] 1 b[P] where b = k1/k2 is the Langmuir constant. It can be also expressed as, 1 1 1 1 (5) [S] b[S] [P] In terms of eq 5, b and [S] can be obtained by plotting 1/Г with respect to 1/[P]. From EOT, we can calculate directly the refractive index of MSNM-3, namely nSNM, according to eq 1. The relationship between nSNM and the adsorption of VOCs can be considered by a three-component Bruggemann equation,58-60 n2 n2 n2 n2 VSiO2 2SiO2 SNM VVOC 2VOC SNM 2 2 nSiO2 2nSNM nVOC 2nSNM (6) 2 2 nfm nSNM 1 VSiO2 VVOC 2 0 2 nfm 2nSNM where VSiO2 and VVOC denote the volume fractions of silica and VOCs. nSiO2, nVOC and nfm are the refractive indices of silica, VOCs in the liquid state and medium filling the nanochannels (assuming it is wavelength-independent). At a
certain temperature, nfm, nSiO2 and VSiO2 are constants. VSiO2 (83.3%) can be simply estimated from the top-view TEM image of SNM. nSiO2 can be derived from a two-component Bruggemann equation (in the absence of VOCs adsorption), 2 2 n2 n2 nfm nSNM VSiO2 2SiO2 SNM 1 V 0 (7) SiO2 2 2 2 nSiO2 2nSNM nfm 2nSNM So VVOC can be related to EOT in terms of eq 1, 6 and 7. It can be further used to calculate Г by assuming silica nanochannels to be cylindrical and the adsorbed VOCs has the same molar volume as that in liquid state, VVOC Vpore (8) spore Vmol (1 VSiO2 ) where Vpore and spore are the volume (m3) and surface area (m2) of a nanochannel. Vmol is the molar volume (m3 mol1) of adsorbed VOCs (in liquid state). Eventually, we can set up the relationship between [P] and Г by solving eq 1 and 58 simultaneously. [P] can be transformed to the concentration of VOCs, cVOC (ppm), by [P] = 101000 cVOC 106 (101000 pa is the ambient pressure under the vapor sensing condition). Physicochemical constants used in the calculation were given in Table S1. Figure 5a-b show that the adsorption of different VOCs follows a classical Langmuir-type model. Г increased rapidly with the concentration in the low concentration range, then turned to increase slowly in the medium range and eventually reached a plateau at a certain high concentration. The value of Г under certain cVOC is mainly decided by the molecular size of VOCs and the interaction between VOCs and the surface of MSNM. Гethanol and Гacetone are much larger than that of benzene, toluene and chlorobenzene, resulting from the smaller molecular size and stronger hydrogen bonding. We can fit this relationship alternatively according to eq 5, as shown in Figure 5c-d. The obtained fitting values are summarized and compared in Table 1. The value of S for acetone and ethanol is similar as the surface density for hydroxyl on amorphous silica surface (2.49 106 7.47 106 mol m2).61,62 While for benzene, toluene and chlorobenzene, this value is smaller. The value of b for acetone is larger than other VOCs, indicating that it
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Additional figures and tables (PDF)
AUTHOR INFORMATION Corresponding Author *Email:
[email protected] ORCID Bin Su: 0000-0003-0115-2279
Notes The authors declare no competing financial interest.
ACKNOWLEDGMENTS The financial support by the Nature Science Foundation of China (21335001, 21575126) and the Nature Science Foundation of Zhejiang Province (LR14B050001) is acknowledged.
REFERENCES Figure 5. The concentration dependence of surface adsorbed aromatic VOCs (a) and polar VOCs (b). The standard curves for aromatic VOCs (c) and polar VOCs (d).
is easier for acetone to adsorb on the surface of MSNM. The analytical sensitivity toward ethanol and acetone is one order of magnitude higher than aromatic compounds. The LOD for all VOCs was obtained at the ppb level, which is better than that of most VOCs sensors reported in literatures (Table S3). Particularly, a LOD of 55 ppb was achieved for acetone. The low LOD and high analytical sensitivity mainly result from the ultrahigh surface area of MSNM and the ultrahigh surface density of adsorption sites. Table 1. Adsorption parameters and analytical data for different VOCs b VOCs
Benzene Toluene Chlorobenzene Ethanol Acetone
1
(pa )
S 10
Sensitivity 6
10
LOD
7
(ppb)
(mol m2)
(mol m2 pa1)
1.06 1.36 1.51 7.69 4.61
2.56 0.13 5.02 0.73 3.65 0.32 28.4 3.8 46.3 1.2
0.242 0.369 0.242 0.370 1.00
710 49 279 28 372 62 78 10 55 7
CONCLUSIONS In summary, the sensitive detection of VOCs based on the optical interferometric response of MSNM is reported. A layer-by-layer stacking approach was devised to vary the membrane thickness to modulate the optical response. We think that the MSNM is advantageous over other interferometric nanoporous membanes in terms of its ultrahigh pore density and ultrasmall channel size. The adsorption of VOCs can induce a remarkable variation of the refractive index, thus yielding a high detection sensitivity at the ppb level. Moreover, driving by hydrogen bonding and dipole interaction, the MSNM selectively responds to polar and aromatic VOCs. We expect that the selectivity and sensitivity can be further improved by proper controlling the nanochannel structure and surface.
ASSOCIATED CONTENT Supporting Information The Supporting Information is available free of charge on the ACS Publications website.
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