Spectroscopic Ultra-Trace Detection of Nitroaromatic Gas Vapor on

Feb 20, 2011 - Optical Materials Express 2014 4, 2409 .... scattering (SERS) substrates for highly selective and sensitive detection of 2,4,6-trinitro...
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Spectroscopic Ultra-Trace Detection of Nitroaromatic Gas Vapor on Rationally Designed Two-Dimensional Nanoparticle Cluster Arrays Jing Wang, Linglu Yang, Svetlana Boriskina, Bo Yan, and Bj€orn M. Reinhard* Department of Chemistry and The Photonics Center, Boston University, Boston, Massachusetts 02215, United States ABSTRACT: Nanoparticle cluster arrays (NCAs) are engineered two-dimensional plasmonic arrays that provide high signal enhancements for critical sensing applications using surface enhanced Raman spectroscopy (SERS). In this work we demonstrate that rationally designed NCAs are capable of detecting ultra-traces of 2,4-dinitrotoluene (DNT) vapor. NCAs functionalized with a thin film of an aqueous NaOH solution facilitated the detection of DNT vapor at a concentration of at least 10 ppt, even in the presence of an excess of potential interferents, including Diesel fuel, fertilizers, and pesticides. Both in the presence and in the absence of this complex background the SERS signal intensity of the NO2 stretching mode showed a continuous, concentration dependent response over the entire monitored concentration range (10 ppt-100 ppb). The small size, superb sensitivity, and selectivity, as well as the fast response time of 90% at 785 nm. A 1200 lines/mm grating with a blazing wavelength of 750 nm was used. The excitation laser was a 785 nm diode laser. After passing through a 785 nm laser line 2244

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Analytical Chemistry filter (Semrock, LL01-785-25), the laser light was injected into the objective using a dichroic (Semrock, LPD-785RU) and focused into the sample plane by a 40 air objective (numerical aperture (NA) = 0.65). The laser spot size on the sample had a radius of 40 μm. The laser power in the sample plane was 27.7 mW corresponding to an irradiance of 551 W/cm2. Light scattered off the sample was collected by same objective and filtered by the dichroic and an additional 803 nm long-pass filter (Semrock, LP02-785-RS). The active area for recording SERS spectra was limited by a slit in the entrance port of the spectrometer to 4.5 μm  31 μm. Ten individual acquisitions with a 2 s integration time were accumulated for each spectrum. Before each measurement, the SERS spectrum of the aqueous NaOH solution on a NCA (without DNT vapor) was taken as background signal, which was subtracted from all subsequently recorded DNT spectra on this chip. For the quantitative analysis of the SERS signal intensity we evaluated the peak intensity of the NO2 stretching mode at 1336 cm-1. Computational Electromagnetics. To estimate the Raman enhancement factors provided by the NCAs, we simulated the near-field intensity spectra of typical 3-5-particle clusters and nanocluster arrays by using the multiparticle generalized Mie theory (GMT) algorithms. GMT is a classical electromagnetic computational technique that provides a rigorous semianalytical solution to the problems of wave scattering by arbitrary arrays of spherical particles.34,35 To stay within the framework of the classical electromagnetic theory, all simulated cluster and NCA geometries had nearest interparticle separations no less than 1 nm.30,36 The intensity spectra were obtained under the excitation by a plane wave incident normally to the array plane, which corresponds to the experimental conditions. The spectra were averaged over all possible in-plane polarizations of the incident field. All the simulations we performed for d = 80 nm gold spheres with experimentally obtained gold refractive index values from Johnson and Christy37 immersed in the ambient medium with the refractive index n = 1.44.

’ RESULTS AND DISCUSSION We devised an experimental strategy for the SERS detection of DNT vapor that seeks to maximize sensitivity through combination of two synergistic effects: (i) analyte enrichment through reactive absorption onto the sensor, and (ii) signal amplification of the absorbed analytes through optimized NCA substrates. Our experimental approach to achieve an enrichment of the analyte in the vicinity of the NCA SERS substrate utilizes the acid-base behavior of DNT, which is efficiently deprotonated in basic buffers to form an anion. The deprotonated nitroaromatic species can form a stabilized Meisenheimer38 complex with a sodium cation in the solution. Since the anion has a higher solubility than the neutral species, whose equilibrium concentration in water is determined by the Henry’s law constant of KH = 9.27  10-8 atm 3 m3 3 mol-1,39 the deprotonation reaction facilitates an increased mass transfer into the basic aqueous solution. A thin film of this solution applied on a NCA therefore “captures” gas-phase molecules and makes them amenable to detection via SERS. Sylvia et al.21 have demonstrated before that wetting of random SERS substrates with a mist of 10 mM aqueous solution of NaOH results in a strong increase in the detection sensitivity. Sylvia et al. were able to detect DNT vapor at concentrations as low as 5 ppb using electrochemically roughened gold surfaces. Our goal was to further boost the

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detection sensitivity of the SERS sniffer by replacing the random SERS substrates through rationally designed NCAs. A systematic characterization of the influence of the nanoparticle diameter on the SERS signal enhancement provided by NCAs has indicated that d = 80 nm diameter nanoparticles provide higher ensemble averaged SERS signal enhancements than 40 or 60 nm diameter building blocks.29 Consequently, we chose d = 80 nm particles as building blocks for the NCAs used in this work. The average SERS enhancement factors provided by NCAs are, however, not determined by the size of the nanoparticle building blocks alone. Because of the distance dependent electromagnetic interactions between nanoparticles within the clusters and between entire clusters, the array morphology as determined by the intercluster separation (Λ) and the cluster size (D) need to be considered, as well (Figure 1a). We simulated the average intensity enhancement as function of wavelength for a (Λ = 100 nm; D = 200 nm; d = 80 nm) NCA, which can be reliably fabricated with high purity. Figure 1b compares the average E-field intensity enhancement for the (Λ = 100 nm; D = 200 nm; d = 80 nm) NCA with the average signal enhancement of isolated clusters (shown in the inset) and an individual 80 nm nanoparticle. The intensity spectra for isolated nanoparticle clusters were first averaged over all possible polarizations of the field incident on each cluster, and then over six possible cluster configurations shown in the inset. The average intensity spectra for the NCAs were obtained by considering seven random NCA configurations of 4  4 clusters and by averaging over 112 (16  7) individual clusters and over various polarizations of the electric field. The gain in E-field enhancement that results from an incorporation of individual clusters into an NCAs is well illustrated by Figure 1b. The NCAs provide higher E-field enhancement than either the individual nanoparticles or the isolated nanoparticle clusters because of synergistic electromagnetic interactions on multiple length scales in the array. The signal intensity of a specific molecular vibration with frequency ω in a SERS spectrum depends on the product of the local field enhancement factors [|Eloc(ω)|/|E0 (ω)|]2 at the pump and emission wavelengths.11,40 Eloc refers thereby to the local field experienced by the scatters, and E0 is the field of the incident light. The E-field intensity of the (Λ = 100 nm; D = 200 nm) NCA in Figure 1b peaks at approximately 775 nm and therefore offers high E-field intensities at both the 785 nm pump (Iav = 1425) and the 1350 cm-1 Stokes Raman wavelength (Iav = 876). The predicted E-field intensities translate into an average Raman enhancement of 1.25  106 for the NO2 stretching mode, predestining this NCA morphology for applications as a spectroscopic DNT sensor. The spatial E-field distribution in the NCA plane at both the pump and emission wavelength is plotted in Figures 1c,d; the E-field is localized in crevices and junctions between the particles, which create “hot-spots” that sustain high E-field intensities at both wavelengths. We fabricated the (Λ = 100 nm; D = 200 nm; d = 80 nm) NCAs using the template guided self-assembly approach described in the Experimental Section. Scanning electron microscope (SEM) images of a resulting NCA are shown in Figures 2a-c. At the highest magnification the configurations of the individual clusters are well recognizable and the similarity to the simulated cluster configurations included in Figure 1 becomes apparent. The experimental procedure for using the fabricated NCAs for vapor measurements is illustrated in Figure 2d. First a thin film of 10 mM NaOH solution was applied to the NCAs using a nebulizer; after this activation step the NCAs were transferred 2245

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Analytical Chemistry into a glass chamber containing DNT vapor with a partial pressure of pDNT. The DNT atmosphere was generated by incubating an aqueous solution of DNT of known concentration (cDNT) in a closed glass chamber at 25 °C overnight. Using the Henry’s law constant (KH) of DNT the resulting partial pressure of the analyte in the gas-phase was calculated as pDNT = KH 3 cDNT. Through variation of cDNT we could systematically change the concentration of DNT in the gas phase. Since the glass chamber needed to be briefly opened for inserting the plasmonic sensors, the actual gas phase concentrations during the measurements were even lower than the calculated

Figure 2. SEM images of a nanoparticle cluster array (NCA) with particle diameter d = 80 nm, cluster binding size D = 200 nm, and intercluster separation Λ = 100 nm. Size bars are (a) 400 nm, (b) 1 μm, and (c) 2 μm. (d) Sample preparation: the NCAs are wetted with an aqueous NaOH mist and exposed to DNT vapor at a defined concentration, which is controlled by the DNT concentration in the aqueous solution contained in the glass chamber at 25 °C.

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equilibrium concentrations. The latter serve as conservative estimates of the DNT vapor concentration in the following discussion. The SERS spectra recorded with NaOH activated NCAs exhibit the characteristic NO2 stretching mode at 1336 cm-1 after exposure to DNT vapor (Figure 3a). The signal intensity of this band is expected to depend both on the exposure time of the NCA to the analyte and its vapor concentration. First, we therefore characterized the time dependence of the SERS signal intensity at a constant DNT concentration. In Figure 3b we plot the peak intensity of the NO2 stretching mode obtained with NCAs incubated in the sublimated vapor of solid DNT for different periods of time. While in the first 1-5 min the SERS signal intensity shows a strong, continuous increase, at longer incubation times the SERS signal intensity does not continue to increase. Instead, we find that after 8 min of incubation the signal is already significantly reduced when compared with the measurement taken after 5 min, and the signal continues to decrease with increasing incubation time until the signal has completely disappeared after 15 min. To test whether the observed signal decrease resulted from an insufficient stability of the NCAs when incubated with the NaOH mist, we inspected the NCAs before and after exposure in the SEM. These experiments revealed that the particles remained bound to the substrate during the sensing experiments, arguing against a systematic removal of the nanoparticles through the NaOH solution as reason for the signal deterioration. Instead, we attribute the decrease in signal intensity at longer incubation times to the drying of the liquid film on the plasmonic array. Indeed, we observed that the liquid film sprayed onto the NCA slowly evaporated as function of time. The evaporation of the liquid on the NCA leads to a decrease in the ambient dielectric constant when the aqueous solution is replaced by air.41 This effect, together with the crystallization of NaOH on the NCA chip upon evaporation of the solvent, can account for a decrease in signal intensity as a function of time. Other effects that can potentially contribute to the observed decrease in SERS signal intensity are interadsorbate interactions, which have been observed to result in a decrease of SERS signal intensity at surface coverages as low as a few tenths of a monolayer.42 Since we obtained the maximum DNT signal intensity with an incubation time of 5 min, all measurements reported in the

Figure 3. (a) SERS spectra of DNT vapor at a concentration of 100 ppb and potential interferents (diesel, water, pesticide, fertilizer vapor at 25 °C). All spectra were recorded on NCAs containing an aqueous NaOH film. The characteristic NO2 stretching mode, which peaks at 1336 cm-1, is marked in the DNT spectrum. (b) Raman intensity as function of incubation time for NaOH solution activated NCAs with DNT vapor (200 ppb). 2246

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Figure 4. (a) SERS spectra of DNT measured on NaOH activated NCAs for concentrations between 100 ppb and 10 ppt. (b) Magnified view of the 250, 50, and 10 ppt spectra; a background spectrum is included, as well. The characteristic NO2 stretching mode at 1336 cm-1 is detected for concentrations down to 10 ppt.

following were performed with this acquisition time. We point out that although the NCAs reach peak performance after 5 min, this does not exclude that, depending on the concentration, DNT vapor can be detected much earlier. At a concentration of 100 ppb DNT, for example, the analyte provides sufficient SERS signal intensity for detection at the first recorded time point after an incubation time of 1 min. Overall, we conclude that the sensor response is instantaneous, but the signal intensity for a given concentration is time dependent. In this regard the NCAs behave similar to other state-of-the art trace vapor explosive sensors with diffusion controlled analyte adsorption.7,43 In the next step, we set out to explore the sensitivity of NaOH activated NCAs for DNT vapor. To that end we exposed NCAs to DNT vapor concentrations between 100 ppb and 10 ppt and recorded the corresponding SERS spectra. Representative spectra for the investigated DNT concentrations are shown in Figure 4a; in Figure 4b we plot only the spectra of the three lowest investigated DNT concentrations together with a background spectrum with an enlarged intensity scale. The characteristic 1336 cm-1 NO2 stretching mode is unambiguously identified in all spectra, even at concentrations as low as 10 ppt. This impressive detection threshold considerably exceeds the sensitivity of canines for gas-phase nitroaromatic compounds2 and is comparable to the best sensitivities achieved by both photonic1,8,22 and non-photonic43-45 based gas sensors. We cannot assume that under our experimental conditions the DNT distribution between vapor phase and NaOH solution reaches an equilibrium. However, a double logarithmic plot of the recorded 1336 cm-1 SERS signal as function of the DNT concentration (blue squares in Figure 5) shows a continuous linear increase of the SERS intensity as function of concentration. This power-law dependence of the SERS intensity on the DNT vapor concentration confirms a systematic response of the sensor and enables a quantification of the DNT vapor concentration through the measured SERS signal intensity. The error bars in Figure 5 represent the fluctuations in the SERS signal obtained under otherwise identical conditions on 5 different NCAs. The systematic concentration dependent response observed with the NCAs confirms that these engineered substrates are reliable SERS sensors that provide a reproducible signal amplification. Most practical applications do not require the sensing of the pure explosive vapor but, instead, necessitate the detection of the

Figure 5. Peak intensities of the 1336 cm-1 band without (blue) and with (red) interferents (diesel, fertilizer, and pesticide) as function of the DNT concentration.

analyte in a complex atmosphere that can contain background molecules in a much higher concentration than the analyte. Atmospheric background can interfere with the detection of ultra-traces of explosive vapors in multiple ways. First, interferents with spectral features that lie in the same spectral range as characteristic spectral features of the analyte could “cover” the explosive vapor signal. For nitro-aromatic compound this is less of a concern, since naturally occurring nitrates, which could cover the characteristic NO2 stretching mode, are rare. A second potential threat to the sensitivity of NCAs in gas vapor sensing is a covering of the active sensor surface through abundant interferents that coadsorb on the NCAs. The resulting blocking of the sensor surface would necessarily result in a decreased sensitivity and would significantly impact overall sensor performance. To evaluate the influence of potential interferents we set out to quantify the sensitivity of the NCAs for DNT in the presence of Diesel fuel, fertilizer, and pesticide vapor. We chose Diesel fuel since it is a known interferent for explosive vapor sensing, for instance, in landmine detection applications.21,46 We also included commercial fertilizers (Easy Gardener #6528) and pesticides (SC Johnson DRK 94892) as ubiquitous agricultural 2247

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Figure 6. SERS spectrum of 10 ppt DNT vapor in the presence of Diesel fuel, pesticide, and fertilizer vapor background at 25 °C. The NO2 stretching mode is marked by an arrow.

compounds. The SERS spectra of the pure interferent vapors recorded on NaOH activated NCAs at 25 °C are included in Figure 3a. None of the considered compounds contain spectral features that overlap with the characteristic 1336 cm-1 NO2 stretching mode of DNT. We also note in passing that water vapor, which is a significant concern in other spectroscopic analytics (e.g., infrared spectroscopy),47,48 has very small Raman cross sections and therefore does not interfere with explosive vapor sensing using NCAs. To validate the influence of the potential interferents through co-adsorption on the NCA surface, we performed a separate series of experiments in which we exposed the misted NCAs to different concentrations of DNT vapor in the presence of the background vapors. Diesel fuel, fertilizer, and pesticide were placed into the glass chamber containing the aqueous solution of DNT in separate open Eppendorf tubes. The atmosphere in the sample container was again equilibrated in a water bath at 25 °C overnight before the NaOH activated NCA was inserted. The NCA was then incubated in this atmosphere for 5 min, after which a SERS spectrum of the sample was acquired. We evaluated the 1336 cm-1 peak signal intensity over the same concentration range evaluated before for the quantification of the sensor response in the absence of background. The data obtained in the presence of Diesel, fertilizer, and pesticide background are included as filled, red circles in Figure 5. The Raman intensity increases again linearly as function of DNT concentration in a log-log plot, but the response curve is shifted to somewhat lower intensities than observed before without background. The signal intensities remain, however, sufficiently high to enable the detection of 10 ppt of DNT (Figure 6). We rationalize the excellent sensitivity obtained in the presence of the background vapors through the selective enrichment of DNT on the sensor surface through the aqueous NaOH film applied on the NCAs. Furthermore, the aqueous film protects the NCAs from hydrophobic components with high vapor pressures such as the Diesel fuel. The outstanding sensitivity demonstrated by the NCAS in the presence of an excess of background vapor makes these engineered SERS substrates a viable sensor platform for the selective detection of ultra-traces of nitroaromatic compounds in complex atmospheres.

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’ CONCLUSIONS NCAs are engineered SERS substrates that generate high E-field enhancements through a synergistic interplay of electromagnetic interactions on multiple (inter- and intracluster) length scales. In this manuscript we demonstrate that rationally designed NCAs enable the detection of extremely low concentrations of nitroaromatic vapors. Ultra-trace sensitivity for DNT was achieved by combining signal amplification through optimized NCAs with sample enrichment on the NCAs. DNT enrichment was accomplished through application of a thin film of aqueous NaOH onto the NCAs. The analyte efficiently absorbs into the NaOH solution where it can be detected through SERS. This experimental approach facilitated DNT vapor detection at a concentration of 10 ppt within a few minutes. Higher DNT concentrations could be detected even faster. SERS is a vibrational spectroscopy and as such provides molecular specific information. For the nitroaromatic analyte investigated in this work, the characteristic NO2 stretching mode provided a marker band, which enabled its selective detection in the presence of an excess of Diesel fuel, commercial fertilizer, and pesticide vapor. With these background vapors the total SERS signal intensities measured for DNT were somewhat lower than without, but the NCAs still achieved the impressive DNT detection threshold of 10 ppt. The NCA sensors provided a continuous, concentration dependent response over a large concentration range both in the presence and in the absence of background vapors. This behavior will facilitate quantitative DNT vapor concentration measurements using NCAs in the future. One limitation of the current assay is the drying of the NaOH mist on the NCA chip, which prevents a continuous explosive vapor monitoring. We anticipate that this problem can be overcome, for instance, using a sensor design that keeps the NCA chip in a water vapor saturated atmosphere. DNT, whose vapor pressure is approximately 20 times higher than that of TNT, is contained in military grade TNT with concentration of up to 1%.49 DNT is therefore a common marker compound used in the detection of the high explosive TNT. The NCAs’ capability to detect ultra-traces of DNT vapor in the presence of common interferents for gas sensors makes these engineered plasmonic materials a promising photonic sensor platform for landmine or concealed explosive detection. ’ AUTHOR INFORMATION Corresponding Author

*E-mail: [email protected].

’ ACKNOWLEDGMENT We acknowledge financial support from the National Science Foundation through Grants CBET-0853798 and CBET-0953121, and the Army Research Laboratory (cooperative agreement DAAD 19-00-2-0005). ’ REFERENCES (1) Toal, S. J.; Trogler, W. C. J. Mater. Chem. 2006, 16, 2871–2883. (2) Oxley, J. C.; Waggoner, L. P. Detection of Explosives by Dogs; Elsevier: Amsterdam, The Netherlands, 2009. (3) Czarnik, A. W. Nature 1998, 394, 417–418. (4) Moore, D. S. Rev. Sci. Instrum. 2004, 75, 2499–2512. (5) Moore, D. S. Sensing and Imaging 2007, 8, 9–38. (6) Germain, M. E.; Knapp, M. J. Chem. Soc. Rev. 2009, 38, 2543–2555. 2248

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