Optimization of Surface-Enhanced Raman Spectroscopy Conditions

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Optimization of Surface Enhanced Raman Spectroscopy Conditions for Implementation into a Microfluidic Device for Drug Detection Neal D. Kline, Ashish Tripathi, Rustin Yavar Mirsafavi, Ian J. Pardoe, Martin Moskovits, Carl D. Meinhart, Jason A. Guicheteau, Steven D. Christesen, and Augustus W. Fountain Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.6b02573 • Publication Date (Web): 07 Oct 2016 Downloaded from http://pubs.acs.org on October 9, 2016

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Analytical Chemistry

1 Optimization of Surface Enhanced Raman Spectroscopy Conditions for Implementation into a Microfluidic Device for Drug Detection

Neal D. Kline*, Ashish Tripathi§, Rustin Mirsafavi°, Ian Pardoe‡, Martin Moskovits†, Carl Meinhart#, Jason A. Guicheteau§, Steven D. Christesen§, and Augustus W. Fountain III§,¶ *Oak Ridge Institute for Science and Education Research and Technology Directorate, Edgewood Chemical Biological Center, Aberdeen Proving Ground, MD 21010-5424 º Department of Biomolecular Science and Engineering, University of California Santa Barbara, Santa Barbara, California 93106, United States † Department of Chemistry and Biochemistry, University of California, Santa Barbara, California 93106, United States ‡ Excet, Inc., Springfield, VA 22150 # Department of Mechanical Engineering, University of California Santa Barbara, Santa Barbara, California 93106, United States §

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Corresponding author. Email: [email protected] Mailing Address: ATTN: RDCB-DRD-L 1583 Blackhawk Road APG, MD 21010-5424 Keywords: Surface enhanced Raman spectroscopy, Microfluidics, Drug detection ABSTRACT A microfluidic device is being developed by University of California Santa Barbara as part of a joint effort with the United States Army to develop a portable, rapid drug detection device. Surface enhanced Raman spectroscopy (SERS) is used to provide a sensitive, selective detection technique within the microfluidic platform employing metallic nanoparticles as the SERS medium. Using a number of illicit drugs as analytes, the work presented here describes the efforts of the Edgewood Chemical Biological Center to optimize the microfluidic platform by investigating the role of nanoparticle material, nanoparticle size, excitation wavelength, and capping agents on the performance, and drug concentration detection limits achievable with Ag and Au nanoparticles that will ultimately be incorporated into the final design. This study is

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2 particularly important as it lays out a systematic comparison of limits of detection and potential interferences from working with several nanoparticle capping agents: tannate, citrate, and borate which does not seem to have been done before as the majority of studies only concentrate on citrate as the capping agent. Morphine, cocaine, and methamphetamine were chosen as test analytes for this study and were observed to have limits of detection (LOD) in the 1.5-4.7 x 108

M (4.5-13 ng/ml) range with the borate capping agent having the best performance.

INTRODUCTION Worldwide drug trade and drug use has increased significantly over the past several years posing a growing threat to the United States in terms of public health, national security, and the fight against terrorism.1-5 The detection of illicit drugs or their metabolites in bodily fluids has proven to be an effective way to identify individuals who have used or come into contact with them.6 Some of the current analytical methods available for drug testing include gas chromatography with mass spectrometry (GC/MS), high performance liquid chromatography (HPLC), and enzyme linked immunosorbent assay (ELISA).7-12 These analytical techniques are mostly performed in a laboratory environment with highly trained personnel conducting the tests and require time consuming, expensive pretreatment steps and reagents. There are portable drug tests available that rely on the Marquis reagent test or other colorimetric tests to determine the presence of illicit drugs.13 However, such tests require specialized reactants, large sample volumes, and only screen for a limited number of possible drugs. Consequently, there exists a demand for drug testing techniques that are portable, cheap, selective, and can be used to test for numerous substances. Surface-enhanced Raman spectroscopy (SERS) combined with microfluidics is a potential solution for a portable drug testing platform. SERS is a form of vibrational spectroscopy that has


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3 become a valuable technique in nondestructive chemical analysis due to its high sensitivity and ability to discriminate between molecular species based on highly specific vibrational spectroscopic signatures. The foundation of SERS relies on the enhancement of normal Raman signatures of molecules that are adsorbed to an appropriately designed nanostructured substrate that is excited at its plasmon resonance.14,15 Normal Raman signatures have been enhanced up to 6-10 orders of magnitude making the detection of single molecules possible using SERS.16,17 Despite the tremendous advantages of SERS uses outside of the laboratory are impractical due to bulky and expensive laboratory equipment, lack of reproducibility, and expensive substrates generally needed for high sensitivity SERS detection. Combining SERS with a microfluidic platform provides a way to overcome these barriers. Microfluidics is the science of manipulating and analyzing fluid flow in structures of submillimeter dimension.18-20 Microfluidic chip designs have the advantages of using low fluid volumes and production on mass scale enabling them to be disposable, cost effective, and portable. Using microfluidics to design SERS platforms also allows the careful control of the flow and interaction between liquids on a microscale leading to more reproducible results and the use of patterned, immobilized noble metal substrates or colloids as a SERS medium which are typically very cheap to synthesize and can produce large enhancement factors. Meinhart and Moskovits have developed several variations of microfluidic/SERS platforms demonstrating the detection of cancer cells and methamphetamine in bodily fluids and the detection of airborne molecules using colloidal nanoparticles as the sensing medium.21-25 Multiple groups have also designed devices that utilize immobilized SERS substrates such as TiO2 nanotubes, noble metal films over nanostructured black silicon, and noble metal electrodes to detect analytes including



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4 explosives and neurotransmitters.26-29 Combining SERS with microfluidics has the potential to fill the current technological gap in portable, low cost detection devices. In order to incorporate SERS into a microfluidic device for drug detection, optimization of the SERS conditions is crucial. If using colloidal nanoparticles as the SERS medium the combination of nanoparticle material, nanoparticle size, excitation wavelength, and capping agent on the nanoparticle that allows the lowest detection limits need to be determined in order to achieve the best possible results within the microfluidic platform. This report details the investigation of silver (AgNPs) and gold (AuNPs) colloidal nanoparticles of various sizes (20-80 nm) as the SERS medium and measures their performance under excitation wavelengths of 532, 633, and 785 nm while using citrate, tannate, and borate capping agent on the nanoparticles. To demonstrate the applicability of the current study to drug detection, cocaine, methamphetamine, and morphine are used as the probe analytes. EXPERIMENTAL METHODS Chemicals and Materials AgNPs and AuNPs (20-80 nm, citrate capped, NanoXact; 50 nm Au, tannate capped, NanoXact) were purchased from nanoComposix, AgNPs (50 nm, tannate capped, PELCO NanoXact) were purchased from Ted Pella, AuNPs and AuNPs (10-30 nm, borate capped) were synthesized in house. Characteristics of nanoparticle solutions including size distribution and polydispersity is included in Supporting Information. Silver nitrate (AgNO3, ≥99%), gold (III) chloride trihydrate (HAuCl4·3H2O, ≥99.9%), sodium borohydride (NaBH4, 99%), cocaine hydrochloride (C17H21NO4·HCl), methamphetamine hydrochloride (C10H15N·HCl), and morphine sulfate salt pentahydrate (C34H40N2O10S·5H2O) were purchased from Sigma-Aldrich. All chemicals were used as received and all water was obtained from an Elga Ultra AN MK2


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5 water purification system. Samples for Raman measurements were prepared in 500 µL glass vials that had been coated with 0.2 microns of aluminum by thermal evaporation in a Denton Vacuum Explorer. Vials were coated with aluminum to eliminate any background interference from glass that might be observed during the Raman measurements. Glass vials were recycled throughout the study by submerging used aluminum coated glass vials in aqua regia to strip the aluminum and then recoating the vials after washing and drying. Synthesis of Borate Capped AuNPs and AgNPs A slightly modified Creighton method30,31 was used to synthesize the borate capped AgNPs and AuNPs by the reduction of AgNO3 and HAuCl4·3H2O, respectively, with NaBH4. For synthesis of AgNPs solutions of 2.00 mM NaBH4 and 1.00 mM AgNO3 were prepared using ice-cold water to ensure stability of precursors throughout synthesis, especially for NaBH4 which is prone to side reactions with water. A 50 mL plastic test tube containing 20.00 mL of NaBH4 solution was wrapped with copper tubing and a chilled ethylene glycol/water mixture was flowed through copper tubing using a PolyScience PP7LR-20-A11B refrigerated circulating bath to maintain a temperature of 0oC with constant stirring of NaBH4 solution. AgNO3 solution (9.00 mL) was maintained at 0oC in an ice bath and was slowly added dropwise to the NaBH4 solution using a 1.000 mL pipette over a 15 minute period. During the addition of AgNO3, the NaBH4 solution turned from clear and colorless to a clear, pale yellow solution upon initial addition of AgNO3. The yellow color of the solution continued to intensify as AgNO3 solution was added and upon completion assumed an intensely yellow color similar to that of dark urine. After addition of AgNO3 the stirring was allowed to continue for 15-20 minutes to ensure completion of the reaction.



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6 A procedure similar to the one outlined above was used to synthesize the AuNPs. A 2.00 mM NaBH4 was prepared and 20.00 mL was placed into a 50 mL plastic test tube to be chilled by a circulating bath of ethylene glycol/water at a temperature of 10.0oC and constantly stirred. An 8.00 mL solution of 1.00 mM HAuCl4·3H2O chilled to 10.0oC in an ice bath was added dropwise with a 1.000 mL pipette over 15 minutes during which the stirring NaBH4 solution turned from clear and colorless to a clear pink/light red color to a clear, dark red solution upon completing addition of HAuCl4·3H2O. Both the AgNPs and AuNPs were stored away from light in a refrigerator for the duration of the study. UV-Vis Spectroscopy The UV-Vis absorption measurements were performed using a Thermo Evolution 60 UV-Vis spectrometer to obtain the absorbance in the wavelength range from 200-1100 nm for AgNPs and AuNPs. Baselines were acquired using milli-Q pure water; samples were prepared by mixing 0.750 mL of colloid, 0.750 mL of 1.00 x 10-3 M of analyte (morphine, cocaine, methamphetamine), and then adding 0.250 mL of 1.00 M LiCl all in a quartz cuvette. Scans of samples were obtained before and immediately after salt addition. Raman Microscopy The Raman measurements were performed with a JASCO NRS-3200 dispersive Raman microscope system operating at 532, 633, and 785 nm excitation with approximately 4 mW power incident on the sample. A 10× microscope objective was used both to focus the laser on the analyte solutions and to collect the Raman scattered light. The relatively modest laser power and magnification were used to minimize any laser-induced heating of the substrate. The bottom of the microscope objective was above the surface of the liquid so an immersion objective was not needed. The Raman scattered light was dispersed with a 600 grooves/mm diffraction grating


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7 (blazed at 750 nm) and a spectrometer entrance slit width of 100 m was used to obtain a spectral resolution of approximately 8 cm-1. Raman spectral mapping of the colloidal solutions was performed by selecting a 9 location grid, in a rectangular 3x3 format, on the solution and obtaining Raman spectra at each of the locations. Raman spectra were acquired with 5 seconds of integration time collecting one spectrum per mapping point for each particle size study of AgNPs colloid at 532 and 633 nm; for the AuNP size study Raman spectra were acquired with 10 and 15 seconds of integration time at 633 and 785 nm, respectively, collecting one spectrum per mapping point. The capping agent study for AgNPs and AuNPs was carried out at the same wavelengths and with the same parameters on spectral collection except the integration time was increased to 15 seconds for all spectral collection. The Raman scattered light was detected with a thermoelectrically cooled CCD camera (Andor), and the strong Rayleigh scattered light was suppressed with a notch filter (Semrock). Preparation of Samples for SERS Stock solutions of methamphetamine (1.00 x 10-2 M), cocaine (1.00 x 10-2 M), and morphine (1.00 x 10-3 M) were made and varying concentrations of each analyte were prepared by serial dilutions of stock solutions. To probe the effects of nanoparticle size, nanoparticle material, and excitation wavelength, aliquots of 0.150 mL of 20-80 nm citrate capped Au or Ag colloid were pipetted into the glass vial and a 0.150 mL aliquot of a select analyte was pipetted into glass vial and were mixed for approximately 1-5 seconds using the pipette tip. For this portion of the study, all analyte solutions had an initial concentration of 1.00 x 10-3 M. Colloidal samples were also diluted to have equal surface area-to-volume ratios to eliminate any effects on the SERS signal due to varying binding capacities of colloidal solutions. After mixing was



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8 completed, a 0.050 mL aliquot of 1.00 M LiCl was added to induce aggregation of colloidal nanoparticles, solution was mixed, and Raman spectra were collected. The investigation of concentration limits with different capping agents follows a very similar procedure to the one in the previous paragraph. AgNPs 50 nm in diameter and AuNPs 60 nm in diameter capped with tannate and citrate capping agents and 10-30 nm in diameter with a borate capping agent were used for this portion of the study. Serial dilutions of stock analyte solutions were used and a calibration curve generated to determine limits of detection for the different excitation wavelengths, nanoparticle materials, and capping agents. Solutions for this portion of the investigation were prepared in the same manner as the previous paragraph with 0.150 mL aliquots of both the selected colloid and analyte and 0.050 mL of 1.00 M LiCl added to induce aggregation. Theoretical Calculations Density functional theory (DFT) calculations were employed to confirm vibrational band assignments for cocaine (C17H21NO4), methamphetamine (C10H15N), and morphine (C17H19NO3). Calculations were run with Gaussian09 Rev. C01 on a Cray XC30 supercomputer at the Air Force Research Lab at Wright-Patterson Air Force Base through the Department of Defense’s High Performance Computing Modernization Program.32 Optimization and frequency calculations employed the B3LYP hybrid functional of Becke, Lee, Yang, and Parr, and were performed on the molecular structures in vacuum.33 Calculations for the smaller methamphetamine molecule were run with the Dunning augcc-pVTZ basis set while the larger cocaine and morphine molecules were calculated with the smaller Pople 6-31G(d,p) basis set to allow the calculation to finish in the allotted super computer time.34,35 Results and vibrational modes were visualized using the Avogadro 1.1.0


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9 software package.36 Vibrational frequencies for the aug-cc-pVTZ and 6-31G(d,p) basis sets were scaled by factors of 0.968 and 0.961, respectively.37 RESULTS AND DISCUSSION UV-Vis Spectroscopy Figure 1 shows the UV-Vis spectra obtained for methamphetamine (UV-Vis spectra for cocaine and morphine are S2 and S3 in Supporting Information) in AgNPs and AuNPs with spectra recorded both before and after addition of LiCl. The most striking feature of the AgNPs and AuNPs spectra (prior to addition of LiCl) is the intense absorption maxima, due to the dipole absorption of the plasmon resonance of the nanoparticle solutions, between 390-460 nm for the AgNPs and 520-550 nm for the AuNPs.38 This indicates that for both Ag and Au nanoparticles the real part of the dielectric constant is negative with minimal intraband losses, suggesting the imaginary part of the dielectric constant is small. These are necessary conditions for plasmon resonance with high quality factor to occur in the visible portion of the electromagnetic spectrum.39-42 For a multi nanoparticle system the location of the plasmon band is affected by several factors including interparticle distance, surface species adsorbed, dielectric constant of the surrounding medium, onset of interband transitions, density of electrons, and effective electron mass.42-45 The pre-LiCl extinction spectra for AgNPs and AuNPs are observed to broaden (with a shoulder appearing in the 80 nm AgNP) with the absorption maxima red shifting as the nanoparticle size increases. This observation can be attributed to retardation effects, excitation of higher order plasmon modes in the nanoparticle, and increasing polydispersity in the nanoparticle solution.45-50 Aliquots of LiCl were added to the nanoparticle solution to induce aggregation resulting in intense SERS spectra. After LiCl addition the UV-Vis spectra of the nanoparticle solutions



10 show significantly reduced primary plasmon resonances for the AgNPs and AuNPs, and new, broad plasmon resonances appearing with frequencies at longer wavelengths. The residual intensity in the primary plasmon bands for the AgNPs and AuNPs indicate that some of the nanoparticles in solution are unaffected by the addition of the analyte and LiCl and remain unbound. The shift in plasmon resonance frequency was also accompanied by a distinct color change in the nanoparticle solutions as the AgNP solution turned from yellow to a gray/blue color and AuNP solution turned from red to blue. The observed color change and red shifting of plasmon resonance frequencies indicate aggregation of the nanoparticle solutions is occurring

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Figure 1: UV-Vis spectra of 1 x 10-3M methamphetamine in 20-80 nm, citrate capped AgNPs (top row) and AuNPs (bottom row), before addition of LiCl (left column) and after addition of LiCl (right column).

As this study will investigate the effects of nanoparticle material, excitation wavelength and nanoparticle size on SERS intensity, the UV-VIS data shown here can provide some initial information on what we should expect. The AgNPs should present SERS enhancement at 532 nm, 633 nm, and 785 nm excitation with progressively decreasing SERS intensity both from


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11 being off resonance of the plasmon band and the longer wavelength. The AuNPs will most likely not present any SERS enhancement at 532 nm. This is because the secondary plasmon band, which indicates nanoparticle aggregation and where we would expect the SERS enhancement to come from, is red shifted to wavelengths longer than 532 nm. Also Au experiences the onset of interband transitions beginning at 550 nm and these are a very efficient loss mechanism causing the damping of plasmons.2 While the UV-VIS data does not provide much information on the effect that changing nanoparticle size will have on the SERS intensity. It does show the dependence on the locations of the main plasmon band and secondary plasmon band (after LiCl addition) bringing the plasmon more into or off resonance from a specific excitation wavelength. Other factors such as the strength of the analyte/metal binding will affect the limits of detection. This will be discussed in more detail in subsequent sections. SERS SERS spectra were collected for the various analytes using AgNPs and AuNPs and are displayed in Figure 2 and compared to powder spectra of each analyte. SERS spectra were collected after addition of LiCl was added as no signal was observed prior to LiCl addition. Not all of the bands present in the normal Raman spectra of the powders experience enhancement and are observed in the SERS spectra obtained with the nanoparticle solutions. For the Raman bands that do experience enhancement, lines have been overlaid on the spectra to allow correlations to be drawn between the normal Raman spectra and the SERS spectra. The labeled SERS bands are then compared with theoretical predictions and vibrationally assigned in Table 1.



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Figure 2: SERS and normal Raman spectra of methamphetamine (left spectra), cocaine, (center spectra) , and morphine (right spectra). The red trace in each spectrum is the SERS spectra of 1 x 10-3 M of each analyte obtained with 50 nm, citrate capped AgNPs, the blue trace is the SERS spectra of 1 x 10-3 M of each analyte obtained with 50 nm, citrate capped AuNPs, and the black trace in each spectrum is the normal Raman spectrum of each analyte in powder form for reference. All spectra shown were obtained with a 633 nm excitation laser at approximately 4.0 mW of power, 3 x 3 map collecting one spectra per point with a 15 s integration time, and diluting the AuNPs to the same surface area:volume as the AgNPs. Table 1: SERS bands labeled in Figure 2 are vibrationally assigned and compared to theoretical predictions.

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Vibrational Assignment γ(benzene ring)+ ωs(C-H, benzene ring) β (H5C6-CH2-CH)+ ωas (C-H, benzene ring)+ γ(benzene ring) δ(benzene ring) ωas(C-H2)+ δ(benzene ring)+ βas(CH3)+ τ ( H5C6-CH2-CH )+ β(H3C-CH-CH2) δ(benzene ring) δ(benzene ring) γ(benzene ring) γ(piperidine/pyrollidine ring) υs(H2C-CH-CH, piperidine ring)+υas (H2C-CH2-CH2, pyrollidine ring) δ(benzene ring) υ(C-O, piperidine ester)+ βas(C-H3, piperidine ester)+γ(piperidine/pyrollidine ring)+ω(C-H, piperidine ester) υas(H5C6-C-O) +δ(benzene ring) + ω(4-CH2,2-CH, piperidine/pyrollidine ring) ω(2-CH, piperidine ring)+ ωs(CH2, piperidine ring) δ(benzene ring) δ(benzene ring) υ(C=O, benzoate ester) δ(Ring A,C,E)+β(H2-N-CH3) δ(ring D)+ γ(ring A) δ(all rings) υas (H2C-N-CH, ring D)+δ(all rings)+ ω(OH, ring C)+ ω(C-H, ring C)+ωas(C-H2, ring D) δ(ring A)+ωs(C-H2, ring D)+ω(C-H, ring D)+ ω(C-H, ring C)+ω(OH, ring A) +ω(OH, ring C) δ(benzene ring)

Abbreviations: vs: very strong; s: strong; m: medium; γ: out of plane distortion; δ: in plane distortion; τ: torsion; υ: stretching; β:bending; ω: wag; s: symmetric; as: anti-symmetric.


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Figure 3: Molecular structures of analytes methamphetamine (top left), cocaine, (top right), and morphine (bottom center).

Vibrational assignments presented in this study are consistent with assignments made in previous investigations.51-56 The molecular structures of the analytes are also presented in Figure 3 as an aid for visualizing vibrational mode assignments. When comparing SERS spectra obtained with the AgNPs vs. AuNPs, there are several similarities between the two nanoparticle solutions. For instance, band C in the methamphetamine spectra and J in the cocaine spectra represent in-plane distortions of the benzene rings in the respective molecules and are clearly observed in both nanoparticle solutions; bands O and P in the cocaine spectra represent an in-plane benzene ring distortion and the C=O stretch of the benzoate ester group and appear intensely in the SERS spectra of the AgNPs and AuNPs. Additionally bands R, S, and V in the morphine spectrum can be attributed to various in-plane and out-of-plane distortions of the ring structures of that molecule and are observed in both nanoparticle solutions. Since many of the same SERS bands are observed with approximately the same relative intensities in the SERS spectra recorded with the AgNPs and AuNPs, some commonality clearly exists in the manner in which the molecules bind to the surfaces of the two materials.57 While there are many similarities between the SERS spectra of the AgNPs and AuNPs there are some notable differences as well. One of the main differences is the intensity of the



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14 SERS bands is much greater with the AgNPs than with the AuNPs although nanoparticle size, excitation wavelength, analyte solutions, integration time, laser power, and surface area to volume ratio were controlled for in both nanoparticle solutions. This disparity in observed intensity can be attributed to the fact that Ag is a more efficient plasmonic material at 633 nm than Au leading to more enhancement for Ag at this particular excitation wavelength.39,41,42,58 Another difference is that some of the SERS bands that are observed with the AgNPs don’t seem to be observed at all in the AuNPs. Examples include band A in the methamphetamine spectra; bands F, G, and K in the cocaine spectra; and band Q in the morphine spectra. One possibility is that due to the difference in enhancement of the Ag vs. Au, there is simply not enough enhancement being provided by the Au surface to observe those particular bands with the AuNPs. Particle Size The ultimate goal of this study is to determine the optimal nanoparticle material, nanoparticle sizes, excitation wavelength, and capping agents for incorporation into a microfluidic based sensor. To determine the optimal nanoparticle size, AgNPs and AuNPs ranging in size from 20-80 nm were studied with SERS spectra being collected for each particle size after addition of LiCl and aggregation was induced (Figure 4). There is a clear trend observed regarding nanoparticle size for AgNPs and AuNPs starting at 20 nm in which the analyte SERS signal increases until reaching 50-60 nm in diameter and then drops off at 70 and 80 nm. Similar trends have been observed in previous studies 38,59-61


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50

60

70

80

Particle Size (nm)

90

100

10

20

30

40

50

60

70

80

Particle Size (nm)

Figure 4: Peak area as a function of nanoparticle size for 1001 cm-1 SERS band of cocaine, 1000 cm-1 SERS band of methamphetamine, and 627 cm-1 SERS band of morphine. Top left graph represents data taken with AgNPs at 532 nm, top right is AgNPs at 633 nm, bottom left is AuNPs at 633 nm, and bottom right is AuNPs at 785 nm. All nanoparticles were capped with citrate and each data point represents experimental trials done in triplicate.

Several phenomena can affect the observed enhancement. Surface plasmon resonances dephase on the femtosecond time scale, and thermalize on the picosecond time scale. In small nanoparticles, dephasing is dominated by non-radiative channels such as electron-electron interactions, while thermalization occurs primarily by electron-phonon or electron-defect scattering.62-64 In addition, the mean free path of electrons in Ag and Au is 40-50 nm which means that in very small nanoparticles (20-30 nm) the effective conductivity of the metal is reduced due to electron scattering at the nanoparticle surface reducing the quality factor of the plasmon thereby lowering the SERS enhancement.65,66 The lower SERS enhancement from the smaller nanoparticles will make them an undesirable choice to employ them in the microfluidic device as the sensing medium.



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16 In larger nanoparticles non-radiative damping pathways become less important and radiative damping becomes dominant, as the rate of radiative damping is proportional to the total number of oscillating electrons (i.e. its volume). This allows radiative pathways to play a larger role as metallic nanoparticles increase in size.67 As non-radiative damping pathways become less prevalent this results in a larger local electromagnetic enhancement as the particle size increases, but only up to a point as the radiative damping channels begin to dominate. Additionally, as the AgNPs and AuNPs increase in size, the plasmon resonance bands of the post-LiCl UV-Vis spectra (Figure 1) show a large degree of red shift so that, depending on the excitation wavelength used, making resonance with the plasmon band better or worse. The combined effects of SERS enhancement increasing/decreasing with particle size due to different damping pathways and also the red shifting of secondary plasmon bands means there should be an optimal nanoparticle size to obtain maximum SERS enhancement. Our results indicate that there is an optimal size of AgNPs and AuNPs around 50-60 nm which shows the largest amount of SERS signal for the analytes. Capping Agent Using metal nanoparticles as a SERS medium for analyte detection can be a more complicated and difficult proposition than using other mediums such as a planar metal substrate. For example, with nanoparticles a capping agent (some kind of organic or inorganic ligand) has to be attached to the metal surface in order to stabilize the particles in solution, which is an issue that is largely absent if using planar metal substrates. The presence of the capping agent complicates the detection process because the capping agent and analyte compete for binding sites on the metal surface. In order to observe the analyte it needs to have a higher binding affinity than the capping agent used to stabilize the nanoparticle solution thereby replacing it.


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17 Unfortunately, precise thermodynamic binding constants for the analytes and capping agents used in this study is largely absent in the literature, although sufficient qualitative principles exist to suggest which should likely be the most loosely bound and the easiest to displace.69-73 Additional complications arise when background signatures from the capping agents interfere with analyte signals. Sufficient spectroscopic overlap between analyte/capping agent signals would invalidate the use of that particular capping agent. Given the difficulties arising from binding-site competition between the capping agent and analyte and also the potential for spectral interference, the optimal choice of capping agent is critical in developing a SERS based detection system using metal nanoparticles. With the optimal nanoparticle size being determined in the previous section, the final aspect of the investigation involves evaluating various capping agents on the AgNPs and AuNPs by determining limits of detection while varying the excitation wavelength between 532, 633, and 785 nm. The three capping agents that were studied are citrate, tannate, and borate (Figure 5), chosen because these are three of the more weakly bound capping agents allowing their displacement by analyte, thereby minimizing background interference.

Figure 5: Molecular structures of capping agents citrate (top left), tannate, (right), and borate (bottom left).

The LODs for the different capping agents, nanoparticle materials, and excitation wavelengths are shown in Table 2. The best performing combination was the AuNPs



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18 with borate capping agent at 633 nm for which the spectral and calibration data is shown in Figure 6 (spectral and calibration data for other experimental conditions are reported in the Supporting Information). AuNPs with the borate capping agent present a very clean background in comparison with citrate and tannate capping agent and appears to be easily displaced by the analytes under consideration. The second best performing combination was AuNPs with a citrate capping agent, although significant background interference from the citrate capping agent remains (Figure S10, Supporting Information). The tannate capped AuNPs gave relatively poor results in comparison to the other two capping agents, mainly due to the presence of a very strong, broad background that interfered with the analyte signals. Overall the limits of detection of the AuNPs for the citrate and borate capped experiments were observed to be 1-2 orders of magnitude lower than those obtained with the AgNPs for any capping agent. A limited study was also conducted at 785 nm with the AuNPs and the same background issues encountered with citrate and tannate as were at 633 nm. The borate capped AuNPs, while background free at 785 nm, gave limits of detection that were at least one order of magnitude worse that at 633 nm. Morphine consistently registered a limit of detection 1-2 orders of magnitude lower than cocaine or methamphetamine with all nanoparticles and capping agent combinations, except with the borate capped AuNPs at 633 nm. The reasons for this likely arises from a combination of factors including a greater ability of morphine to displace the capping agents and bind to the Ag or Au surface, differing Raman cross sections of the analytes, and also the fact that the morphine signals are sufficiently isolated from the background signals of the capping agents that they can be more easily observed. With the AuNPs, the isolation of the morphine signals from the background signals may be primarily responsible for the lower detection limits, especially since with the background-free borate capped AuNPs cocaine and methamphetamine could be


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19 observed at comparable concentrations with morphine. The reasons for the lower limits of detection with AgNPs are difficult to determine confidently. Table 2: Limits of detection for different excitation wavelengths, nanoparticle materials, and capping agents for the different analytes. Excitation Wavelength

Nanoparticle Material

Capping Agent

Morphine

Cocaine

Methamphetamine

Ag

Citrate

8 x 10-6 M ±4 x 10-6 M

3 x 10-5 M ±4 x 10-6 M

9 x 10-5 M ±3 x 10-5 M

Tannate

2.3 x 10-6 M ±3 x 10-7 M

1.2 x 10-5 M ±7 x 10-7 M

1.8 x 10-5 M ±1 x 10-6 M

Borate

3.2 x 10-6 M ±5 x 10-7 M

3 x 10-5M ±4 x 10-6 M

3 x 10-4 M ±1 x 10-4 M

Citrate

2.9 x 10-6 M ±3 x 10-7 M

1.8 x 10-5 M ±2 x 10-6 M

3 x 10-5 M ±5 x 10-6 M

Tannate

5.0 x 10-6 M ±1 x 10-6 M

1.9 x 10-5 M ±2 x 10-6 M

4 x 10-5 M ±6 x 10-6 M

Borate

1.4 x 10-6 M ±1 x 10-7 M

3.0 x 10-5 M ±4 x 10-6 M

3 x 10-4 M ±7 x 10-5 M

Citrate

4.8 x 10-8 M ±1 x 10-8 M

9 x 10-7 M ±3 x 10-7 M

1 x 10-6 M ±1 x 10-7 M

Tannate

2.1 x 10-5 M ±3 x 10-6 M

1.0 x 10-4 M ±7 x 10-6M

5 x 10-4 M ±3 x 10-4 M

Borate

4.7x 10-8 M ±9 x 10-9 M

1.5 x 10-8 M ±1 x 10-9 M

3.0 x 10-8 M ±4 x 10-9M

532 nm

633 nm

Ag

Au

1200

1200

1200

1000

1000

1000

800

Counts

1400

Counts

1400

Counts

1400

800

600

600

400

400

400

600

800

1000

1200

1400

1600

1800

2000

400

600

Raman Raman Shift Shift (cm-1) (cm-1)

3500

800

1000

1200

1400

1600

1800

1e-5M 5e-6M 1e-6M 5e-7M 1e-7M 9e-8M 8e-8M 7e-8M 6e-8M 5e-8M 4e-8M 3e-8M 2e-8M 1e-8M Water

800

600

400

400

2000

600

Raman RamanShift Shift (cm-1) (cm-1)

12000

R2=0.9466 2 R =0.9466 10(±4 x 109)*x y=-30(±300)+3.0 x 10 10 y = -33.1+2.96 x 10 *x

2500

R2=0.9748 R =0.9748 y=-4600(±700) +1.4 x 1011(±1 x 1010)*x y = -4550+1.37 x 10 *x

1000

1200

1400

1600

1800

2000

R2=0.7695 R =0.7695 y=-300(±300) +1.9 x 1010(±4 x 109)*x 2

2

10000

800

Raman RamanShift Shift (cm-1) (cm-1)

y = -320+1.87 x 1010*x

10

2000

3000

8000

Peak Area

2500

2000

Peak Area

1500

Peak Area

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


6000

4000

1000

500

2000 1500

0

0

1000 4.0e-8

5.0e-8

6.0e-8

7.0e-8

8.0e-8

9.0e-8

1.0e-7

1.1e-7

-2000 3.0e-8

-500

4.0e-8

5.0e-8

6.0e-8

7.0e-8

8.0e-8

9.0e-8

1.0e-7

1.1e-7

Concentration (M)

Concentration (M)

0.0

2.0e-8

4.0e-8

6.0e-8

8.0e-8

1.0e-7

1.2e-7

Concentration (M)

Figure 6: Spectral (top panel) and calibration data (bottom panel) for each of the analytes using the borate capped, 30 nm Au colloid at 633 nm. The left column is methamphetamine, middle column is cocaine, and right column is morphine. Calibration data was constructed using peak area for 1000 cm-1 SERS band of methamphetamine, 1001cm-1 SERS band cocaine, and 627 cm-1 SERS band of morphine. The linear portion of the analytes’ concentration profile was isolated and the line of best fit was determined using a least squares fitting algorithm. The concentrations were determined by taking 3* the standard error in the yintercept divided by the slope of the

line.



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20 It is reported that Ag is a more efficient plasmonic material than Au.39,41,42,58 While that may be true our results show AuNPs demonstrate a better LOD than AgNPs. The LOD values not only depend on plasmonic efficiency of the substrate but also on the binding affinity of the chemical to that substrate. Several studies examining the binding of nitrogen containing compounds to different metals including Ag and Au have been conducted.74-76 Acioli and Srinivas74 studied nucleobase binding to Ag and Au. The authors found that both Ag and Au bind the nucleobases though a nitrogen site and that an Au surface had twice the binding energy of an Ag surface. Jang75 looked at the binding of DNA nucleosides to AuNPs and determined the binding predominately occurred through nitrogen sites of an imidazole or pyrimidine ring and that binding to an Au surface will happen more readily through a nitrogen atom rather than through a competing binding site such as a carbonyl group. Wu et al.76 examined the binding of pyridine to a series of metals: Cu, Ag, Au, Ni, Pd, and Pt and actually found that the binding between Ag and pyridine was the weakest out of all the metals studied. These results are significant and related to our experiments for a couple of reasons. First, when several functional groups are available for binding to a metal, the main binding mechanism was found to be through the nitrogen atom even in the presence of other functional groups that through which the analyte could potentially bind.74,76 Given that the drug molecules examined in this study have nitrogen sites available for binding (in addition to –OH, C=O in some cases) it is reasonable to think the predominant binding mechanism will be through the nitrogen atoms in the drugs. Nitrogen containing compounds were found to have a higher propensity to bind to Au than to Ag.74,75 This higher binding affinity for AuNP more than offsets the lower plasmonic efficiency compared to AgNP resulting in a lower LOD.


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21 The Department of Health and Human Services (HHS) has issued guidelines of physiological concentrations of drugs that would constitute a positive initial test for cocaine (150 ng/mL), methamphetamine (500 ng/mL) and morphine (2000 ng/mL).77 As this combined microfluidic/SERS platform is being developed as a portable drug detection device to initially identify individuals under the influence and also to potentially rapidly identify drugs in point-ofcare settings, it is imperative to verify that the analytical method can detect physiologically relevant concentrations of illicit drugs. The LODs obtained for morphine (4.7x 10-8 M ±9 x 109

M, 13 ng/mL ±2 ng/mL), cocaine (1.5 x 10-8 M ±1 x 10-9M, 4.6 ng/mL ±0.3 ng/mL ) and

methamphetamine (3.0 x 10-8 M ±4 x 10-9M, 4.5 ng/mL ±0.6 ng/mL) are well within the ranges of physiologically relevant concentrations to determine drug exposure indicating that this would be an appropriate method for use in the field. A comparison between the LODs of various techniques both laboratory based and portable is presented in Table 3. While the laboratory based techniques using chromatography and/or mass spectrometry approaches do achieve better LODs, the LODs reported from other portable methods are comparable to what was achieved in this study.



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22 Table 3: Comparison of LOD of different techniques for detection in various matrices.

Analysis Method Electrophoresis-electrospray ionization ion trap mass spectrometry (lab based)12 Ultra HPLC-quadrupole time of flight mass spectrometry (lab based)78 Gas chromatography/mass spectrometry (lab based)8 SERS with fused gold colloids in glass (portable)79 Dynamic SERS and support vector machines (portable)80 SERS with borate capped AuNPs (current study)

Matrix Hair

Analyte Morphine Cocaine Amphetamine Cocaine Cocaine

LOD 0.05 ng/mg 0.015 ng/mg 0.040 ng/mg 0.5 ng/mL 0.2 ng/mL

Saliva

Methamphetamine Cocaine Cocaine

5 ng/mL 5 ng/mL 10 ng/mL

Urine

Methamphetamine

100 ng/mL

Aqueous

Morphine Cocaine Methamphetamine

13 ng/mL 4.6 ng/mL 4.5 ng/mL

Urine Blood Saliva

CONCLUSIONS An investigation of SERS conditions exploring nanoparticle size, nanoparticle material, nanoparticle capping agent, and excitation wavelength has been presented. The study was carried out to determine optimal SERS conditions for detecting drugs using Au and Ag nanoparticles as a SERS substrate for implementation in a microfluidic device. The optimal sizes for the AgNPs and AuNPs were found to be 50 nm and 60 nm, respectively. The best performing nanoparticle material, capping agent, and excitation wavelength were found to be AuNPs with a borate capping agent using 633 nm laser excitation. The borate capping agent on the AuNP provided a very clean background that did not interfere with the analyte signals and were readily displaced in the presence of analyte molecules. The limits of detection observed for the methamphetamine, morphine, and cocaine tests analytes were in the 1.5-4.7 x 10-8M (4.5-13 ng/ml) range which are acceptable LODs under HHS standards for initial testing for the presence of a drug and are consistent with other competing portable technologies.


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23 ACKNOWLEDGEMENTS The authors would like to acknowledge Tracey Hamilton of the U.S. Army Medical Research Institute of Chemical Defense, Gunpowder, Maryland for the TEM images of the borate capped nanoparticle solutions. Opinions, interpretations, conclusions and recommendations are those of the authors and are not necessarily endorsed by the United States Government. This research was supported in part by an appointment to the Student Participation Research Program at the U. S. Army Edgewood Chemical Biological Center administered by the Oak Ridge Institute for Science and Education through an interagency agreement between the U. S. Department of Energy and ECBC. Funding was provided by the U. S. Army through PE0602622A Project 552, “Forensic Analysis of Explosives”, and the Institute for Collaborative Biotechnologies through contract no. W911NF-09-D-0001 from the U.S. Army Research Office. References 1. United Nations Office on Drugs and Crime. Drug Trafficking and the Financing of Terrorism Retrieved from https://www.unodc.org/unodc/en/frontpage/drug-trafficking-and-thefinancing-of-terrorism on April 8, 2016. 2. National Institute on Drug Abuse. Nationwide Trends Retrieved from https://www.drugabuse.gov/publications/drugfacts/nationwide-trends on April 11, 2016. 3. Washington Times. Terrorist Organizations Still Profit from Afghan Drug Trade Retrieved from http://www.washingtontimes.com/news/2013/sep/20/terrorist-organizations-stillprofit-afghan-drug-t/ on April 11, 2016. 4. UNODC. World Drug Report 2012, United Nations Publications, Sales No. E.12.XI.1; United Nations: New York, 2012. 5. Stojanovska, N.; Fu, S. L.; Tahtouh, >; Kelly, T.; Beavis, A.; Kirkbride, K. P. Forens. Sci. Int. 2013, 224, 8-26. 6. Cone, E. J. Ann. N. Y. Acad. Sci. 1993, 694, 91-127. 7. Welter, J.; Meyer, M. R.; Kavanaugh, P.; Maurer, H. H. Anal. Bioanal. Chem. 2014, 406, 1957-1974. 8. Strano-Rossi, S.; Colamonici, C.; Botre, F. Anal. Chim. Acta 2008, 606, 217-222. 9. Gaillard, Y. P.; Cuquel, A. C.; Boucher, A.; Romeuf, L.; Bevalot, F.; Prevosto, J. M.; Menard, J. M. J. Forens. Sci. 2013, 58, 263-269 10. Saber Tehrani, M.; Givianrad, M. H.; Mahoor, N. Anal. Methods2012, 4, 1357-1364. 11. Pujol, M. L.; Cirimele, V.; Tritsch, P. J.; Villain, M.; Kintz, P. Forens. Sci. Int. 2007, 170, 189-192. 12. Gottardo, R.; Bortolotti, F.; De Paoli, G.; Pascali, J. P.; Miksik, I.; Tagliaro, F. J. Chromatogr. A 2007, 1159, 185-189.



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27

TOC Figure



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108x126mm (72 x 72 DPI)


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Optimization of Surface-Enhanced Raman Spectroscopy Conditions

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