Mosaic-like Silver Nanobowl Plasmonic Crystals as Highly Active

Jul 9, 2015 - (3, 4) Briefly, a master with a photoresist pattern of a square array of cylindrical NWs on a SiO2/Si substrate is replicated using a mi...
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Mosaic-like Silver Nanobowl Plasmonic Crystals as Highly Active Surface-Enhanced Raman Scattering Substrates Alfred J. Baca,*,† Joshua Baca,† Jason M. Montgomery,*,‡ Lee R. Cambrea,† Peter Funcheon,‡ Linda Johnson,† Mark Moran,† and Dan Connor† †

Chemistry Department, U.S. Navy NAVAIR-NAWCWD, China Lake, California 93555, United States Department of Chemistry and Physics, Florida Southern College, Lakeland, Florida 33801, United States

‡

S Supporting Information *

ABSTRACT: We present a simple approach to creating a type of surface-enhanced Raman scattering (SERS) substrate composed of a mosaic-like structured Ag metal surface on nanobowl plasmonic crystals (NBPCs) formed by combining soft nanoimprinting and substrate (in situ) heating during metal deposition. This new type of sensor exploits the electromagnetic enhancement of localized surface plasmon resonances (LSPR) produced by a template nanostructured metal surface and surface plasmons (SP) in-between the gaps of the mosaic surface to create a highly SERS-active substrate. Our approach is simple, in that it implements low processing temperatures (200 °C) and does not require any postdeposition annealing or exposure to high temperature environments, enabling the use of mechanically flexible substrates. These SERS substrates exhibit higher SERS intensities in comparison to those obtained with the corresponding square array of smooth (room temperature metal deposition) nanobowl structures with similar spatial layouts. As an example toward an application, we demonstrate polychlorinated biphenyl (PCB-77) SERS detection using Ag mosaic NBPC substrates. Three-dimensional finitedifference time-domain (3D FDTD) simulations qualitatively capture the key features of these systems and suggest a route to the fabrication of optimized, highly efficient SERS substrates in silico. Raman-active substrate.10 Other approaches rely on the selfassembly of particles14 and/or polystyrene spheres26 to generate templates for metal deposition. These methods are fast and can be low-cost approaches to generating Raman-active templates. For example, Shiohara et al.14 recently reported very interesting work in the area of gold nanostar−satellite clusters in which they were able to control the deposition of nanospheres onto gold nanostars to generate multiple hotspots. These methods to create self-assembled features with sharp edges represent a promising approach to SERS substrate fabrication. Other approaches for SERS substrate fabrication implement the use of anodic alumina oxide (AAO) disks or the selfassembly of polystyrene nanobeads to generate nanotemplates.5,8,15 Chen et al.5 recently reported the formation of a gold nanobowl template loaded with Ag nanoparticles, and promising results for the rapid detection of polychlorinated biphenyls were demonstrated in this work. However, a possible disadvantage of these approaches is that rely on cumbersome methods to generate templates that show modest control of spatial dimensions over large areas. This limitation might preclude their use in more advanced SERS detection schemes. So despite this previous, important work on nanostructures for

1. INTRODUCTION Surface-enhanced Raman scattering was first discovered in the 1970s,1,2 and although several decades have passed since its discovery, there remains a great deal of interest in the topic.3−17 The field is mature, and SERS is considered a powerful tool for use in biosensing applications due to its ability to determine structural information on a species near or bound to a plasmonically enhanced or roughened metal surface. Some of the earliest and more simplistic SERS substrates implemented a coarse or roughened metal surface or randomly distributed noble metal nanoparticles. Recent advances in nanofabrication processing18−20 and the introduction of new fabrication techniques,21−25 combined with stronger theoretical modeling tools,13 have generated a new class of highly SERS active substrates. There remains a need to develop SERS substrates that are low cost, easy to manufacture, and capable of reproducible SERS outputs for the practical implementation of SERS in biosensing and chemical detection applications. Traditional SERS substrates typically harness enhancements from surface plasmon excitations in the gaps formed in metallic nanoparticle clusters or in nanostructured metallic films. More recent work in the fabrication of SERS substrates exploits multiple enhancement mechanisms on a single substrate for sensing applications in a way that increases the sensitivity of the substrates. For instance, Maznichenko et al. generated a unique 3-D network of titanium dioxide that showed multiple modes of SERS mechanisms occurring from a traditionally non© XXXX American Chemical Society

Received: April 21, 2015 Revised: July 6, 2015

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determined from our measurements and that from our previous work with nanowell and nanopost plasmonic crystals.3,4 The soft imprinting process begins with dicing transparent or frosted glass slides (reflection optical measurements) into 1 in. × 1 in. substrates. The diced glass slides are submerged in a 1% solution of Micro-90/water in a beaker which is then placed in a Maxomatic ultrasonic shaker for 15 min. The substrates are thoroughly rinsed with acetone followed by isopropyl alcohol and deionized water. The glass substrates are then heated on a hot plate at 250 °C for 1 min to evaporate any residual water from the cleaning process and carefully placed on the spincoater. A dropper is used to cover roughly 2/3 of the substrate with SU8-(5). The substrate is then spin-coated with vacuum spin-coater in a three-step program: (step 1) 10 s of spinning at 1000 rpm, (step 2) 60 s of spinning at 2000 rpm, and (step 3) 5 s of spinning at 500 rpm. The SU8-(5)-coated substrate is then prebaked on a hot plate again for 5 min at 120 °C to evaporate any residual solvent. The replicated stamp is coated with two drops of ethanol and subsequently placed into contact with a thin layer (∼6 μm) of SU-8 photoresist spin-coated on a glass slide and allowed to imprint for 1 h. The stamp is then carefully removed from the substrate, and the substrate is exposed to a UV light source for 3 min. The cross-polymerized substrate is then thermally acclimated for future heating in a deposition chamber by placing it on a hot plate at 200 °C for 30 min. Deposition of a thin Ag metal layer (10, 25, and 50 nm) using an AJA International hybrid electron beam/sputter-coating chamber at a rate of 0.1 Å/s and deposition pressure of ∼1.5 × 10−7 Torr onto the completed soft nanoimprinted structures at range of temperatures (i.e., range between 22 and 220 °C) completes the fabrication of the SERS substrates. 2.3. Transmission, Reflection, and Raman Characterization. Transmission and reflection measurements for smooth and mosaic nanobowl plasmonic crystals were measured with a Varian 5G UV−vis−NIR. The samples were adhered onto a sample holder with a 1 mm aperture. The samples were prepared for SERS measurements by soaking the Ag metal coated mosaic and smooth plasmonic arrays in a 15 mM solution of BT in ethanol for 1 h immediately after depositing the Ag metal film, rinsing with copious amounts of ethanol, and drying with nitrogen. For PCB studies, both smooth and mosaic Ag NBPC substrates were functionalized with DT by exposing the substrates for ∼12 h to a 10 mM solution of DT in ethanol. PCB-77 was diluted to 5 mM in acetone, and samples were placed in contact with the PCB-77, air-dried, and characterized afterward. The detection substrate for PCB used in this paper consisted of DT modified mosaic Ag surface. The SERS spectra were collected with a Nicolet Almega XR dispersive Raman microscope (Thermo Electron Corp., Madison, WI) using a 785 nm excitation laser source and an Olympus 10× MPlan objective. A 50 μm pinhole was used as the spectrograph aperture. The resolution is ∼9−17 cm−1 with a spot size of ∼3 μm, and each spectrum is an average of three scans with a 10 s integration time. Scanning electron microscopy (SEM) measurements were performed on a Carl Zeiss Supra55 FESEM (field emission SEM), and atomic force microscopy (AFM) imaging and analysis were performed with Asylum MFP-3D AFM and Argyle software, respectively. 2.4. FDTD Calculations. To model the interactions of light with our nanostructures, we used three-dimensional finitedifference time-domain (3D-FDTD) simulations to solve Maxwell’s curl equations for the electric (E) and magnetic (H) fields. In the FDTD approach, E and H are represented on

SERS, there remains interest in new SERS substrates that can complement or extend established methods for SERS detection. Recently, an alternative strategy has been demonstrated that relies on the use of deterministic, low-cost printing approaches (i.e., soft lithography) for the fabrication of SERS-active substrates.3,4,27 The advantages of deterministic routes to the assembly of nanostructures include the low cost processing, the scalability to large areas, and the potential for engineering in silico for operation at various wavelengths all on the same substrate. These advantages make printing approaches that rely on soft lithographic patterning very attractive to most envisioned SERS applications. Our recent work3,4 demonstrated the use of soft nanoimprinted relief features composed of nanowells or nanoposts as highly active SERS substrates that rely on the use of plasmonic enhancement for garnering a SERS response. Herein, we report a new type of soft imprinted polymer nanobowl template with a mosaic silver surface formed in situ by controlled heating during metal deposition via electron beam evaporation. We believe these substrates combine enhancements generated from plasmonic modes on the structurally ordered template and plasmonic modes generated from nanogap formation within the metal clusters on the mosaic surfaces. These templates are generated at relatively low temperatures (mosaic formation starts at 100 °C but optimal surfaces are produced at 200 °C) and do not require high temperature environments, thus enabling their use with plastic substrates. As an analytical application of these substrates we demonstrate the detection of an environmentally persistent contaminant polychlorinated biphenyl-77. Cost effectiveness, easy fabrication, and the ability to engineer their SERS response in silico suggest a strong potential for various uses in sensing and other applications.

2. EXPERIMENTAL DETAILS AND COMPUTATIONAL STUDIES 2.1. Materials. Reagents and materials were used as received without further purification. Poly(dimethylsiloxane) (s-PDMS, Sylgard 184, Dow Corning) was purchased from Ellsworth Adhesives. Materials used for the fabrication of hard PDMS (h-PDMS), such as 25−30% methylhydrosiloxane− dimethylsiloxane copolymer (HMS-301), 7−8% vinylmethylsiloxane−dimethylsiloxane copolymer (VDT-731), platinum− divinyltetramethyldisiloxane complex in xylene (SIP6831.2), and 1,3,5,7-tetravinyl-1,3,5,7-tetramethylcyclotetrasiloxane (SIT7900.0), were all purchased from Gelest. SU-8 5 was purchased from Microchem products. Frosted and plain glass slides were purchased from Fisher Scientific. Ag pellets (99.99%) were purchased from Kurt Lesker. Benzenethiol (BT), decanethiol (DT), and polychlorinated biphenyl-77 (PCB-77) were purchased from Aldrich. 2.2. Fabrication of Ag Smooth and Mosaic Nanobowl Plasmonic Crystals. Soft nanoimprint lithography was used for fabricating smooth and mosaic plasmonic crystal arrays as shown in our previous work.3,4 Briefly, a master with a photoresist pattern of a square array of cylindrical NWs on a SiO2/Si substrate is replicated using a mixture of h-PDMS and s-PDMS to create a soft PDMS replica stamp. The master houses 16 square arrays of diameters (D) and periodicities (P) ranging from ∼0.17 to 1.12 μm with corresponding periodicities from ∼0.5 to 1.75 μm and a relief depth (RD) of ∼0.36 μm. For this work we measured all 16 arrays but focused on only the four plasmonic arrays with diameters and periodicities that provided the highest SERS outputs as B

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nm diameter wells and a periodicity of 718 nm. Ag deposits in the wells were instead modeled by a disk rather than a ring, consistent with Figure 1d. To create the mosaic surface, the height, hz(x,y), of the surface about the xy-plane was simulated using a random distribution of Gaussian functions:

a discrete, staggered grid of points and are propagated in time using a leapfrog algorithm with finite-difference approximations for derivatives.28 The material composition of each grid point was designated by a dielectric constant consistent with the spatial layout of materials in the nanostructure being modeled. Periodic boundary conditions in the x- and y-directions were used to simulate square arrays of NBPCs with twice a given periodicity to produce four unique wells per unit cell in each simulation. Smooth NBPCs were modeled as a 25 nm thick Ag film atop a SU-8 support with 490 nm diameter wells at a periodicity of 722 nm and a depth of 330 nm. To model the Ag deposits within the well, a 100 nm wide ring along the outer edge of the well bottom was used, consistent with Figure 1c. To model the mosaic NBPCs, a similar layout was used with 500

⎛ (x − x )2 + (y − y )2 ⎞ i i ⎟ hz(x , y) = Ai , j ∑ exp⎜⎜ − ⎟ 2 2σi , j ⎝ ⎠ i,j

(1)

where i and j label a Gaussian function centered at (xi, yj) with a randomly chosen standard deviation σi,j between 16 and 20 nm. The factor Ai,j allows one to tune the surface to a desired height range and rms value over the surface. A Gaussian source, located nearly 1000 nm away from the Ag film, polarized in x with a wavelength range of 300−1000 nm was propagated for 200 fs in the z-direction using a total-field scattered-field approach. A grid spacing of 2 nm was used in each dimension which allowed us to model coarse roughness. To model the dispersive relative dielectric constants for silver, εAg(ω), Drude plus two-Lorentzian models were used with parameters described in an auxiliary differential equation approach.3 Refractive indices of air and SU-8 were modeled using nair = 1.0 and nSU‑8 = 1.59, respectively. Transmission and reflection spectra were calculated by taking the ratio of the normal transmitted power to the incident power integrated over planes above and below the structure, corresponding to the zero-order transmission and reflection, respectively. Absorption plots were calculated using %A = 100% − %T − %R. The time-dependent electric field was Fourier transformed at the excitation wavelength λexc = 785 nm and the Raman scattered wavelength λscatt = 896 nm (corresponding to the 1575 cm−1 band) in order to calculate the time-averaged electric field intensity enhancements (g2(x,y,z,λ) = |E(x,y,z,λ)|2/|E0(λ)|2). The overall average SERS response, G4SERS, for a given NBPC array was determined by averaging over the SERS response at each grid point, given by G 4 SERS =

1 N

∑ gexc 2(xi , yj , zk)gscatt 2(xi , yj , zk) i ,j,k

(2)

where N is the number of grid points in the spanned volume, which included the Ag film.

3. RESULTS AND DISCUSSION Our previous work and that of others have demonstrated the use of soft nanoimprint and other nanolithography techniques to generate highly SERS-active surfaces.3,4,24 Herein we demonstrate a substrate that implements nanostructured plasmonic crystals and the formation of nanogaps resulting in a mosaic metal surface for SERS enhancements. Figures 1a and 1b depict schematic representations and images of smooth Ag NBPCs and mosaic NBPCs, respectively. The smooth Ag NBPCs were fabricated by placing a soft nanoimprinted SU-8 glass substrate in a deposition chamber while maintaining a substrate temperature of 22 °C, resulting in a smoother Ag surface as shown in the SEM image of Figure 1c. The substrate heater was set at 100 °C in order to fabricate the mosaic surface shown in Figure 1d. We found the ability to produce mosaic surfaces is highly dependent on the metal thickness and the deposition temperature as we will show later in this discussion. All substrates were heated to a desired temperature, and once thermal equilibrium was reached, the deposition process was started and the samples were allowed to cool back to room

Figure 1. Schematic representation of smooth Ag nanobowl plasmonic crystals (NBPCs) (a) and mosaic Ag NBPCs (b). (c) and (d) depict scanning electron micrographs (SEM) of smooth Ag and mosaic NBPCs, respectively. (e) Partial cross-sectional SEM image of smooth Ag NBPCs and (f) shows a full cross-sectional image of mosaic Ag NBPCs. (g) and (h) show 1 μm × 1 μm atomic force microscopy phase images for smooth and mosaic Ag NBPCs substrates, respectively. (i) Optical image of arrays of mosaic Ag NBPCs fabricated on a flexible Kapton substrate wrapped around a glass vial. C

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Figure 3. (a) 3-D 2.0 μm × 2.0 μm AFM image of mosaic Ag nanobowls. (b) SERS spectra for smooth and mosaic NBPCs formed at 22 °C (diameter = 490 nm; periodicity = 722 nm) and 100 °C (diameter = 500 nm; periodicity = 718 nm) for BT coated arrays. Background for each NBPCs spectrum (red mosaic and black smooth; dotted line) depicted and measured on a nonpatterned area for each correspond array. All spectra were measured with a 785 nm laser excitation source. Figure 2. Experimentally measured transmission (a, b) and reflection (c) spectral characterization for smooth (red graph) and mosaic (black graph) Ag NBPCs formed at 22 °C (diameter = 490 nm; periodicity = 722 nm) and 100 °C (diameter = 500 nm; periodicity = 718 nm). The red and black dotted graphs correspond to a nonpatterned area for (e.g., background) for smooth and mosaic Ag NBPCs. Dotted black line corresponds to laser wavelength used for excitation SERS collection.

temperature inside the chamber prior to removal from the sample holder. Furthermore, the surfaces are electrically continuous as verified by electrodeposition techniques. Figure 1e shows a cross-sectional image of a smooth NBPCs showing the clear separation between the top metal coating and the bottom disk with minimal metal deposition on the sidewalls of the nanostructures. Because of the master used in this work, the bottom disk is shaped more like a nanobowl and not a true nanodisk. The fabrication of the mosaic metal thin film can be partially attributed to the heating of the SU-8 imprinted sample surface, creating a dewetting process for the Ag metal deposition and generating a continuous thin film with nanogaps in a random layout as shown in the cross-sectional image in Figure 1f. The heated surface causes the Ag deposited particles to agglomerate via surface tension effects to form a random array of Ag nanoparticles constructed into a film that is electrically continuous. As the temperature increase, the gap sizes and the size of the Ag nanoislands that form increase. A another factor that changes the deposition characteristics is the

Figure 4. (a) SEM images of Ag Nanobowls fabricated all at 100 °C maintaining a fixed deposition temperature (D = 514 nm and P = 740 nm) but with varying the metal thicknesses. SEM images correspond to (from left to right) 10, 25, and 50 nm. (b) Depicts the corresponding SERS spectra of the above plasmonic arrays with the solid colored graphs showing the SERS of the patterned and arrays and the corresponding (same color) dotted line spectra show the background response (nonpatterned area) for each sampled thickness.

nanobowl templates acting as point defects and altering the nucleation of the Ag metal as well; a similar phenomenon was D

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demonstrated recently using Au nanoparticles thermally heated for SERS.23 We measured the surface roughness of SU-8 on glass (22 °C, Rms = 0.3 nm; 200 °C, Rms = 0.6 nm) heated at the different temperatures which showed small changes in the roughness over the temperature ranges used and minimal changes between the surface morphology of 22 °C vs that of 200 °C were observed (see Supporting Information Figure S1). Figure 1f shows the surface morphology of the mosaic film which is composed of a cluster of Ag metal particles stacked upon each other in a random fashion. Figure 1g and 1h show atomic force microscopy phase images for a nanopatterned area for smooth and mosaic Ag NBPCs, respectively. The phase images illustrate the subtle changes in height differences in the random array and also show some variation in the spacing of the Ag metal clusters. The phase images indicate changes in height and a larger grain size for the Ag mosaic substrates. Typical roughness (Rms) values obtained from our AFM measurements show an Rms = 4.28 nm for smooth NBPCs and an Rms = 3.34 nm for Ag mosaic NBPCs. As a result of our low processing temperatures ( 30 are displayed as white.

Figure 9. Calculated SERS enhancements (g4SERS = g2exc × g2scatt) for smooth and mosaic NBPCs. (a) and (b) contain a portion of a 2D xzslice through the center of two wells of the smooth and mosaic nanobowls, respectively. Similarly, (c) and (d) contain a 2D xy-slice through the center of the film indicated by dashed line in (a) and (b), showing all four wells in each unit cell. All values of g4SERS > 103 are displayed as white. SERS responses on order of 105−106 are seen near the rims of the nanobowls.

of a thin gold adlayer on top of the mosaic Ag might help improve our sample stability. To evaluate the effect of metal thickness on the SERS response of the mosaic NBPCs substrates (BT modified/ adsorbed), we carried out a series of experiments that varied the Ag metal thickness deposited and kept the deposition temperature the same for each substrate. Figure 4a shows representative SEM images of mosaic Ag NBPCs substrates fabricated at various metal thicknesses at a 100 °C deposition temperature. The SEM images from left to right depict Ag NBPCs with 10, 25, and 50 nm Ag metal thicknesses as measured by the QCM of the AJA deposition chamber. The surface morphology for the mosaic structured surface is highly dependent on the metal thickness during the metal evaporation step, changing from a Ag nanoparticle mosaic surface which is a completely discontinuous thin metal film (SEM image on left) to a mosaic Ag surface (middle SEM image) to a smooth Ag G

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can be difficult to model accurately due to variations in structural dimensions and in metal deposits/defects throughout the plasmonic crystal.32,33 Nevertheless, Figures 7e and 7f show that the FDTD models produce absorption spectra that agree qualitatively with experiment and are capable of capturing the key physics in these structures. Of particular interest are those peaks in Figures 7c,d near the excitation and Raman scattered wavelengths (vertical dashed lines). Figures 8a−d show 2D xz-slices of the time-averaged electric field intensity enhancements, g2(x,y,z,λ) = |E(x,y,z,λ)|2/| E0(λ)|2, for a single well for smooth (a, b) and a single well for mosaic (c, d) substrates at λexc = 785 nm and λscatt = 896 nm. The reflection peak at 785 nm excites an LSPR in the rim of the smooth NBPC while the Raman scattered wavelength excites a similar LSPR (centered at 875 nm in Figure 7d) in the rim of the mosaic NBPC. We believe these LSPR resonances play a predominant role in the SERS enhancements seen in the fabricated substrates, and the observed 1.6 increase in the mosaic structure can be attributed to the mosaic gaps in the metal surface. To show this, we calculated the expected electromagnetic contribution to the SERS enhancement for each substrate, which is related to the product of these fields at each point, or g4SERS = g2exc(λexc) × g2scatt(λscatt). Figure 9 shows 2D xz-slices of g4SERS through two wells for the smooth (a) and mosaic (b) substrates, showing the contributions of the LSPR in the rims of each well. Figures 9c and 9d show 2D xy-slices of g4SERS through the center of the top Ag film in each substrate. It is clear that the coupling of the mosaic gaps and the hole in the mosaic NBPC gives rise to larger electric field enhancements at the excitation and scattered wavelengths. To determine the actual improvement, an average SERS response, G4SERS, was calculated using eq 2 throughout a volume containing the entire Ag film. The ratio of the average SERS enhancement of the mosaic to the smooth substrate was 2.6, very close to the observed 1.6. The average SERS response calculated using eq 2 was an order of magnitude larger for the mosaic than the smooth NBPC, suggesting the tailored use of nanogap formation with patterned nanostructures can drastically enhance the sensitivity of a SERS substrate. Therefore, while the FDTD modeling presented herein was not used for a quantitative description or optimization of the mosaic substrates, it did provide a more qualitative picture of the plasmonic nature of the mosaic substrates and the role of the gaps in the mosaic surface.

which all contain controlled amounts of PCB. For example, painted steel components on Navy ships contain regulated amounts of PCBs (>50 ppm), and PCB is found in applied interior paints and primers. Paint must be removed and heated in controlled areas during welding/cutting to prevent migration of PCBs, which can be an environmental hazard for workers. Recently, a great amount of research has been performed in the detection of PCB using SERS-active substrates.15,30 To show the analytical utility of our mosaic Ag surfaces, we measured the SERS performance of PCB on mosaic surfaces at a concentration of 5 mM. Figure 6a shows an SEM image of an optimized (25 nm Ag thickness; 200 °C deposition) mosaic Ag DT modified substrate.31 The DT modification facilitates the physical “trapping” of PCB molecules and tethers the PCB molecules in the vicinity of the nanobowl rim, where most of the electromagnetic enhancement is generated. The SERS curve (difference curve subtracting DT only) in Figure 6b shows the output of PCB molecules measured using the mosaic NBPCs (diameter = 490 nm; periodicity = 740 nm). To generate these spectra, we used our Raman software to subtract the DT spectra (only DT) minus that of the PCB 5 mM spectra. Please see Supporting Information which shows the Raman spectra for just DT on mosaic surface, DT plus PCB on a mosaic, and the powder bulk PCB 77 Raman data. Modification of the Ag surface with DT shows a clear fingerprint region of PCB molecules denoted by dotted lines in Figure 6b. With further optimization, lower levels should be detectable with our Ag mosaic surface. In order to ascertain the role of the nanogaps in the Ag surface for observed enhancements in the SERS response for the mosaic substrates in the BT study, we compared 3D-FDTD simulations of a smooth NBPC geometry to a “mosaic-like” geometry. Figure 7a contains an illustration of the smooth NBPC substrate model, which consisted of a 25 nm Ag film atop an SU-8 support with 490 nm diameter, 330 nm deep wells with a periodicity of 722 nm. A 100 nm Ag cylindrical ring was used to model the nanobowl in the bottom of the well, consistent with Figure 1c. Figure 7b contains an illustration of mosaic NBPC substrate model, for which a rough mosaic-like surface was generated in the z-direction according to eq 1 with a minimum height of 9 nm, a maximum height of 25 nm, and an average height of 19 nm over a xy-range of 1436 nm × 1436 nm, twice the desired periodicity in each direction. Each socalled unit cell then consisted of a rough metal film atop an SU8 support and a 2 × 2 square array of 500 nm diameter, 330 nm deep wells at a pitch of 718 nm (Figure 7b contains only one of these wells). A rough disk with the same parameters above was used to model the nanobowl in the bottom of each well, consistent with Figure 1f. Periodic boundary conditions were applied to create the full plasmonic crystal. By constructing the mosaic NBPC in this way, any effects due to the periodic boundary conditions on the random rough surface itself would mainly appear outside the spectral range of interest. Figures 7c and 7d contain the calculated transmission and reflection spectra of mosaic (black) and smooth (red) arrays, respectively. Figures 7e and 7f contain absorption spectra approximated as %A = 100% − %T − %R for the mosaic and smooth substrates, respectively, as well as the experimental absorption (gray) corresponding to the curves in Figure 2. A comparison between the simulated spectra and those provided in Figure 2 shows that the FDTD substrates give rise to starker spectral features owing to their perfectly periodic nature. Spectral features in the fabricated surfaces are less apparent and

4. CONCLUSIONS In conclusion, we have presented experimental and theoretical results of mosaic nanostructured Ag nanobowl plasmonic crystal arrays formed by soft imprint lithography combined with in situ heating during metal deposition. This simple and easy to use method affords the fabrication of mosaic nanostructured SERS substrates with good spatial uniformity and reproducible SERS response in contrast to SERS substrates fabricated via room temperature metal deposition and certain colloid assembly methods. The as-produced substrates are highly versatile, and the process lends itself to large area fabrication of unusual format optical nanostructures for applications in sensing and other emerging areas in nanophotonics. Our theoretical analysis shows that FDTD modeling also demonstrates the ability to engineer the SERS response for both smooth and mosaic nanobowl structures in good qualitative agreement with theoretical predictions, suggesting a route to high performance SERS substrates in silico. We show H

DOI: 10.1021/acs.jpcc.5b03824 J. Phys. Chem. C XXXX, XXX, XXX−XXX

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The Journal of Physical Chemistry C

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that careful selection of metal thicknesses and deposition temperature is critical to the production of substrates showing large SERS enhancements. Fully optimized mosaic NBPC arrays can be used for the detection of a persistent environmental toxin, PCB-77, suggesting possible uses of mosaic NBPC for applications in environmental monitoring and other sensing applications.

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ASSOCIATED CONTENT

S Supporting Information *

SEM and AFM images of SU-8 films at 22 °C and 200 °C; SERS spectra of (bulk) powder PCB-77, decanethiol, and PCB with decanethiol. The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/ acs.jpcc.5b03824.

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AUTHOR INFORMATION

Corresponding Authors

*E-mail [email protected] (A.J.B.). *E-mail jmontgomery@flsouthern.edu (J.M.M.). Author Contributions

A.J.B. and J.M.M. designed the research and directed the work. J.B. performed all of the SERS measurements, calculated the results, and fabricated all of the samples. J.M.M. led the modeling research with help from P.F., L.R.C., L.J., M.M., and D.C. helped characterize the samples. A.J.B, J.B., and J.M.M. wrote the manuscript and discussed the results. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work was supported by the NAVAIR In-House Laboratory Independent Research (ILIR) program managed by Scott Munro. A.J.B. thanks Prof. John A. Rogers and Prof. Ralph G. Nuzzo for generously donating masters used in this work. The computational portion of this research used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract DE-AC02-05CH11231. J.M.M. and P.F. thank Jeffrey M. McMahon for his parallel 3D FDTD code.

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REFERENCES

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DOI: 10.1021/acs.jpcc.5b03824 J. Phys. Chem. C XXXX, XXX, XXX−XXX

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