Topographically Flat Nanoplasmonic Sensor Chips for Biosensing and

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Topographically Flat Nanoplasmonic Sensor Chips for Biosensing and Materials Science Ferry Ardy Anggoro Nugroho, Rickard Frost, Tomasz J. Antosiewicz, Joachim Fritzsche, Elin Maria Larsson Langhammer, and Christoph Langhammer ACS Sens., Just Accepted Manuscript • DOI: 10.1021/acssensors.6b00612 • Publication Date (Web): 09 Dec 2016 Downloaded from http://pubs.acs.org on December 12, 2016

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Topographically Flat Nanoplasmonic Sensor Chips for Biosensing and Materials Science

Ferry A. A. Nugroho1, Rickard Frost1, Tomasz J. Antosiewicz1,2, Joachim Fritzsche1, Elin M. Larsson Langhammer3,* and Christoph Langhammer1,*

1

2

Department of Physics, Chalmers University of Technology, 412 96 Göteborg, Sweden

Centre of New Technologies, University of Warsaw, Banacha 2c, 02-097 Warsaw, Poland 3

Insplorion AB, Medicinaregatan 8A, 413 90 Göteborg, Sweden

Corresponding authors: *[email protected]; *[email protected]

ACS Paragon Plus Environment

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ABSTRACT

Nanoplasmonic sensors typically comprise arrangements of noble metal nanoparticles on a dielectric support. Thus they are intrinsically characterized by surface topography with corrugations at the 10–100 nm length scale. While irrelevant in some bio- and chemosensing applications, it is also to be expected that the surface topography significantly influences the interaction between solids, fluids, nanoparticles and (bio)molecules, and the nanoplasmonic sensor surface. To address this issue, we present a wafer-scale nanolithography-based fabrication approach for high-temperature compatible, chemically inert and topographically flat and laterally homogeneous nanoplasmonic sensor chips. We demonstrate their sensing performance on three different examples, for which we also carry out a direct comparison with a traditional nanoplasmonic sensor with representative surface corrugation. Specifically, we (i) quantify the film-thickness dependence of the glass transition temperature in poly(methyl metacrylate) thin films, (ii) characterize the adsorption and specific binding kinetics of the avidin – b-BSA protein system and (iii) analyze supported lipid bilayer formation on SiO2 surfaces.

KEYWORDS plasmonic sensor, flat topography, surface corrugation, polymer glass transition, supported lipid bilayer formation, avidin adsorption, b-BSA specific binding


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The sensing functionality in nanoplasmonic sensors stems from noble metal nanoparticles, which exhibit optical properties that are distinct from the bulk due to the excitation of localized surface plasmon resonance (LSPR).1 When the LSPR is excited, the polarization of electrons in the nanoparticle, induced by the incoming photons, creates locally enhanced electric fields. These make plasmonic nanoantennas sensitive probes for the detection of changes in their local surroundings, e.g., the refractive index of a solid or a fluid, or the binding of molecular species to the nanoantenna surface.2 Hence, plasmonic antennas have been widely explored in nanoplasmonic bio- and chemosening,3,4 as well as in materials science applications.5 However, as a natural consequence of the nanoparticulate nature of the individual plasmonic sensor entities, when they are deposited or grown on the surface of a sensor chip to be used in a device, they will create surface corrugations at the tens to hundreds of nanometers length scale. While in some applications this is not a significant concern (or sometimes even an advantage6,7), the surface topography may also significantly influence the interaction between fluids, thin films, (bio)molecules and nanoparticles, and the nanoplasmonic sensor surface.6–11 Therefore, if the plasmonic nanoantennas are to be employed as non-invasive probes for the investigation of a physical or chemical process in a nanomaterial5 or in a biomolecular system,3,12 this constitutes a significant problem because the response obtained will most likely be affected by the presence of the plasmonic nanoprobes. For example, it is well known that biomolecules, such as lipids and proteins, form adlayers that are very sensitive to surface curvature at the nanoscale.6,7,10,13–17 Despite the obvious benefits of planar nanoplasmonic sensor surfaces in this context, reports of such structures are lacking in the literature, with the exception of the work by Jose et al.18 In their work they presented a topographically flat nanoplasmonic sensor substrate fabricated using a polymer-based template stripping approach. While this work elegantly demonstrates the


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functionality of a planar nanoplasmonic sensor surface in a study of supported lipid bilayer (SLB) formation, it does not make any direct comparison between flat and corrugated nanoplasmonic sensor surfaces. Moreover, the fabricated structures suffer from limitations imposed by the fact that they are constructed using polymeric materials, in particular poly(dimethylsiloxane) (PDMS). For example, experiments at elevated temperatures or in chemically harsh environments are not possible, and PDMS may lead to sample contamination19 and is not compatible with cleanroom environments, which can complicate integration in nanodevices. Here we address these specific limitations, as well as the general processing challenges in making planar surfaces with embedded metallic nanostructures, by presenting a wafer-scale nanolithography-based

fabrication

approach

for

high-temperature

compatible

and

topographically flat nanoplasmonic sensor chips, where the metallic structures are homogeneously embedded in an ultrasmooth (sub-1 nm roughness) silica matrix. For this purpose we use hole-mask colloidal lithography (HCL),20 reactive ion etching (RIE) and plasmaenhanced chemical vapor deposition (PECVD). Beyond structural characterization and careful analysis of the bulk refractive index sensitivity of these sensors, we demonstrate their sensing performance on three different examples, for which we also carry out a direct comparison with traditional nanoplasmonic sensor chips comprising the same type amorphous arrays of silicaembedded Au nanodisks but protruding from the surface. Specifically, we (i) quantify the filmthickness dependence of the glass transition temperature, ܶ௚ , in poly(methyl metacrylate) – PMMA – thin films, (ii) characterize the adsorption and specific binding kinetics of the avidin – b-BSA protein system, and (iii) analyze SLB formation, to fully assess the potential of our flat


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sensor chips and benchmark them towards the established indirect nanoplasmonic sensing (INPS) platform21 with corrugated surface.

Experimental Section Nanofabrication of Topographically Flat Nanoplasmonic Sensor Chips: A schematic of the fabrication process is presented in the Supporting Information SI to complement the short description given here. The fused silica substrate was first cleaned by 5 min ultrasonication in acetone and rinsing in isopropanol, followed by blow-drying in an N2 stream. Subsequently, an oxygen plasma ash was applied to remove organic contaminants. A sacrificial layer of poly(methyl methacrylate) (PMMA, Microchem Corporation, 4 wt. % diluted in anisole, Mw = 950000) was spin-coated onto the substrate at 2000 rpm for 1 min, followed by soft baking at 170 oC on a hotplate for 10 min. The sample was then subjected to a 5 s oxygen plasma ash (50 W, 250 mTorr, Plasma ThermBatchtop RIE 95m) to enhance the hydrophilicity of the sample surface.

Subsequently,

a

positively

charged

polyelectrolyte

solution

(poly

diallydimethylammonium, PDDA, Mw = 200000–350000, Sigma Aldrich, 0.2 wt. % in Milli-Q water, Millipore) was pipetted on the sample and incubated for 40 s before rinsing in deionized (DI) water, leaving a thin positively charged layer on the surface. Water-suspended negatively charged polystyrene beads (PS, diameter 100 nm, sulfate latex, Interfacial Dynamics Corporation, 0.2 wt. % in Milli-Q water, Millipore) were then dispersed on the sample surface and left to incubate for 3 min, followed by rinsing in DI water and blow-drying under N2. In the next step, a 20 nm thick Cr film was evaporated onto the sample using a Lesker PVD 225 Evaporator at 5 x 10-7 base pressure and 1 Å s-1 evaporation rate. Then, the PS beads were tapestripped (SWT-10, Nitto Scandinavia AB), leaving a Cr film with 100 nm holes at the positions


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of the stripped PS beads. Reactive oxygen plasma etching (50 W, 250 mTorr, Plasma ThermBatchtop RIE 95m) was then used to selectively remove the PMMA exposed underneath the nanoholes in the masking Cr film all the way down to the fused silica substrate. In the next step, which is the first one deviating from the standard HCL protocol,20 reactive ion etching with NF3 (25 W RF-power for 45 s, at a total pressure of 8 mTorr, and NF3 and N2 flows of 7 sccm and 50 sccm, respectively) was used to create disk-shaped 20 nm deep wells in the fused silica substrate. After the etching, 20 nm Au was evaporated (Lesker PVD 225 Evaporator at 5 x 10-7 base pressure and 1 Å s-1 evaporation rate) onto the sample and through the holes in the Cr mask layer to selectively fill the wells and form Au nanoantenna particles inside them. Subsequently, the PMMA and Cr masks were removed in a lift-off process in acetone and the sample was cleaned in isopropanol. Any remaining resist was then removed using an oxygen plasma ash (50 W, 250 mTorr, Plasma ThermBatchtop RIE 95m) before, as the last step, depositing a 10 nm thick SiO2 layer to cover the disk-shaped Au nanoantennas embedded in the fused silica support and to provide a uniform surface chemistry and flat topography. Finally we note that at this stage also other surface chemistries can be applied by sputtering, chemical vapor deposition, atomic layer deposition, or physical vapor deposition of thin films, to further tailor the surfaces for a specific application. Nanofabrication of Corrugated Nanoplasmonic Sensor Chips: Corrugated plasmonic sensor chips were fabricated following precisely the steps described above, according to the standard HCL protocol,20 however without the RIE process. FDTD Simulations: Numerical calculations were carried out using the FDTD method with a commercial code from Lumerical, Inc. A gold nanodisk (permittivity from Johnson & Christy22) with diameter of 100 nm and thickness of 22 nm is placed in an SiO2 matrix with a refractive


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index of 1.45. The dielectric layer over the disk is 10 nm thick for the embedded flat case, while for the traditional corrugated sensor it conformally encapsulates the nanodisk. We used a totalfield/scattered-field source and employed a 1 nm mesh around the nanodisks. Bulk Refractive Index Sensitivity Measurements: The flat and corrugated sensor chips were mounted in a titanium micro flow cell of an Insplorion XNano system (Insplorion AB, Göteborg, Sweden). A peristaltic pump (Ismatec) was used to establish fluid flow through the chamber. The chips were illuminated using a fiber-coupled halogen lamp (AvaLight-Hal-S, Avantes) while the wavelength-resolved extinction spectra (400–1100 nm) were continuously recorded by a fibercoupled fixed grating spectrometer (AvaSpec-HS-TEC, Avantes). Five different concentrations of Milli-Q water (Millipore) and ethylene glycol (Sigma Aldrich) solution (mixing ratios 100:0, 20:80: 40:60, 60:80 and 80:20 wt. %) were prepared to produce media with refractive index ranging from 1.33 to 1.41. The measurements were done at a constant flow rate of 100 µL min-1 at room temperature with exposure of 8 min to each water:ethylene glycol solution. Polymer Glass Transition Experiments: PMMA (Microchem Corporation, 4 wt. % diluted in anisole, Mw = 950000) films were spincoated on the sensors with different rotating speed to achieve different thicknesses. The latter where then experimentally determined by ellipsometry (J. A. Woollam M2000). For the ܶ௚ experiments, the samples were mounted in a quartz tube gas flow reactor system with optical access (Insplorion X1, Insplorion AB, Göteborg, Sweden), connected to a mass flow controller (Bronckhorst) supplying dry and inert Argon atmosphere at constant pressure of 1 atm. The samples were illuminated using a fiber-coupled halogen lamp (AvaLight-Hal-S, Avantes) while the extinction spectra were collected by a fiber-coupled fixed grating spectrometer (AvaSpec-1024, Avantes). The sample temperature was monitored via a thermocouple in direct contact with the sample surface. The ܶ௚ measurements were carried out


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according to the following procedure: i) The sample was heated to 80 oC and dwelled for 1.5 h. ii) Temperature was reduced to 40 oC. iii) Three cycles of heating/cooling were run in sequence: heating to 200 oC with 5 oC min-1 rate and cooling back to 40 oC. All of the processes described were run under 50 mL min-1 constant flow of Ar to ensure dry and inert conditions. The results reported in the main text were obtained from the second heating scan since the first heating scan was used to equilibrate the polymer after spin coating. Protein Adsorption Experiments: Commercial avidin and b-BSA (Sigma Aldrich) were diluted with Milli-Q water to a final concentration of 1 mg mL-1. From the stock solution, 20 µg mL-1 avidin and b-BSA diluted in phosphate buffered saline (PBS) were prepared. PBS was prepared from tablets (the tablets yields 0.01 M phosphate buffer, 0.0027 M potassium chloride and 0.137 M sodium chloride, pH 7.4). The protein adsorption experiments were carried out in the same Insplorion XNano system as the bulk refractive index sensitivity experiments, with a constant flow rate of 100 µL min-1 at room temperature. Supported Lipid Bilayer Formation Experiments: POPC (1-palmitoyl-2-oleyl-sn-glycero-3phosphocholine) liposomes were prepared by the extrusion method.23 Dry POPC was dissolved in chloroform to a final concentration of 10 mg mL-1. From this stock solution, 12 mg of lipids was added to a round-bottomed flask, and the solvent was evaporated under a flow of nitrogen gas while the flask was slowly rotating. Residual solvent was removed by applying vacuum for more than two hours. Subsequently the dried lipids were hydrated in 2.4 mL PBS, to reach a final concentration of 5 mg mL-1. To produce unilamellar liposomes with a narrow size distribution and an average size on the order of 80–90 nm24 the lipid suspension was extruded 11 times through a 100 nm polycarbonate membrane and another 11 times through a 30 nm polycarbonate membrane using a mini extruder (Avanti Polar Lipids Inc., USA). The vesicle solution was


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stored at 4°C. The SLB formation experiments were carried out in the Insplorion XNano system at a concentration of 100 µg mL-1 with a constant flow rate of 100 µL min-1 at room temperature.

Results and Discussion Sensor Characterization The flat nanoplasmonic sensor chips, schematically depicted in Figure 1a, were made by using the modified HCL nanofabrication protocol20 described above. As the key step, the obtained hole-mask was utilized for RIE of disk-shaped 20 nm deep wells in the fused silica substrate, into which, subsequently, 20 nm Au was evaporated to grow plasmonic nanoparticles directly inside the wells. As the last step, PECVD was used to deposit a 10 nm thick SiO2 layer to cover the Au nanoantennas and thus homogeneously embed them in a silica matrix. In this way, flat topography (Figure 1b and c) and uniform surface chemistry are achieved without the use of polymers, ensuring high temperature compatibility and chemical stability even in harsh environments.25–29 We also highlight that other surface chemistry than silica can be easily applied by deposition of a thin film of the material of choice either directly after the growth of the Au nanoantennas in the wells, or after the deposition of the SiO2 layer. In this way, the sensor surface can be tailored for a specific application.


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Figure 1. Flat sensor chip structural characterization. (a) Schematic depiction of the topographically flat nanoplasmonic sensor chip with embedded amorphous array of plasmonic Au nanodisks. The three-dimensional sketch shows the three “layers” of the device, i.e. the wells in the fused silica substrate, the Au nanodisks grown inside the wells, and the topographically flat SiO2 capping layer. Except for the thickness of the fused silica substrate, the sketch is drawn to scale. To the right, a cross-sectional false-colored SEM image of the chip is shown together with a corresponding sketch. Note that the structure shown in the SEM image is not coated with the SiO2 layer. The scale bar in the SEM image is 50 nm. (b) AFM height profile and (c) representative line-scans across the sensor surface (including the SiO2 capping layer) reveals a flat surface with an overall peak-to-peak average roughness, Ra, on the order of 0.9 nm.

As the first characterization step of the flat sensors we derive their bulk refractive index sensitivity (BRIS) experimentally, and analyze theoretically the sensing mode volumes by finite-


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difference time-domain (FDTD) simulations. Moreover, we directly compare them in this respect with traditional nanoplasmonic sensor chips comprised of Au nanodisks protruding from the surface and conformally covered by a 10 nm PECVD-grown SiO2 layer21 (Figure S2). Figure 2a and b show experimentally measured (for an amorphous array of nanoantennas) and simulated (for a single nanoantenna) optical spectra of a flat and corrugated sensor, respectively. In both cases the resonance for the flat sensor with the nanodisk(s) embedded in SiO2 is red-shifted with respect to the situation where the disk(s) are located on top of the substrate, due to the higher effective refractive index of the environment. We also notice a slightly larger line-width for the flat structure. The small mismatch in the resonance position between experimental data and the simulations is related to the interaction between nanodisks in the amorphous array in the experiment, which is characteristic of the HCL method and governed by the center-to-center distance between the particles in the array.30


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Figure 2. Optical and bulk refractive index sensitivity characterization. (a) Experimental and (b) simulated optical spectra for a flat (blue) and a corrugated (red) plasmonic sensor. The scattered field amplitude distributions around the metal nanoparticles for the (c) flat and (d) corrugated plasmonic sensors are very similar. However, the field is more evenly distributed in the vertical direction for the flat/embedded case because in a dielectrically asymmetric environment the electromagnetic energy is drawn into the higher refractive index dielectric. The black lines mark the boundaries between the metal disk, the SiO2 layer, and air. The red dashed lines mark an assumed sensing volume of 30 nm from the metal surface. (e) Experimentally measured bulk refractive index sensitivity (BRIS) for a flat (blue) and a corrugated (red) plasmonic sensor chip. The “steps” in faint color in the background correspond to the raw peak shift data used to derive the BRIS by linear regression and are plotted versus time.


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Before experimentally assessing the BRIS for the flat and corrugated sensors, it is interesting to analyze the field distribution and sensing volumes of the two structures. We use FDTD to calculate the scattered fields shown in Figure 2c and d for the flat and corrugated sensor, respectively. We find that the amplitude of the scattered electric field of both sensors is very similar, although the LSPR is more evenly distributed in the vertical direction for the planar case. This comes about because in a dielectrically asymmetric environment the electromagnetic energy is drawn into the higher refractive index dielectric. For a corrugated surface sensor this means that the BRIS for nanodisks located directly on a flat dielectric support is lower compared to a situation where they are placed on nanopillars.31 Similarly, application of a capping layer with a higher refractive index causes more energy to be directed away from the substrate.32 In the present situation for an embedded nanodisk, however, the BRIS is expected to be lower compared to a protruding nanodisk despite “more” dielectric at the sides and above the nanodisk, and the resulting more symmetric field distribution. This is because the protruding disk with its exposed circumference offers a larger sensing volume compared to the completely embedded one. This can be explained quantitatively by defining the sensing volume to extend 30 nm from the nanosensor surface (at this distance the field intensity has roughly decayed to 1/e of its surface value, that is, the decay length), as marked in Figure 2c and d by the dashed red line. Based on this definition, the sensing volume for a protruding disk is ca. 70% larger than for the embedded one of the same dimension. More importantly, the energy density contained within this volume is ca. 2.8 times larger, as derived from the FDTD simulations (Table S1). This corroborates that, in general, the sensitivity of the flat sensor is expected to be lower, compared to its “standard” counterpart. Our experimental derivation of the BRIS for the two types of


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sensor chips is summarized in Figure 2d, and indeed reveals a lower value for the flat sensor chip, compared to the corrugated one.

Glass Transition Temperature in Thin PMMA Films In a first set of experiments to assess the flat plasmonic chips for application in the field of materials science, we investigated the thickness dependence of the glass transition temperature, ܶ௚ , of PMMA thin films, for which we earlier have carried out an identical study with corrugated (INPS) sensors.21 Therefore, this is an ideal test case for benchmarking the flat sensors. At the same time, it is an interesting system to investigate the role of surface corrugation when the polymer film thickness approaches the dimensions of the protruding sensor nanodisks. The principle mechanism of the sensing for this system relies on the fact that, upon heating, the polymer film expands, which, in turn, reduces its refractive index (Figure 3a). The rate of the expansion depends on the phase of the polymer (i.e. whether it is in the glassy or rubbery state below and above ܶ௚ , respectively) and thus a change in the rate, d∆λpeak/dT, at a certain temperature signals the glass transition. In Figures 3b - f we plot the measured change in the plasmon peak position, ∆λpeak, of flat sensors coated with homogeneous PMMA films (thickness range from 21 to 370 nm), as a function of temperature. At this point it is important to note that the observed peak shifts are calibrated such that the contribution from the intrinsic thermal sensitivity33 of the plasmonic elements used is removed by subtraction of a blank sensor reference measurement (see Figure S4 for details). Thus the response is solely due to the thermal evolution of the PMMA films. Universally, two distinct linear regions exist for all film thicknesses, which mark the two different phases of PMMA within the probed temperature range. To determine the phase transition temperature ܶ௚ , we take the crossing point from linear


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fits to the two regions corresponding to the different phases. We find increasing ܶ௚ with decreasing PMMA film thickness, which agrees well with the literature34,35 and our earlier results.21 To directly compare the data obtained using the corrugated INPS sensor21 and the new flat chip, we plot the thickness dependence of ܶ௚ in the same graph in Figure 3g. Clearly, the results are completely complementary and show a single trend. This has two important consequences: (i) the information obtained by the two different sensor types is the same, and (ii) for the PMMA thin film system the presence of surface corrugation of ca. 20 nm is not affecting the result. The latter is straightforward to understand for the film thickness range above 50 nm but not completely obvious for the thinnest film (21 nm), whose thickness is basically the same as the surface corrugation induced by the protruding plasmonic nanoantennas. In this regime, it is to be expected that the polymer film thickness is not homogeneous, i.e. it may be thinner on top of the nanodisk sensor than in between as a consequence of the spin coating used for film deposition. As we discuss in detail in the SI based on FDTD simulations (Figure S3 and corresponding text), the reason that we still get the same result from the two different sensors is that the measured signal on the corrugated one to the largest extent stems from the polymer located to the side of the protruding nanodisks, where the nominal thickness of 21 nm is retained. As the last analysis step, and to corroborate the identical thickness dependence of ܶ௚ found by the two different plasmonic sensors, we fit the data points to an empirical model presented by Kim et al.36 (see SI for details). From the fit we can then extrapolate the glass transition temperature for bulk PMMA, ܶ௚௕௨௟௞ , and obtain a value of 109 °C. This agrees very well with the


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108 °C reported elsewhere,37 obtained by modulated differential scanning calorimetry, and thus further corroborates the validity of our experimental approach as a whole.

Figure 3. Polymer thin film glass transition temperature measurements. (a) Configuration schematic and working principle of nanoplasmonic sensing of the glass transition temperature in PMMA polymer thin films. Upon heating, the PMMA expands and thus its refractive index changes. This change is reflected as a peak shift in the plasmonic response. (b) – (f) Peak shift response, ∆λpeak, upon heating of a flat plasmonic sensor coated with PMMA films of different thicknesses. From these data the glass transition temperatures, ܶ௚ , can be derived for PMMA films with thickness of (b) 21 nm, (c) 37 nm, (d) 71 nm, (e) 171 nm, and (f) 370 nm, as the intersection point of the two linear fits. The gray areas denote the uncertainty in the derived ܶ௚ based on the 95 % confidence interval of the linear fits. (g) ܶ௚ as function of film thickness with data points obtained from a flat (blue) and corrugated (red) sensor. The error bars of the measured ܶ௚ values from the flat sensor correspond to the uncertainty in the procedure used to


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determine the ܶ௚ value. The data points from the corrugated sensor are adapted from Langhammer et al.21 The solid black line denotes the best fit based on a ܶ௚ -film thickness model introduced by Kim et al.36 to the combined data points (i.e. from both flat and corrugated sensors), and the dashed black line denotes the bulk glass transition temperature, ܶ௚௕௨௟௞ = 109 °C, extrapolated from the fit.

Protein Adsorption and Binding For the next set of experiments, we focus on applying the flat plasmonic chips in the field of biosensing, to shed light on the role of surface topography. To this end, it is known that nanoparticle size via different surface curvature,10,13–15 as well as the ratio between flat and curved surface for facetted nanostructures,6 affect both binding kinetics and molecule-surface interactions and thus, e.g. molecular orientation upon binding or degree of protein denaturation.16,17,38 For our first experiment related to this field, we investigate the adsorption of the biotin-binding protein avidin (Av) on the silica surface of our chip, followed by the subsequent specific binding of biotinylated bovine serum albumin (b-BSA) to the Av monolayer. Upon exposure to silica surfaces, Av spontaneously adsorbs and forms a (sub)monomolecular adlayer.39 On the other hand, b-BSA does not adsorb on silica if the concentration in solution is not very high39 but binds strongly to Av due do their remarkably high affinity. This is therefore an interesting model system to investigate the influence of surface topography on a nanoplasmonic sensor. The typical response of a flat and corrugated plasmonic sensor upon sequential adsorption of Av and b-BSA (20 µg mL-1) is shown in Figure 4a. Upon exposure to Av, for the flat sensor, a rapid


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positive ∆λpeak occurs before it quickly saturates. In contrast, for the corrugated sensor, after the initial rapid response, we observe a second regime where the peak shift slows down but does not reach saturation even after 60 min of exposure. At this point, a ∆λpeak value of around 0.8 nm and 1.8 nm is reached for flat and corrugated sensors, respectively. The difference in the absolute magnitude of the measured response is related to their different sensitivities discussed above. As the next step, we rinse both systems with buffer for another 60 min to remove the loosely bound Av from the surface. Again we observe faster signal saturation for the flat sensor. We then introduce b-BSA to the silica-Av surface. On both sensors, the ∆λpeak signal saturates quite quickly and we observe an absolute peak shift that is approximately twice as large for the corrugated sensor, consistent with the previous Av adsorption step. As the last step, we then rinse again with buffer. However, this time no ∆λpeak is observed for both sensors, corroborating the known fact that b-BSA strongly and irreversibly binds to Av. To further investigate and closely compare the kinetics for the two processes on both types of sensors, we normalize ∆λpeak for Av adsorption and b-BSA binding (Figure 4b and c, respectively). For Av, it is clear that the kinetics is very different on the two sensors (for repeated experiments see Figure S6 in the SI). The adsorption process on the flat sensor occurs rapidly and reaches saturation already within ca. 10 min. On the other hand, Av adsorption on the corrugated sensor displays two regimes: (i) an initial rapid one, very similar to the flat sensor, and (ii) a slow second regime that is almost linear in time and completely absent on the flat sensor. In order to single out the factor creating the difference in the kinetics we compare our data with the related literature. The plasmonic signal evolution on the corrugated sensor is very similar


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with the one observed by Junesch et al.,7 who used an array (also nanofabricated by the HCL method) of plasmonic nanoholes of similar size and thus with almost identical surface curvature, and also observe two regimes of rapid and slow kinetics upon Av adsorption. For the Av adsorption kinetics obtained on the flat sensor, we can make a direct comparison to the work reported by Wolny et al. who used the quartz crystal microbalance with dissipation monitoring (QCM-D) technique,39 which can be considered as a flat surface analogue of the measurement we performed here. The reported adsorption kinetics is strikingly similar to our flat sensor data, as it quickly saturates within a similar time scale and does not exhibit the second slow regime characteristic for the corrugated plasmonic sensor surfaces. Therefore, at this point it is clear that the difference in the kinetics is due to the presence of surface topography. Most likely, the nanoscale surface curvature at the boundary between the sidewalls and the flat top of the nanodisks (positive curvature), as well as between the sidewalls and the underlying substrate (negative curvature), affect the protein-surface interactions (see Figure 4d). Specifically, we speculate that the binding rate, as well as the final molecular conformation, depend on if the proteins adsorb on a flat surface or on an area with nanoscale surface curvature on the sensor chip.16 Such discrepancies in protein adsorption characteristics then give rise to two different regimes in the adsorption kinetics of a corrugated sensor surface, where both flat and curved areas are present, as observed. We also note that, despite amounting a small number of Av as compared to the overall surface of the sensor, the edge of a plasmonic nanodisk (i.e. the boundary between the sidewalls and the flat top of the disk and the flat substrate) exhibits the highest sensitivity towards a change in local refractive index.40 Thus adsorption and binding events occurring on the curved sections of the nanodisk contribute significantly to the total magnitude of the measured ∆λpeak.


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In striking contrast, the binding kinetics of b-BSA on both flat and corrugated sensors is very similar (Figure 4c and Figure S6 in the SI for repeated experiments) as b-BSA rapidly binds and saturates within around 3 min on both types of sensors. This can be understood in the way that the b-BSA – Av interaction is specific, that is, b-BSA exclusively binds to Av and not to the silica surface of the sensor. Therefore, it is not expected to be sensitive to topographical variance on the sensor surface to the same extent, as it only will bind to Av molecules that provide a binding site (Figure 4e). Our observations thus shed light on the role of surface topography of plasmonic nanosensors when studying protein adsorption and biomolecule interactions, and indicate that its importance strongly depends on the studied system at hand.

Figure 4. Protein adsorption and specific binding kinetics. (a) Temporal evolution of the spectral shift of the LSPR peak (∆λpeak) of a flat (blue) and corrugated (red) nanoplasmonic sensor upon exposure to 20 µg mL-1 avidin (Av, blue area) and biotinylated bovine serum albumin (b-BSA, yellow area). The white areas denote rinsing with buffer. The corresponding normalized ∆λpeak signals are shown in (b) for Av adsorption and in (c) for b-BSA specific binding to the Av. Evidently, the adsorption kinetics of Av on the flat and the corrugated surface


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is different. Adsorption rapidly saturates on the former while a second regime of slow kinetics is observed on the latter. In contrast, the binding kinetics of b-BSA is almost identical on the flat and corrugated surface (for repeated experiments see the SI). (d) Schematic cross-sectional and to-scale illustration of the Av adsorption on the surface of a corrugated and a flat sensor, which highlights the different regions on the corrugated surface where the Av binding is affected by the positive and negative curvature present at the boundary between the sidewalls and the flat top of the disk and the flat substrate. Av molecules affected by curvature are depicted in darker color to provide an indication for their relative abundance. (e) Schematic illustration of the b-BSA specific binding on the pre-adsorbed Av. Since the binding is specific, b-BSA quickly binds to the Av where binding sites are available. Thus the binding process is independent of the topographical profile of the underlying silica surface. Note that the proteins (Av of 4 nm x 5.5 nm, and b-BSA of 4 nm x 8 nm) are drawn to scale to the sensors. However, the binding conformations are arbitrary and should only serve as schematic conceptual illustration.

Supported Lipid Bilayer Formation In this last example, we set out to study the formation of SLBs on the chemically identical SiO2 supports of a flat and corrugated sensor chip, respectively, to facilitate direct comparison. SLBs are an important model of cell membranes with diverse applications in biotechnology, which is why their formation on different types of surfaces has been widely studied.41 Traditionally, such studies are carried out by employing experimental techniques such as QCM-D, ellipsometry, and surface plasmon resonance (SPR), with penetration depths of their acoustic or optical fields on the order of few hundred nm.42,43 This length scale is far greater than the thickness of an extended SLB (~5 nm). Consequently, in the past years, nanoplasmonic sensors, whose


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penetration depth (or sensing volume – see Figure 2c and d) is of the order of few tens of nm only, have been employed as alternative characterization technique for the study of SLB formation.24,44,45 However, it is still unclear how the surface corrugation inherent to traditional nanoplasmonic sensors may affect the SLB formation process and the specifics of the formed SLB. Therefore here we investigate this issue by directly comparing the SLB formation under identical conditions on both a flat and corrugated nanoplasmonic sensor surface. Figure 5a shows the temporal evolution of ∆λpeak for the corrugated and flat plasmonic sensors, respectively, upon exposure to lipid vesicle suspension (100 µg mL-1, Ø ~80 nm in buffer). Initially, we observe a monotonic change of ∆λpeak for both sensors until around 6 min when the response displays a slow but significant acceleration resulting in a characteristic “kink”, which signals the successful formation of extended SLBs.46,47 Finally, the ∆λpeak signals saturate at around 1.7 and 3.1 nm for flat and corrugated sensors, respectively. The difference in absolute amplitude of the measured response between the two samples is again the consequence of the lower overall sensitivity of the flat sensor due to the smaller sensing volume discussed above. To qualitatively compare the response of, and thus the SLB formation on, both sensors we plot the SLB formation kinetics in a normalized fashion in Figure 5b. In the figure, we divide the SLB formation process into two regimes separated by the “kink”, in which two processes dominate, respectively: (i) vesicle adsorption onto the surface and (ii) vesicle rupture and SLB formation. We observe that the vesicle adsorption kinetics in regime (i) on both sensors is practically identical, while the rupture kinetics in regime (ii) on the flat sensors is faster than on the corrugated one. These findings can be rationalized by examining the factors that affect both processes, as schematically drawn in Figure 5c. Vesicle adsorption kinetics on a surface is mainly governed by temperature, precursor concentration, flow rate and chemical composition of


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the surface.41,48 Since all parameters are identical for both sensors in our experiments, similar adsorption kinetics is expected. On the other hand, the vesicle rupture process is more complicated and controlled by additional factors. In particular, the surface topography is known to govern the spreading of bilayers on solid supports.41,49,50 To this end, SLBs can very intimately adapt to the topography of an underlying homogeneous support down to a feature size of less than 10 nm.51–53 However, during the formation of the SLB on a surface featuring curvature, a higher energy barrier has to be surmounted due to the “bending” of the SLB, which, in turn, results in slower SLB formation kinetics compared to an ideal flat SLB.41,53,54 To quantitatively analyze our kinetics data in this respect, we plot the SLB formation rate k (i.e. d normalized ∆λpeak/dt) as function of time (Figure 5d). Again, we can clearly distinguish the two regimes for the vesicle adsorption and rupture process. The adsorption kinetics is very similar for both sensors whose maximum rate of 0.0020 A.U. min-1 is reached after around 4 min. Shortly after, the system transitions to the rupture process, in which the rate for the flat sensor quickly increases until it reaches a maximum of 0.0052 A.U. min-1. On the other hand, the rate of the corrugated sensor reaches a maximum of 0.0046 A.U. min-1 around one minute later. This is in good agreement with the aforementioned scenario. The ratio of the maximum rates of corrugated and flat sensor is 0.88 in this first experiment, and we use this parameter to assess the robustness of our result by plotting it for three consecutive identical experiments in the inset in Figure 5d. We find that these reproducibility tests result in very similar ratios of the maximal SLB formation rate, that is, 0.87 ± 0.03. Therefore we draw the following two key conclusions from our analysis: (i) Surface topography present on traditional nanoplasmonic sensors affects the kinetics of the second phase of SLB formation, that is, the vesicle rupture rate due to the necessary bending of the SLB at the plasmonic nanoparticle edges. (ii) The presence of


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plasmonic nanoantennas protruding from a sensor chip surface influences the SLB formation process. This is important to consider when quantitatively analyzing and comparing results, and highlights the importance of choosing appropriate plasmonic sensor nanoarchitecture.

Figure 5. Sensing of supported lipid bilayer (SLB) formation. (a) Temporal evolution of the spectral shift of the LSPR peak (∆λpeak) of a flat (blue) and corrugated (red) nanoplasmonic sensor upon exposure to lipid vesicle suspension (purple shaded area, 100 µg mL-1, Ø ~80 nm in buffer). (b) Normalized ∆λpeak signal of the data shown in (a). The characteristic “kink” is observed, and it separates the two regimes of SLB formation, that is, (I) the adsorption of lipid vesicles on the surface and (II) their rupture and formation of the SLB. Note that the rupture kinetics of the lipid vesicles on the corrugated sensor is slower than on the flat sensor, whereas the vesicle adsorption rate is essentially the same on both. (c) Schematic illustration of the two


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regimes of SLB formation on a flat and corrugated sensor surface. Note that the relative size of the individual lipids compared to the plasmonic sensors is arbitrary, whereas the vesicle size is drawn to scale. (d) The rate, k = d∆λpeak norm./dt, of the SLB formation on the two sensors, where the two regimes denoted (I) and (II) again correspond to the vesicle adsorption and rupture process, respectively. Inset: the ratio kcorrugated/kflat of the maximum rate during vesicle rupture for three different measurements to demonstrate the reproducibility of our experiments. The dashed line and light gray area denote their mean and standard deviation, respectively.

Conclusion In conclusion, we presented topographically flat nanoplasmonic sensor chips that were nanofabricated by using a modified version of Hole-Mask Colloidal Lithography and exhibit a measured surface roughness of less than 1 nm. They comprise an amorphous array of Au nanoparticle plasmonic sensors, embedded in a chemically inert and high-temperature compatible silica matrix. We analyzed their sensing volume and bulk refractive index sensitivity experimentally and by FDTD-simulations, and demonstrated their sensing performance on three different examples, for which we also carried out a direct comparison with a traditional nanoplasmonic sensor with representative surface topography to scrutinize the importance of nanoscale surface corrugation for the obtained results. Specifically, we (i) quantified the filmthickness dependence of the glass transition temperature in poly(methyl metacrylate) thin films down to the 20 nm regime, (ii) characterized the adsorption and specific binding kinetics of the avidin – b-BSA protein system and (iii) analyzed supported lipid bilayer formation on SiO2. For case (i) we found almost perfect agreement between results obtained using a flat and corrugated sensor surface, respectively, due to the isotropic nature and homogeneity of the studied material.


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For case (ii) we identified two different scenarios for the unspecific avidin adsorption to the SiO2 and the specific binding of b-BSA to the preadsorbed avidin layer, respectively. For avidin adsorption we found a significant dependence of the adsorption kinetics on the specifics of the sensor used, whereas for the specific binding of the b-BSA no sensor surface topography dependence of the kinetics was observed. This is explained by the curvature-dependent adsorption/denaturation of avidin on the SiO2 surface, contrasting the specific covalent - and thus support geometry independent - binding of b-BSA to a preadsorbed avidin adlayer. For case (iii) we observed that surface topography present on traditional nanoplasmonic sensors affects the kinetics of the second phase of supported lipid bilayer formation, that is, the vesicle rupture rate due to the necessary bending (and associated energy barrier) of the lipid bilayer at the plasmonic nanoparticle edges. Our results thus highlight the importance of choosing appropriate plasmonic sensor nanoarchitecture in both biosensing and materials science applications, to ensure that surface topography is not affecting the probed process. Furthermore, they hint at interesting opportunities to explore tailored surface topography inherent to traditional nanoplasmonic sensors in systematic studies of nanoparticle-(bio)molecular interactions.


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ASSOCIATED CONTENT Supporting Information Schematic of the fabrication process, structural characterization of the corrugated sensor chip, electromagnetic energy distribution in the vicinity of the plasmonic nanoparticle, intrinsic temperature sensitivity of the flat sensor chip, model for thickness-dependent ܶ௚ and its fit to individual data set from flat and corrugated sensors, repeated measurements on Av – b-BSA adsorption on flat and corrugated sensor surface. This material is available free of charge via the Internet at http://pubs.acs.org.

AUTHOR INFORMATION Corresponding Author *(EMLL): [email protected] (CL): [email protected] Author Contributions The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript.

ACKNOWLEDGMENTS We acknowledge financial support from the Swedish Foundation for Strategic Research Framework Programs RMA11-0037 and RMA15-0052, the Mistra Environmental Nanosafety project, the Swedish Research Council project 2014-4956 and the Chalmers Area of Advance for Nanoscience and Nanotechnology. We also thank the Knut and Alice Wallenberg Foundation for


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their support of the infrastructure in the MC2 nanofabrication laboratory at Chalmers, and the Swedish Research Council for their support of the µ-fab cleanroom infrastructure in Sweden. TJA thanks the Polish National Science Center for support via the project 2012/07/D/ST3/02152.


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Topographically Flat Nanoplasmonic Sensor Chips for Biosensing and

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