Critical Issues in Localized Plasmon Sensing - ACS Publications

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Critical Issues in Localized Plasmon Sensing Ofer Kedem, Alexander Vaskevich,* and Israel Rubinstein* Department of Materials and Interfaces, Weizmann Institute of Science, P.O. Box 26, Rehovot 7610001, Israel ABSTRACT: Localized surface plasmons (SPs), that is, charge density oscillations in metallic nanostructures often excited by coupling to electromagnetic radiation, have been widely studied for use in sensing applications. Here we present recent work from our group related to several major issues in the field, which have not been treated in depth in previous reviews. Specifically, we discuss the distance dependence of the localized plasmon response; the differences in response between transmission and reflection mode measurements; comparison with other, closely related sensing techniques; the use of sandwich configurations (e.g., biological sandwich assays) to enhance the response; and the search for alternative plasmonic materials, other than the widely used (but expensive) gold and silver. For each topic we review the existing literature and provide a detailed account of our contributions. (LSPR), which is the main topic of this Article.2,3,5 We focus on optical measurements, where the LSPR is manifested as a strong extinction band in the UV−vis−NIR range, distinctly different from the spectrum of the bulk metal. The frequency and intensity of the resonance band depend on a variety of factors, including the metal composition, the size, shape, and separation of the metal nanostructures, as well as the dielectric properties of the surroundings.2 The plasmon electric field, confined to the metal nanostructure, decays evanescently into the dielectric medium. Changes in the dielectric constant of the medium within the plasmon electric field will cause a shift of the resonance frequency and intensity of the LSPR extinction band. In 1908, Gustav Mie expressed the Maxwell equations for the case of spherical NPs in a homogeneous medium.6 The extinction of a film of metallic spheres in the long-wavelength, electrostatic dipole limit can be described by4,7

1. INTRODUCTION Plasmonics. The past 15 years have seen an explosion of research in the field of plasmonics, involving researchers from varied disciplines, such as physics, chemistry, biology, materials, and engineering, exploring the various principles and applications. The field is concerned with plasmons, which are charge-density oscillations, typically (though not always) in metals.1,2 There are several types of plasmons: Bulk or volume plasmons exist in bulk metals and are only rarely studied because coupling into them (and thus exciting and utilizing them) is difficult, although it can be achieved using, for instance, electron beams. At the interface between two materials with the real part of the dielectric constants having opposing signs, there can exist surface plasmons (SPs), that is, charge density oscillations confined to the surface and propagating along the interface. SPs can be excited by incident light of appropriate frequency to form a surface plasmon polariton (SPP), a hybridized excitation of a photon and a plasmon. SPs on smooth metal films cannot be directly excited by incident light from air due to a momentum mismatch between the light and the SPs.3 One way to increase the photon’s momentum is to shine the light at a specific angle through a prism, coupled to the metal film; another is to add periodic corrugations on the film (forming a grating).2,3 This energy-dependent excitation process is termed surface plasmon resonance (SPR), and the coupled energy is dissipated as reemitted light and heat. High loss in metals limits the propagation distance of SPPs to a few micrometers. SPR is widely used in commercial biosensor systems, mostly for affinity studies.3,4 Further confinement of SPs, that is, in nanosized features, can result in localized SPs. We use nanoparticles (NPs) as a generic term for description of metal nanosized features that can be prepared using techniques such as chemical synthesis, vacuum evaporation of island films, dewetting of continuous films, and so on. Free-space radiation readily couples to these, in a process termed localized surface plasmon resonance © XXXX American Chemical Society

E (λ ) =

⎤ 24π 2NAa3εm3/2 ⎡ εi(λ) ⎥ ⎢ 2 2 λ ln(10) ⎣ (εr(λ) + χεm) + εi(λ) ⎦

(1)

where E(λ) is the extinction (scattering and absorption), NA is the area density of NPs, a is the radius of the metallic sphere, εm is the dielectric constant of the medium surrounding the metallic nanosphere, λ is the wavelength of the incident radiation, εr and εi are the real and imaginary components of the metallic NP’s dielectric function, and χ is a variable that depends on the shape of the NP (2 for a sphere). Maximal extinction (i.e., the SP band) will be observed, according to eq 1, at a wavelength for which εi(λ) is relatively small and εr(λ) = −χεm. For certain metals (e.g., Ag, Au, Cu) showing a negative εr in the visible range, the latter relationship is fulfilled in the visible spectral region. εr for metals has a Received: October 7, 2013 Revised: January 30, 2014

A

dx.doi.org/10.1021/jp409954s | J. Phys. Chem. C XXXX, XXX, XXX−XXX

The Journal of Physical Chemistry C

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strong wavelength dependence, and thus a change in εm leads to a shift of the resonance wavelength and a change in the extinction intensity.9 Excitation of localized SPs is observed in various complex nanostructures. Although in complex structures the extinction cross-section cannot be described by the simple eq 1, the sensitivity of the resonance frequency (the LSPR band wavelength) to changes in the refractive index (RI) of the immediate environment is a general phenomenon forming the basis for sensing based on RI change.2,3,5,10−16 Plasmonic Coupling and Plasmon Rulers. When plasmonic NPs come into close proximity with one another, new coupled plasmon modes arise. This can be explained using a plasmon hybridization model, akin to molecular orbital bonding.8 For NP dimers, the individual plasmon modes couple to form a “bonding” mode at a lower energy, as well as a highenergy “anti-bonding” mode. Depending on the symmetry, the modes can be bright or dark.8 Some LSPR sensing systems utilize interparticle coupling in solution by functionalizing colloidal metallic NPs so as to cause aggregation, and thus a strong color change, upon exposure to a target analyte.8,17−19 Plasmon coupling arising from close proximity of NP ensembles formed by sequential immobilization20 may be used in so-called sandwich assays. These approaches provide sensors requiring just the naked eye to determine color change and hence the presence of an analyte.15 Plasmon hybridization may also be used in a more quantitative manner, as plasmon rulers. The distance between the NPs controls the degree of coupling and accordingly the energies of the peaks in the measured extinction or scattering spectrum. Using this universal scaling behavior, plasmon ruler equations were derived that quantitatively estimate the separation between metal NPs from the observed fractional shift of the plasmon band.21,22 In a calibrated system, a change in the distance between members of a dimer, arising from, for example, analyte binding, can be detected and quantified by the spectral change. Such plasmon ruler systems have been used in a variety of cases, such as detecting DNA23,24 and proteins25 in complex media, studying the dynamics of DNA bending and cleavage,26 and observing single DNA hybridization events.27 The 1-D plasmon ruler concept was also expanded to three dimensions using coupled plasmonic oligomers.28 We focus on systems composed of immobile particles, assuming that the optical response depends only on changes in the RI of the environment caused by analyte binding. Plasmon−plasmon coupling is expected to become an important factor in the spectral response only in the case of a short interparticle spacing, roughly less than the particle radius.8 The systems discussed in this Article display only weak coupling effects because, on average, the interparticle spacing is large enough to prevent effective coupling. Refractometric Sensing. Refractometric sensing was first introduced for solution-based NPs,29 but the majority of research has been performed using plasmonic nanostructures immobilized on inert solid substrates. Immobilization of the nanostructures prevents aggregation and hence convolution of the refractometric response with plasmon coupling effects. The transition from solution-based to substrate-based transducers changes the geometry of the system. Whereas colloidal NPs experience an RI change (due to, e.g., analyte adsorption) with spherical symmetry, in a substrate-based transducer, only the part of the NP exposed to the medium experiences RI shifts, generating a response. The latter decreases the sensitivity of the

refractometric response, but the reduced sensitivity is compensated for by the robustness of LSPR transducers based on immobilized NPs. Hence, immobilization of NPs on a solid support provides a convenient platform allowing flexibility in the preparation of specific recognition interfaces, a prerequisite for practical applications. In a typical plasmonic RI sensing scenario, a metal NP (or nanohole) film on a solid substrate is first coated with a recognition interface to provide specificity. The recognition layer is typically composed of molecules that can selectively bind a given analyte, for example, antibodies, DNA strands, and so on. The transducer’s transmission or reflection spectrum is then recorded, followed by exposure to the investigated solution and another spectral measurement, with the spectrum being recorded either during incubation (for in situ measurements) or following incubation (ex situ measurements). Should the solution contain the specific analyte, it is expected to bind to the recognition interface, displacing the medium that previously occupied the space (e.g., water, buffer, air). If the analyte RI is different from that of the medium, then the displacement will effect a change in the NPs’ resonance band, changing the transducer LSPR spectrum. We have developed a procedure allowing stabilization of Au island film morphology by partial embedding into the underlying substrate (glass), induced by long annealing at temperatures in the vicinity of Tg of the glass substrate.30,31 Au island films stabilized by partial embedding in the glass were used by us as a model system for quantitative studies of the sensitivity of LSPR transducers. Figure 1 (center to right)

Figure 1. Photograph of three gold nanoisland films evaporated on glass substrates. Left: as-deposited, 5 nm (nominal thickness) Au. Center: a similar sample, after annealing 10 h at 580 °C; the annealing forms the nanoislands’ final shape while partially embedding them in the glass. Right: a similar annealed sample, after coating with a 21 nm polyelectrolyte (PE) multilayer film, showing a substantial color change.

shows the colorimetric change of a morphologically stable island film affected by assembly of a dielectric coating. There is a clear similarity between a colorimetric response arising from change of the dielectric medium of colloidal NPs, easily observed by the naked eye,32 and the present case of color change resulting from relatively thick dielectric coatings on immobilized metal islands (Figure 1). Figure 2 shows a typical example of an antibody−antigen sensing scenario. The analyte layer is not necessarily a full monolayer, and partial monolayers are especially relevant in kinetic studies. In such cases, the LSPR response is linearly proportional to the analyte coverage, as we have previously shown.33,34 B



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Figure 2. Illustration of a typical antibody−antigen sensing scenario, with the plasmon evanescent field shown in red; presented schematically are cases where the plasmon field is too short (left), too long (center), and just right (right) for maximal response.

and Huffman.46 Extensions of Mie scattering to the core−shell case were also formulated, for example, by Xu et al.47 and Khlebtsov et al.48 While a rigorous core−shell approach is more accurate, it was found that the response of an LSPR transducer to layer adsorption can be described by a simple phenomenological equation (eq 2).49 This equation was originally developed by Jung et al. for SPR transducers (i.e., propagating plasmons); its validity for NP-based LSPR transducers was later verified by Malinsky et al.50

The spectral response to changes in the dielectric properties of the surrounding medium is the result of the plasmon evanescent electric field, extending from the NP into the medium. Except for the case of a perfect sphere in a homogeneous medium, the field varies spatially as a result of the NP’s geometry (e.g., field enhancement in areas of high curvature) or disruption induced by the substrate or by other adsorbates.2 Hence, analyte adsorption at different areas of the NP is expected to produce responses of varying sensitivity. Owing to experimental limitations, only a few studies have explored the effects of the field’s spatial variation on LSPR sensing. Feuz et al. explored the different responses to analyte adsorption at the bottom or the side of nanoholes35 and to adsorption on nanodisks and at hot-spots between the nanodisks;36 Beeram et al. selectively adsorbed analytes at different sites on nanoplates;37,38 and Sannomiya et al. explored the response to binding of Au-NP-labeled DNA at different sites on Au NPs.39 Spectral measurements can be performed on single metal NPs or nanoholes,40−42 an approach that can offer advantages in terms of sensitivity but involves great complexity and considerable cost.39,43,44 The vast majority of LSPR sensing studies, however, utilize NP films, and are therefore classified as ensemble measurements. Because the particles in the ensemble can be of differing shapes and can bind a different number of analyte molecules each, in such measurements the different responses of the particles are averaged. Hence, a typical LSPR sensing response reflects two averaging mechanisms: different responses of the large number of NPs measured and sites of differing sensitivity on each NP. We focus on several topics that in our opinion have not received sufficient attention in previous reviews on LSPR sensing and that are of critical importance for future development and implementation of LSPR transducers in sensing applications, emphasizing our contributions in these areas.

R = mΔη(1 − e−d / ld)

(2)

where R is the response (e.g., wavelength shift, intensity change), m is the refractive index sensitivity (RIS), a parameter characteristic of the specific transducer, Δη is the difference in the RI between the adsorbed layer and the medium it displaced (e.g., air, water), d is the layer thickness, and ld is the plasmon decay length, also a parameter characteristic of the specific transducer. The RIS can be easily determined by measuring the transducer spectrum in bulk solvents of different RI values; the effectively infinite layer thickness simplifies eq 2 to the linear relation R = mΔη, and m is easily extracted as the slope of R versus Δη curve. Note that eq 2 and its simplified linear version are the first approximation of the LSPR response to RI change; over a wide RI range, the response to bulk RI change often displays a clear nonlinearity.49 The deviation from linearity, however, is typically small for relatively small RI changes, and hence eq 2 is usually satisfactory for practical purposes. An LSPR transducer is commonly coated with a recognition interface, a layer which selectively adsorbs a desired analyte, to afford specificity; the equation for this case is then51 R = mΔηe−d1/ ld(1 − e−d2 / ld)

(3)

where d1 and d2 are the thicknesses of the recognition interface and analyte layer, respectively, and Δη is assumed to be the same for both layers. Equations 2 and 3 are widely used in LSPR sensing studies. Equation 3 implies that no single value of ld will produce a maximal response but that its value must be selected based on the thicknesses d1 and d2. For effective sensing, the plasmon field must encompass a large enough volume to include the region of space where analyte binding takes place. However, for a relatively large field and thin analyte, adsorption of the analyte will effect an RI change in only a small fraction of the sensing volume. Because the particle’s LSPR is sensitive to the RI of the entire sensing volume, this will result in only a small change in the resonance. These scenarios are illustrated in Figure 2; for optimal performance, a transducer with appropriate decay length for a given application must be selected. Note that various other surface-enhanced phenomena are also dependent on the local intensity of the evanescent electromagnetic field.52 Most notable are surface-enhanced Raman scattering (SERS)53,54 and metal-enhanced fluorescence (MEF).55−58

2. LSPR RESPONSE Plasmon Decay Length. LSPR refractometric sensing is based on RI changes, caused by analyte adsorption in the vicinity of the plasmonic metal particle. The sensitivity to the environment is provided by the evanescent nature of the plasmon electric field, extending from the metal particle into the surrounding medium. For RI changes to produce a measurable shift in the resonance, they must occur in a region of appreciable field intensity. To a good approximation the plasmon field decays exponentially with the distance from the particle’s surface, and hence effective sensing is limited to a typical range of tens of nanometers, a region termed the sensing volume. The common case of sensing of adsorbed analyte layers on plasmonic particles is effectively a core−shell system (metal core−dielectric shell). A solution for scattering by a small coated sphere was first formulated by Aden and Kerker in 195145 and later generalized to a multilayer coating by Bohren C



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are shown in Figure 3A−C, and representative extinction spectra of the bare Au island films are presented in Figure 4.

Several groups have investigated the LSPR distance dependence for various systems, although they rarely quantified it. In 1996, Liz-Marzán, Giersig, and Mulvaney synthesized Au-silica core−shell NPs and examined the effect of the shell thickness on the spectra.59 Schmitt et al. later formed Au NP monolayers coated with polyelectrolyte (PE) multilayers and observed an exponentially diminishing per-layer response.60 Okamoto et al. coated NP monolayers with the polymer PMMA and quantified the decay length for two particle sizes.61 In 2001, Malinsky et al. fabricated Ag nanotriangle arrays and found a linear short-range response (up to 2 nm) using alkanethiols of increasing chain lengths.50 The latter work first applied eq 2, originally proposed for SPR transducers, to LSPR systems, based on the wavelength shift saturation for thick shells found in Mie scattering calculations by Kelly et al.62 Malinsky et al.’s work was later expanded by Haes et al. to include several particle sizes63 and to examine the longer range response (up to 40 nm) of the same particles, using a Cu−thioacid multilayer system; they also reported an exponential decay of the response although again did not quantify the distance dependence.64 Haes et al. also suggested utilizing different sizes and shapes of metal particles to tune the decay length for the desired application. Whitney et al. performed a similar study of these systems using atomic layer deposition (ALD) to obtain high-resolution information (in adlayer thickness).65 In 2002, Xu et al. formulated an extension of Mie theory for core−shell particles and noted the superior performance of small particles under certain conditions, attributed to their stronger field localization.47 Nath et al. adsorbed a few PE bilayers on multiple types of Au NP monolayers, with diameters varying from 12 to 49 nm, noting a faster decay for smaller particles.66 In work done by our group in 2005, Doron-Mor et al. explored the distance dependence of the response in systems of random evaporated Au nanoislands using a coordination-based multilayer system, previously developed by the group. 67 The same year, Rindzevicius et al. used alkanethiols to study the short-range (up to 2 nm) response of nanoholes in an Au film and roughly estimated their decay length.40 A 2008 work by Dahlin et al. used an unusual approach to exploring the sensing volume of a nanohole array, combining both LSPR and quartz crystal microbalance (QCM) responses in a single transducer.68 In 2009, Chen et al. measured the decay length for high- and lowaspect ratio Au nanodisks.69 The same year, Sannomiya et al. explored the RIS and the response to thin layer adsorption for several gold NP film types.70 Kiel et al. also utilized PE multilayers to explore the distance dependence for three Au NP diameters but did not quantify the results.71 In 2011, we reported the decay length and RIS of random Au nanoisland films of seven average particle sizes using a PE multilayer system.72 By applying a systematic quantitative analysis of several particle sizes, we unveiled a near-linear correlation between the RIS and decay length, not previously reported. The nanoisland films are fabricated by resistive evaporation of Au on glass substrates, followed by high-temperature (550− 600 °C) annealing to form single-crystalline Au islands as well as partially embed the islands in the glass, thereby stabilizing the system. The average size of the islands can be varied by tuning the evaporated nominal (mass) thickness, and we refer to the film types by the nominal thickness used. The studies reported here used a range of 3−10 nm nominal thickness, corresponding to a 20−100 nm in-plane diameter, respectively. Scanning electron microscopy images of some of the samples

Figure 3. HRSEM images of gold island films of (A−C) 3, 5, and 10 nm (nominal thickness), annealed 10 h at 580 °C. (D−F) 10 nm (nominal thickness) Au islands coated with 40 polyelectrolyte layers, in plan view (D) and in isometric view (60° from normal), showing the surface (E) and internal composition (F). In-lens (A−E) and chamber-mounted Everhart−Thornley (F) secondary-electron detectors were used. Reproduced from ref 72.

Images of the annealed Au nanoisland samples coated with a PE multilayer are shown in Figure 3D−F. The nanoisland films were coated with PE multilayers of known thicknesses, and changes in the LSPR spectrum for each successive PE bilayer were recorded. Changes in the extinction spectra upon layer adsorption are shown in Figure 5 for two island sizes, that is, small and large particles (20 and 100 nm average diameter), showing faster saturation of the response for the smaller particles. The plasmon peak shifts for successive layer adsorption on Au islands of various particle sizes show the same trend (Figure 6). Decay curves such as those shown in Figure 5 were fitted to eq 2 to extract the RIS and the decay D



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Figure 4. Representative extinction spectra of bare gold island films of various nominal thicknesses (indicated), annealed. Extinction is given in absorbance units (A.U.). Reproduced from ref 72.

Figure 6. Plasmon peak wavelength shifts for the deposition of polyelectrolyte layers on annealed Au island films of indicated nominal thicknesses; values are the mean of four slides per Au thickness. Experimental points are connected for viewing convenience. Reproduced from ref 72.

Figure 7. Refractive index sensitivity (RIS) as a function of decay length, for annealed Au island films of various nominal thicknesses (indicated). The red line is a linear fit; data points are the mean of four samples each, and the error bars represent standard deviations. Adapted from ref 72.

dimensions of the studied analyte−receptor system. For example, in the common case of biosensing, where the molecular dimensions are typically several nanometers, small islands exhibiting lower RIS values are actually expected to provide a higher overall sensitivity as a result of better matching of the decay length.72 In 2012 Tian et al. used PE multilayers to explore the relationship between aspect ratio and decay length for Au nanorods (NRs). They found a linear relationship between the decay length and NR diameter and the decay length and NR length but no relation between decay length and aspect ratio.74 While the authors did not report the RIS values, we extracted them, along with the decay lengths, from the decay curves presented in the paper, which we fit to eq 2. The results show a seemingly linear relationship between the decay length and the RIS for a set of NRs with a constant diameter and increasing length (Figure 8A) but no relation for NRs of constant length and increasing diameter (Figure 8B). This is to be expected because the authors monitored the long wavelength, longitudinal plasmon resonance, which is much more sensitive to length than to width. A linear regression (adj. R2 = 0.93) of the RIS as a function of the decay length for variation of the NR length (Figure 8A) produces the relationship: m = −401 ± 70 nm/RIU + ld × (48.9 ± 6.5 RIU−1). The slope here is vastly steeper than that in our results (Figure 7), where the slope is:

Figure 5. Extinction spectra for annealed (A) 3 and (B) 10 nm (nominal thickness) Au island films, coated with polyelectrolyte multilayers. Reproduced from ref 72.

length, revealing that these two basic parameters of the LSPR transducers are nearly linearly correlated (Figure 7). A linear regression (adj. R2 = 0.71) produces the relation: m = 58.2 ± 3.9 nm/RIU (refractive index unit) + ld × (2.43 ± 0.62 RIU−1). The implications of the direct correlation between the RIS and decay length of the LSPR transducers are far-reaching and crucial for optimization of the transducers for sensing applications, that is, for obtaining a maximal response. While LSPR transducers are commonly evaluated on the basis of the RIS as a sole parameter,12,13,73 our results indicate that the plasmon decay length must be included in defining the transducer sensitivity. The correlation between the RIS and decay length leads to the conclusion that a higher RIS is not always beneficial for sensing, as it implies a longer decay length; maximizing the transducer response requires the interrelated RIS and decay length to be optimized with respect to the E



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linearly correlated with each other (Figure 9, inset). A linear fit (adj. R2 = 0.998) produces the relationship: m = 56.29 ± 0.02(nm/RIU) + ld × (0.329 ± 0.001 RIU−1). The slope here is shallower than in our experimental results. From this calculation two conclusions are evident: (i) The direct correlation between RIS and decay length is a basic property of plasmonic transducers, easily reproduced with a simplified model, and (ii) as previously noted, the slope of the linear relationship strongly depends on the specific plasmonic structure. A possible explanation for the three vastly different values found for the slopes is the particles’ aspect ratio − the modeled particles are perfect spheres. Our experimental particles are flattened ellipsoids or somewhat elongated discs with in-plane aspect ratios of ∼1.1 to 1.2; and Tian et al.’s particles are NRs, with aspect ratios ranging from ∼1.6 to ∼3.6. The results suggest that the slope grows with the aspect ratio, although further research into this issue is needed to test this hypothesis. Long-Range Response. In 2006, Murray et al. reported oscillations of the plasmon peak wavelength in NP films as a function of overlayer thickness for thicknesses far beyond the decay length and attributed them to interaction with the reflected field.75 In 2007, Rindzevicius et al. suggested using this phenomenon for long-range RI sensing and offered an image dipole approach to model the oscillations.76 Later work by the Szunerits group further explored the use of this effect in sensing, detecting the adsorption of thin layers on top of thick (over 100 nm) spacer layers.77 In 2012, our group, in collaboration with T. Sannomiya (Tokyo Institute of Technology), carried out a systematic study exploring the long-range response for three types of gold NP films with vastly different particle sizes (20, 35 and 100 nm average in-plane diameter, denoted (according to the Au nominal thickness) Au3nm, Au5nm, and Au10nm, respectively).78 We coated the NP films, as well as smooth continuous Au films (denoted AuCont), with SiOx coatings (x ≤ 2) in the thickness range 15−348 nm and measured their reflection and (for the NP films) transmission spectra. The NP films displayed oscillations of the plasmon peak wavelength as a function of the coating thickness, with changes in the spectrum occurring far beyond the known decay lengths, in line with the literature reports; an example is shown in Figure 10. Furthermore, we observed oscillations in the transmittance and reflectance for all wavelengths. The oscillations at any given wavelength have the same periodicity for all NP films regardless of their different decay lengths as well as for AuCont (Figure 11). The phase of the oscillation, however, differs substantially between the NP films and AuCont. The NP film can act as a mirror by far-field interaction, introducing a phase shift to the reflected light, which is different from that introduced by a smooth mirror. We modeled several NP arrays (in collaboration with T. Sannomiya) using a Multiple Multipole Program (MMP); the model systems are denoted PxxDyy, where xx is the particle periodicity (50 or 250 nm, in both x and y directions) and yy is the NP diameter (15, 25, or 35 nm). The model systems showed oscillations similar to those of the experimental transducers. The NP film/dielectric coating system is a specific case of a Fabry−Pérot interferometer (etalon), where light reflected from both the NP film and the dielectric coating−air interface interferes at the detector. The interference leads to oscillations of the measured intensity as a function of the phase difference between the reflected waves.

Figure 8. Refractive index sensitivity (RIS) as a function of plasmon decay length for Au nanorods of various dimensions (indicated, in nanometers), varying the nanorod length, including a linear fit (A) or the nanorod width (B). Data extracted from ref 74.

2.43 ± 0.62 RIU−1. This indicates that the decay length/RIS correlation factor is not a universal factor, but depends on the nanostructure type. Core−Shell Calculations. To further explore the correlation between the RIS and the decay length, we calculated the extinction cross-section of a single spherical NP using a simple core−shell model based on the Drude model with dipole polarizability in the static limit. By analogy to our work on the decay length,72 we modeled a dielectric shell of various thicknesses coating an Au NP and determined the RIS and decay length by exponential fitting. We repeated this procedure for particles with radii in the range 10−40 nm in 0.25 nm increments. Both the decay length and the RIS were found to be linearly correlated with the NP radius (Figure 9) and thus

Figure 9. Calculated results for spherical Au core/dielectric shell NPs: plasmon decay length and RIS as a function of NP core radius. Inset: RIS as a function of decay length (black line), with a linear fit (red line). F



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Figure 11. Experimental reflectance at a wavelength of 500 nm for the three island sizes studied and for AuCont (indicated). Reproduced from ref 78.

experimental systems, especially Au10nm, and the P50 models) are wider, attributed to interparticle plasmonic coupling. For Au10nm in particular, a feature in the red-NIR range is also the result of coupling (panel A). The phase plots show an inflection point around the LSPR wavelength, which is typical of resonant systems.80 The inflection point marks the transition from inphase to out-of-phase oscillations with respect to the driving force. The phase plots show a less abrupt shift around the inflection point for the denser systems (Au10nm, P50D35), characteristic of strong damping due to interparticle coupling (panels B, D). Previous theoretical work on similar systems did not include the effect of the phase shift upon reflection, treating the system as a regular mirror, which lead to poor agreement with the experimental results. The observed long-range oscillations of the plasmon peak are thus the result of superposition of the plasmon spectra with thin-film interference, not related to the plasmon decay length. Concurrent with our work, Saison-Francioso et al. also studied the long-range effects seen in LSPR transducers in terms of Fabry−Pérot modes using a modified Green’s Tensor and FDTD (finite difference time domain) modeling.81

3. MEASUREMENT MODE The LSPR band can be monitored using transmission or reflection measurements, with the choice typically dependent on experimental considerations (e.g., substrate transparency, instrument setup), and both modes are often used. However, the information provided by either measurement is not equivalent. Light entering the sample can follow three possible channels: transmission, absorption, and scattering (specular or diffuse). The transmitted radiation, exiting the sample at the end opposite the incident light, is the radiation that was not absorbed or scattered (though with a small contribution of front-scattered light). Thus, transmission (or extinction) measurements combine information about scattering and absorption. The scattering and absorption cross sections have different intensities and wavelength dependencies, leading to the difference between the results of transmission and reflection measurements.82−85 These differences raise the question of whether the SP response of the two modes to RI changes is different. In 2003, Khlebtsov et al. modeled the scattering and extinction spectra of Au colloids, with the results showing a similar response for either measurement mode.48 In 2009, Svendendahl et al. compared the performance of LSPR transducers in the transmission and (back) reflection modes

Figure 10. Experimental (A) transmission and (B) reflection spectra, shown using a color map, and (C) wavelength shift and intensity change of the transmission minimum for Au5nm samples coated with 15−348 nm SiOx films. Reproduced from ref 78.

We analyzed the oscillations in intensity as a function of coating thickness in all experimental and model systems, at each wavelength, using the modified asymmetric etalon eq 479 IR =

(A − 2 cos(

2πnt ω

+p

))R

( 2πωnt + p)

1 + R2 − 2R cos

(4)

where IR is the measured reflectance intensity, A is a parameter related to the reflection coefficient, n is the coating RI (constant, 1.46), t is the coating thickness, ω is the oscillation periodicity, p is the oscillation phase with respect to coating thickness, and R is the reflectivity of the etalon. The results of the fit for some of the systems are shown in Figure 12. As expected, the reflectivity is higher for larger particles and for denser films (panels A, C). The peaks for the denser films (the G



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Figure 12. Etalon reflectivity (A,C) and phase (B,D) derived from the etalon model for the experimental systems (A,B) and the P50 model systems (C,D). Reproduced from ref 78.

for thin-layer adsorption. The authors concluded that there is no difference in the SP peak wavelength shift, although the relevant figure in that paper shows a slight advantage of the reflection mode.86 We studied the RIS of evaporated and annealed (10 h at 580 °C) Au nanoisland films of seven different average sizes and an immobilized Au NP film in the transmission and reflection modes.87 The measurements entailed recording the spectra of the samples in solvents of different RIs; the slope of the LSPR peak wavelength shift as a function of RI is the RIS (Figure 13). We found consistently higher RIS in the reflection mode, by 42−105% for the evaporated films (Figure 14) and by 180% for the immobilized solution-synthesized Au NPs. As previously discussed, the RIS measurement does not take into account the effect of the plasmon decay length on the transducer sensitivity, and hence one cannot draw immediate conclusions regarding thin layer sensing in transmission or reflection modes from the previous results alone. To examine the situation in a realistic sensing scenario, where the RIS and decay length are both involved, we examined the response to dielectric overlayer adsorption for three types of Au nanoisland films, ranging from 20 to 100 nm average in-lane diameter (3 to 10 nm nominal thickness), finding distinctly larger plasmon peak wavelength shifts in the reflection mode in all cases for overlayers up to ca. 20 nm thick (Figure 15). In later work, we compared the response of LSPR transducers to thin-layer adsorption in the transmission and reflection modes for measurements in air or water.88 In that study, we evaluated the response by comparing intensity

Figure 13. Plasmon peak wavelengths for 5 nm (nominal thickness) Au nanoisland films, annealed, and immobilized Au NP samples, measured in air (only the nanoisland films) and in solvents of varying refractive index in the transmission (T) and reflection (R) modes. The lines represent linear regressions of the data in solvents, used for calculation of the RIS; the slopes, in nm/RIU, are given next to the respective lines. Data points for islands and NPs are the mean of four and six samples each, respectively; error bars represent standard deviations. Reproduced from ref 87.

changes at a single wavelength and evaluated the responses using a newly defined sensitivity parameter, S value, explained H



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Figure 16. RIS determined by immersion in solvents of different RIs of gold nanoisland slides of seven nominal thicknesses (3−10 nm, indicated) as a function of the plasmon peak wavelength in EtOH in the transmission and reflection modes. Data points are the mean of four samples each, and the error bars represent standard deviations.

Figure 14. RIS of the studied Au island films, measured in the transmission and reflection modes. Data points are the mean of four samples for each thickness; error bars represent standard deviations. The top axis gives the mean major axis of ellipses approximating Au islands of the corresponding nominal thicknesse based on HRSEM image analysis. Reproduced from ref 87.

techniques of comparable experimental complexity. Consideration of the relative merits of sensing methods calls for simple parameters that can quantify the sensing performance and allow a comparison between different methods as well as between different LSPR transducers. Various suggestions for quantification methods have been presented over the years. A widely used option is the figure-of-merit (FoM), which has several definitions in the context of plasmonic sensing, all of which are quite problematic. The most common definition of the FoM in LSPR sensing is RIS/Γ, where Γ is the plasmon line width, as full width at half-maximum (fwhm).92 This definition of the FoM recognizes that peak shifts are easier to measure for narrower peaks, but neglects the crucial aspect of distance dependence. In 2009, Unger et al. discussed this issue in detail and suggested a new FoM, taking into account the field confinement (decay length), sources of noise (instrument, signal and background), and analyte properties.93 The same year, Nusz et al. developed a model for the molecular detection limit (MDL) of a plasmonic NR-based transducer.94 The MDL is the minimal number of bound molecules that can be detected, and in Nusz’s model it depends on the relative sizes of the sensing and analyte volumes, the uncertainty in peak determination, the spatially dependent RIS (decay length), and the RI difference between the analyte and the medium. In 2010, Otte et al. introduced a FoM applicable to both LSPR and SPR transducers to facilitate comparison between the two, finding a somewhat higher sensitivity for LSPR.95 The same year, Becker et al. formulated a different FoM, denoted FOM*, based on intensity variations rather than peak wavelength shifts.92 The parameter for thin layers, FOM*layer, was defined as the relative change in signal intensity, divided by layer thickness, at a single wavelength (chosen to provide a maximal FOM*layer). In 2013, Valsecchi et al. published a highly detailed discussion concerning the assessment of plasmonic sensor performance.96 While their focus is on periodic structures, the quantification methods are valid for all plasmonic transducers. Comparison. While studies in the field of LSPR sensing commonly describe new types of transducers or proof-ofconcept for new sensing scenarios (antibody−antigen, proteincarbohydrate, etc.), quantitative comparisons with competing technologies (other than SPR) are hard to come by. The primary objective of the majority of LSPR transducers is biosensing, and hence the response to small analytes, sometimes in submonolayer coverage, is of major interest.

Figure 15. Plasmon peak wavelength shift upon adsorption of polyelectrolyte layers for 3, 5, and 10 nm (nominal thickness) nanoisland films (indicated) in the transmission (black symbols) and reflection (red symbols) modes (indicated). Sample preparation followed the same procedures as in ref 72, and measurements were performed as in ref 87.

later (Section 4). We found that reflection-mode measurements provide superior sensitivity in all cases (Figure 17A), confirming our previous observations. Miller et al., using theory and calculations, predicted that the RIS is a linear function of the plasmon peak wavelength.89 This correlation has been reported by various authors,70 including our group.90,91 It appears to hold also for the increased RIS of reflection mode measurements (Figure 16). The peaks in reflection spectra are wider and flatter than the corresponding transmission spectra, increasing the inaccuracy in peak determination, evidenced by the larger error bars (Figures 14 and 16).

4. COMPARISON WITH RELATED OPTICAL TECHNIQUES Quantification. LSPR sensing, as an emerging technology, must compete with, and ideally out-perform, existing optical I



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Early work in our group concerned the submonolayer sensitivity of several LSPR transducers, finding it to be comparable to that reported for SPR transducers.97 In 2009, Svendendhal et al. compared the response to thin-layer binding (using the biotin−avidin system) of SPR and LSPR transducers, the latter using either transmission or back-reflection.86 The authors found comparable performance for SPR and LSPR when measuring the LSPR peak shift. They also comment on the irrelevance of the RIS and FoM (RIS/Γ), both much higher for SPR, in predicting the response to thin layer adsorption, because these neglect the effects of field confinement. The following year, Otte et al. compared LSPR and SPR transducers, concluding that LSPR offers 15% better surface sensitivity.95 In 2012, we explored the relative merits of LSPR transducers and Fabry−Pérot based interferometers (FPbIs), utilizing a new sensitivity parameter (“S value”).88 The S value takes into account both the absolute and relative changes in intensity (measured at a single wavelength) upon analyte adsorption and is defined as S = ΔI·(ΔI/I), where ΔI is the absolute change in transmittance or reflectance upon adsorption and I is the mean of the transmittance or reflectance before and after adsorption.88 Fabry−Pérot-based interferometers (a method otherwise known as reflectometric interference spectroscopy, or RIfS; the device is also known as etalon) are composed of a reflective layer (e.g., a metal film on a substrate) coated with a transparent spacer (interference layer) terminated with a recognition interface to which an analyte can be bound.98,99 Several varieties of this system have been developed and used in the past, including use in the transmission mode,100 and combined with SPR.101 In 2002, Hänel et al. compared the performance of RIfS and SPR, concluding that the two techniques offer a comparable sensitivity.102 We developed an interest in such systems following our work on long-range oscillations in the LSPR peak, which are the result of interference effects (see Section 2).78 Because FPbI and LSPR transducers are quite similar in construction and operation, it was intriguing to compare their sensing performance. Our test case was a 2.1 nm analyte layer adsorbed onto a 2.1 nm recognition layer; we found that the LSPR transducers offer substantially higher S values for measurements in both wet and dry states (Figure 17). A notable difference between the methods is that in FPbI the measurement wavelength can be freely chosen (although with a reduced sensitivity at longer wavelengths), whereas in LSPR systems deviating from the plasmon peak wavelength in either direction quickly reduces the sensitivity. (See figure S1 in ref 88.) Thicker recognition interfaces greatly reduce the response for LSPR (because the analyte is farther from the NPs) but make no difference for FPbI because the thickness of the interference layer can be simply reduced to compensate for the thicker interface. Thicker analytes reduce the LSPR transducers’ sensitivity advantage as well due to the transducers’ exponentially decaying response (Figure 18). We thus conclude that LSPR transducers are superior for thin analytes and recognition layers (several nanometers each), whereas FPbI gains advantage for thicker layers as well as when flexibility in the measurement wavelength is required (for instance, due to the overlap of the plasmon peak with absorbing species in the measurement solution).

Figure 17. (A) Experimental sensitivity values in air and in water for the LSPR transducers. T and R denote transmission- and reflectionmode measurements. (B) Calculated sensitivity values in air and in water for the interference-based transducers, measured at wavelengths of 400 and 800 nm (indicated). All values are for a 2.1 nm analyte layer adsorbed onto a 2.1 nm recognition layer. Reproduced with permission from ref 88. Copyright 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

5. SANDWICH ASSAYS Analytes studied in biosensing applications can range in dimensions from small molecules of ≤1 nm to protein complexes tens of nanometers wide. Smaller analytes usually produce a weaker response and may therefore be difficult to detect, which is why larger labels (e.g., proteins, NPs) are sometimes recruited to aid in the detection by binding to the small analyte and enhancing the signal. For substrate-based transducers, this transducer/analyte/label scheme is commonly known as the sandwich configuration. This enhancement approach requires the analyte to possess multiple binding sites to enable binding to both the transducer and the label. In 2002, Haes et al. first used this configuration in LSPR sensing using an Ag nanotriangle array-based transducer with the biotin−streptavidin system.51 Following adsorption of streptavidin (the analyte), the transducer was exposed to biotinylated Au NPs, which bind to streptavidin, producing a large shift in the resonance frequency as a result of the large change of the local dielectric properties. In 2003, Hutter et al. used Au nanoislands functionalized with DNA, to which a complementary DNA (the analyte) was attached, the latter labeled with an Au or Ag NP, thus greatly increasing the LSPR signal.103 In 2005, Haes et al. implemented an antibody sandwich assay on Ag nanotriangles to study a possible Alzheimer’s disease pathogen.104 In 2012, Guo et al. utilized a similar approach with gold NRs and an aptamer−antigen− antibody sandwich assay.105 Lee et al. took the antibody J



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4 nm) red shift of the LSPR peak (Figure 19A). As the SP peaks of the islands and the NPs largely overlap, it is difficult to

Figure 19. UV−vis spectra (left) and HRSEM images (right) corresponding to the binding of mannose-coated Au NPs (ManNPs) to Con A bound to mannose-modified ∼35 (A) and ∼300 nm (B) (average diameter) Au NP films, annealed. Spectra were recorded in solution after formation of a mannose SAM (black lines), binding of Con A (red lines), and incubation with Man-NPs (blue dashed-dotted lines). Inset in (A): difference spectra obtained by subtracting the spectrum recorded after formation of the mannose SAM from the spectrum after binding of Con A (red line) and the spectrum after binding of Man-NPs (blue line). Inset in (B): tilted projection of a single island coated with Man-NPs in a sandwich configuration. Scale bars: 200 nm. Reproduced from ref 109.

Figure 18. (A) Experimental reflectance of an Au5nm LSPR transducer (average of two samples) and calculated reflectance of a 130 nm ZrO2 based interference transducer with a 78.7 nm spacer, for increasing PE analyte thickness on a 2.1 nm recognition interface, measured in air. (B) Sensitivity values for the same transducers. Reproduced with permission from ref 88. Copyright 2012 WILEYVCH Verlag GmbH & Co. KGaA, Weinheim.

distinguish their individual responses; however, a difference spectrum (Figure 19A, inset) shows a shoulder to the left of the main plasmon peak in the range of the colloid SP (∼525 nm). The NPs are also visible in HRSEM imaging (Figure 19A); however, the similarity in size hampers the possibility to distinguish between the NPs and the nanoislands. These difficulties were largely alleviated by using much larger Au nanoislands, ca. 300 nm in diameter, displaying a substantially longer SP wavelength, ∼805 nm. Binding of the NP labels to Con A bound to the large nanoislands produced a much larger red shift (∼50 nm) and intensity increase in the LSPR band as well as the appearance of a short wavelength peak in the vicinity of the small NPs’ SP (Figure 19B). In this case, the small NPs are clearly distinguishable in HRSEM imaging (Figure 19B). In control experiments, galactose-functionalized NPs produced essentially no response. As a result of the close proximity of the nanoislands and the Man-NPs in both systems, new coupled plasmon modes are expected to arise. The short wavelength peak observed in the spectra is likely to be composed of two contributions, one from the high-energy component of a nanoisland/Man-NP coupled mode and the other from the single Man-NP mode. It is difficult to ascertain the exact composition of the observed peak in these systems. Use of mannose-stabilized Au NP labels improves substantially the detection limit. Moreover, because the mannosefunctionalized NPs bind specifically to Con A, and not to many other proteins that may be bound to the transducer due to nonspecific binding, the NPs also improve the selectivity. Hence, the plasmon response to adsorption of Con A as well as to subsequent adsorption of mannose-functionalized NPs was measured in the presence of a large excess of the nonspecific protein BSA. Exposure to BSA alone produces a minimal

sandwich a step further, connecting an enzyme to the antibodies of the outer layer; exposure to a solution containing the enzyme’s substrates resulted in product precipitation on the Au nanodisk array, further shifting the resonance.106 In 2013, Spadavecchia et al. published a variation on Hutter et al.’s 2003 work, comparing the results of two different types of plasmonic NP labels, that is, NRs and nanostars, in the amplification step.107 Note that the authors seem to have erroneously assigned an extinction peak at 429 nm to the plasmon resonance in Au nanostars; this wavelength is far shorter than the plasmon wavelength of Au NPs. The peak arises most likely from residual Protoporphyrin IX, used in the nanostars’ synthesis.108 In 2012, our group (in collaboration with P. Seeberger, MaxPlanck-Institute of Colloids and Interfaces, Potsdam) utilized LSPR transducers to study protein−carbohydrate interactions. Au nanoislands were functionalized with a self-assembled monolayer (SAM) of PEG-thiol modified D-(+)-mannose to bind the analyte, that is, the tetrameric lectin protein Concanavalin A (Con A).109 Con A selectively binds to mannose and not to similar sugars such as galactose, which was used as a control in this study. The protein has four active sites; hence when it binds to the sugar SAM on the transducer surface some of these sites are available for binding additional mannose molecules. The initial response was amplified using a sandwich configuration, that is, by binding 16 nm (diameter) mannose-functionalized Au NP labels to the Con A bound to the sugar SAM on the Au nanoislands. When using a transducer comprising small (∼35 nm diameter) nanoislands, the adsorbed Au NPs promote a large increase in intensity and a small (3 to K



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their plasmon spectra and RIS; however, measurement of the latter was hampered by the presence of a native oxide layer, as the authors noted.114 They concluded that for triangular NPs of similar size and shape, the plasmon peak wavelength shows the order Au > Cu > Ag > Al, whereas the order of the fwhm (full width at half-maximum) is Al > Au > Ag > Cu. The plasmon resonance of Au is tunable from ∼530 nm to the NIR, depending on size and shape, whereas that of Al is in the nearUV. The combination of a resonance in the visible range, and a relatively narrow resonance, makes Cu a particularly intriguing candidate. Langhammer et al. studied the plasmon spectra of Al nanodisks of various diameters and observed a red shift of the peak over time, attributed to a growing oxide layer.115 In 2009, Pastoriza-Santos et al. synthesized Cu NPs in solution and monitored the change of the plasmon band over time due to oxidation.116 In 2011, Schwind et al. measured the corrosion kinetics of Al nanodisks, by either monitoring the plasmon spectra (which changed due to the growth of an oxide layer as well as changes in the particles’ shape) or measuring mass change using QCM.117 Zorić et al. explored the peak positions, line width, and underlying physical mechanisms of plasmons in Au, Pt, or Al nanodisks.118 Kim et al. formed arrays of Cucoated SiO2 NPs, measured their RIS, and used them for multiplexed DNA sensing.119 In 2012, Sekhon et al. presented a model and used it to calculate the RIS and sensing figure-ofmerit (FoM) for NRs of Au, Cu, Ag and Al of various aspect ratios.120 In 2013, Schwind et al. studied SPR and LSPR bands in Au and Al nanohole arrays and used the LSPR band to follow the corrosion of Al under ambient conditions.121 McMahon et al. theoretically explored the possibility of using poor metals (Al, Ga, In, Sn, Tl, Pb, and Bi) for plasmonics in the near- to far-UV range, finding sensitivities similar to those of Ag and Au.122 More recently, efforts have been devoted to expanding the scope of plasmonics beyond metals. In 2010, West et al. discussed a variety of plasmonic materials, including metals, metallic alloys, semiconductors, and graphene, focusing on applications such as wave-guiding rather than sensing.123 A 2013 review by Naik et al. had a similar focus.124 These authors suggested the use of transparent conductive oxides (TCOs) as LSPR materials in the NIR, with quality factors similar to those of metallic particles.125 Guler et al. studied the use of nitrides for LSPR, specifically TiN for sensing in the NIR (800−1300 nm) and ZrN for the visible range because it exhibits a resonance band similar to that of Au.126 In 2012, our group introduced fabrication of Cu or Cu2O NP films on glass substrates by means of chemical (electroless) deposition (CD).127 Preparation of Cu or Cu2O NPs was controlled by varying the CD solution composition (Figure 21). The Cu NPs display a SP band around 600 nm, whereas the Cu2O NPs show a characteristic extinction band between 400 and 550 nm. The initial step in the CD involved deposition of Au seeds on the substrate, by adsorption of Au ions onto aminosilane-modified glass substrates, followed by reduction, to form Au clusters serving as nucleation centers for subsequent Cu or Cu2O deposition. It was found that the size and spatial distributions of the Cu2O NPs are superior to those of the Cu NPs (Figure 21). Hence, an alternative Cu NP fabrication scheme was presented, entailing chemical reduction of Cu2O NP films (Figure 22). Both Cu2O and Cu NP films exhibit strong adhesion to the glass, showing no substantial spectral changes upon rinsing and drying.

extinction change, within the level of instrument noise. Con A can be detected above ca. 50 nM without the NPs, while the detection limit is reduced to

Critical Issues in Localized Plasmon Sensing - ACS Publications

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