NANO LETTERS
Plasmon Resonance in Silver Nanoparticles Arrays Grown by Atomic Terrace Low-Angle Shadowing
2008 Vol. 8, No. 10 3248-3256
Floriano Cuccureddu,*,† Shane Murphy,† Igor V. Shvets,† Mauro Porcu,‡ and H. W. Zandbergen‡ Centre for Research on AdaptiVe Nanostructures and NanodeVices (CRANN), School of Physics, Trinity College, Dublin 2, Ireland, and National Centre for High Resolution Electron Microscopy, Department of Nanoscience, Delft Technical UniVersity, Lorentzweg 1, 2628 CJ, Delft, The Netherlands Received June 4, 2008
ABSTRACT The plasmonic properties of aligned silver nanoparticles grown by atomic terrace low-angle shadowing (ATLAS) were studied by optical transmission spectroscopy. ATLAS is a novel nanofabrication technique that combines the advantages of self-assembly with control of the nanostructure features. The silver nanoarrays were optically characterized and distinct optical responses with strong polarization dependence were obtained indicating the existence of a strong near-field coupling between the particles. We found that different morphologies gave rise to a similar optical response due to the local contributions to the overall response. Numerical model based on discrete dipole approximation was used to give a qualitative insight into the studied phenomena.
The interaction between an external electromagnetic field and electrons results in an oscillating dipole field. This may cause strong coupling between the light and the material at a resonance frequency within the visible wavelength range.1 This phenomenon is called surface plasmon resonance (SPR). It is also referred to as localized surface plasmon resonance (LSPR) for metal nanoparticles and creates a strongly enhanced electric field on the particle surface. The structures that display plasmonic phenomena are made up of ordered nanoparticle arrays or holes. The possibility to organize the nanoparticles over a larger scale and exploit their properties can lead to a new generation of plasmonic materials with novel properties. The absorption features of the spectra, that is, peak position, line widths, and so forth, are sensitive to many parameters such as size, shape, material conductivity, and the environment’s optical properties.1 In the case of metallic nanostructures and arrays of nanoparticles, complexity is added by the interaction of the oscillating dipole fields between parts of the nanostructures or between the neighboring particles resulting in a shifted LSPR compared to a single particle LSPR frequency. In such arrays collective effects play a fundamental role. Since the plasmonic properties are dependent on interparticle interactions, one can tune the optical properties of the entire material.2,3 The near-fields of * To whom correspondence should be addressed. E-mail:
[email protected]. † Trinity College. ‡ Delft Technical University. 10.1021/nl801600w CCC: $40.75 Published on Web 09/18/2008
2008 American Chemical Society
adjacent particles interact with each other thus coupling the electron oscillations together. Linear and planar arrays of nanoparticles and planar nanostructures have an added advantage for optical and sensor applications as they could be used as the basis of the sensor.4 There are further opportunities for plasmonic devices that are easier to implement in planar geometry than in a 3D configuration.5-7 Furthermore, linear chains of metal nanoparticles and linear metal nanostructures can channel the flow of electromagnetic energy over hundreds of nanometers without significant loss due to near-field coupling, leading to applications in electromagnetic energy transport and subwavelength photonic waveguiding.8-11 Photonic scanning tunneling microscopy (PSTM) and scanning nearfield optical microscopy (SNOM) are key tools to study the coupling of the light with metal nanostructures and to determine the field distribution at the nanoscale, which is of importance in the development of light-guiding structures.12-15 On the other hand, strong amplification of the electric field has led to the development of surface-enhanced Raman spectroscopy (SERS) increasing the resolution of Raman scattering to single molecule detection.16 Much of the recent interest in this field has been powered by advances and growing expertise in fabrication methods. However, despite the progress in particle synthesis and selfassembly, one of the main difficulties for plasmon resonance analysis in nanosized structures remains the realization of
Figure 1. TEM micrographs of the alumina sample viewed along [10-10] at (a) low magnification and (b) high resolution. A 2 nm macrostep is visible as formed by the bunching of 10 monosteps.
nanostructures with well-controlled composition, size, shape, and distribution, especially forming regular arrays on substrates. Until recently, most effort has focused on nanoparticles dispersed in colloidal solutions or fabricated via a chemical route, using techniques such as spin coating.17,18 Other techniques, such as laser ablation, allow the deposition of nanoparticles on various kinds of supporting substrates. However, they usually generate random distributions of clusters with no order at all. In order to fabricate linear and ordered arrays of nanoparticles on a substrate, the bestestablished tool is electron beam lithography (EBL).10,19 At this stage, only EBL provides a high degree of control in patterning. Yet, this technique presents several drawbacks: only small areas can be covered by nanoparticles, it is a slow and expensive multistage process, and it is diffraction-limited with a resolution limit for most common EBL instruments being around few tens of nanometers. The most appealing development for the future of nanoscale processing is represented by the “bottom-up” approach because of its promise of cost-effective and large-scale production capabilities.20-22 In this paper, we concentrated on the development of a novel self-assembly fabrication technique to grow arrays of closely ordered nanostructures and show how the SPR response can be tuned by tailoring the nanoparticle features. The atomic terrace low-angle shadowing (ATLAS) is a high throughput nanofabrication technique that offers a high degree of control on the nanoparticle features using glancing angle deposition on vicinal surfaces. The shadowing effect provided by the step-and-terrace morphology facilitates generating linear arrays of material which decorate the steps. Careful choice of process parameters, such as deposition angle, deposition flux, substrate material, substrate miscut, and so forth, enables tailoring the morphology of the nanostructures with great precision. A more detailed description of the technique and the instrument can be found elsewhere.23,24 By means of ATLAS we were able to routinely produce arrays of silver nanoparticles where the optical properties, and in particular the plasmon resonance, could be investigated as a function of the particle features. Nano Lett., Vol. 8, No. 10, 2008
Figure 2. Nanoparticle size dependence on the deposition time for a deposition rate of 3.6 Å/min.
Table 1. Average Particle Size and Interparticles Distance for the Three Samples Considered
Sa15 Sa23 Sa30
deposition time [min]
average width [nm]
average spacing (peak-to-peak) [nm]
15 23 30
31.4 ( 5.6 14.7 ( 3.7 20.6 ( 3.7
55.1 ( 22.3 18.8 ( 5.8 25.3 ( 5
High purity silver (99.9%) was deposited at 3.6 Å/min on vicinal c-plane sapphire substrates (MTI Corporation25) with 3° miscut along [11-20]. The deposition time varied from 15 to 30 min. It is known that annealing of (0001) R-alumina samples for several hours in air produces a terrace-and-step morphology consisting of wide terraces separated by surface steps.26,27 TEM analysis was carried out to examine the step morphology more closely. These images (shown in Figure 1) confirm the step-and-terrace structure of the substrates. The surface of the substrate is characterized by the presence of steps at somewhat irregular intervals corresponding to the terraces whose size matches our AFM results. Figure 1 is a high resolution micrograph of the alumina sample viewed along [10-10]. Since the crystal structure of alumina is clearly visible, great attention was directed at the morphology of a single step. As can be inferred from the micrograph, the step is formed by the gathering of the monosteps, attesting that the annealing caused a step bunching process on the surface. The linear arrays of aluminum atoms are clearly visible in the high resolution micrograph in Figure 1b. In this case, the gathering of 10 monosteps by step bunching leads to the formation of a 2 nm high macrostep. The substrate was loaded on the sample holder with a beam-terrace angle of 3°. The samples were characterized by atomic force microscopy (AFM) in semicontact mode. The extinction spectra of the silver nanoparticles were recorded using a UV-vis spectrophotometer (Shimadzu UV2401PC) with reference to a sapphire substrate subjected to the same annealing procedures. Two different configurations were studied using linearly polarized light with the electric field oscillating in the substrate plane parallel (longitudinal case) and perpendicular (transverse case) to the linear arrays of particles. 3249
Figure 3. AFM image of silver array deposited on the sapphire surface by ATLAS for (a) 15 min (Sa15), (b) 23 min (Sa23), and (c) 30 min (Sa30) at 3.6 Å/min. The elongated shape in (c) is an artifact due to the scanning drift along the y-axis of the image.
Figure 4. Optical absorbance spectra with light linearly polarized (a) parallel (longitudinal component) and (b) perpendicular (transversal component) with respect to the aligned nanoparticles arrays. The resonance wavelengths are indicated by numbers.
Figure 5. Resonance wavelengths for different filling factors following the Maxwell-Garnett approximation (black squares). At low filling factors, the resonance matches the Mie solution (open circle).
The average particles sizes are reported in Table 1 for the samples considered. AFM image analysis reveals the particle shape is conical with a quite regular circular base. The scanning drift generates an apparent deformation in some images showing particles with a slightly elongated shape along the scanning direction and the AFM tip convolution gives an apparent size greater than the actual size. The data reported 3250
in Table 1 refers to the size extrapolated from the AFM images. After deposition, the silver nanoparticles lie on the terraces decorating the steps with regularity. As shown in Figure 2 the average lateral size follows a clear trend and increases with the deposition time for a constant deposition rate. However, the substrate morphology plays an important role in the way the nanoparticles grow and organize themselves on the substrate, affecting the average size values. In Figure 3, AFM scans of three samples grown using different deposition time are reported. The sample deposited for 15 min (Sa15) has wider islands that partially coalesce. These ensembles of particles are separated by several nanometers, and this affects the overall average interparticles spacing. From the analysis of particle distance based on the AFM scans, this sample shows a broad distribution of interspacings (confirmed by the high standard deviation) with a lack of regularity. The other two samples considered (Sa23 and Sa30) have nanoparticles positioned with increased uniformity with a narrower interparticle spacing distribution and in turn a lower standard deviation. Although the annealing and preparation procedure is the same for every substrate, each of them has a distinctive arrangement of steps, terraces, and coalescence points that heavily influence the nanoparticles separation and overall morphology. The optical properties of the nanoarrays were investigated by UV-vis optical analysis at normal incidence illumination and the results are shown in Figure 4. Linearly Nano Lett., Vol. 8, No. 10, 2008
Figure 6. DDA optical spectra calculations for (a) oblate and (b) prolate spheroids with different axis ratios of thickness to lateral diameter. Qext is the extinction factor equal to Cext/πa2eff where Cext is the extinction cross section and aeff is defined through the effective volume: 4πa3eff/3. The thick line indicates the red-shifted longitudinal component while the dashed line represents the blue-shifted transversal polarization.
Figure 7. DDA optical spectra calculations for a single chain made of 2, 3, and 10 aligned spheres (a). The thick line indicates the redshifted longitudinal component while the dashed line represents the blue-shifted transversal polarization. The introduction of defects in the array (panel b) causes a different response for different proximity due to the near-field interaction. Only the longitudinal component is shown.
Figure 8. Difference between longitudinal and transversal resonance frequencies as function of the particle size.
polarized light was shone parallel (longitudinal polarization, Figure 4a) and perpendicular (transverse polarization Figure 4b) to the nanoparticles chains. This configuration is insensiNano Lett., Vol. 8, No. 10, 2008
tive to any plasmon modes oriented out of the substrate plane and does not provide information on optical anisotropy in the direction perpendicular to the surface. A remarkable splitting of the peaks is clearly visible and the polarization dependence highlights that strong interparticle interactions are consistently present, which is in agreement with theoretical work already published.10,11 The longitudinal polarization of the light produces a noticeable redshift while the transversal polarization generates a blueshift, with the latter less pronounced. The peak resonance wavelength is sensitive to the sample morphology. The sample with the smallest particle width (Sa23, 14.7 nm) shows the least peak splitting and an increase in lateral size to about 20.6 nm (Sa30) generates a more significant shift due to the enhanced coupling of the adjacent nanoparticles. The sample Sa15 has an anomalous morphology with larger islands and a greater average spacing than Sa30 but the resonance frequency shifts are comparable. This situation provides a straightforward example of how the morphology of the film can directly affect the overall optical response. Nanoparticle arrays of 3251
Figure 9. DDA optical spectra calculation for (a) oblate spheroids of different effective radius and (b) the same spheroids with a comparison between absorption and scattering response.
Figure 10. AFM image of the silver arrays formed on the sapphire surface before (a) and after annealing for 30 min at (b) 200 °C and (c) 400 °C. The Fourier transform highlights the loss of asymmetry and particle alignment.
samples Sa15 and Sa30 have rather different particle size and yet, similar resonance curves. This illustrates the important role of the interparticle separation. In this particular case, a uniform and ordered structure with smaller nanoparticles presents the same optical response as one with less ordered but larger nanoparticles where the bunched areas possess an enhanced interaction which is likely responsible for the similarity of the overall resonance curves of the two samples. In principle, resonance wavelength tuning, that is, the splitting of the peak, can be due to anisotropy of the particle. Plasmon resonance of spheroids shows in fact two different peaks related to the two different axes with the splitting being related to the axis ratio.1,28 However electromagnetic interactions between nanoparticles yield complex extinction spectra where the resonances are split and this makes it difficult to separate the influence of other parameters such as the nanoparticle shape. Assuming a nonwetting interaction our nanoparticles show a conical shape with the out-of-plane axis much smaller than the inplane ones. If the nanoparticles are closely packed, the dipoles associated with each of them interact resulting in the splitting of the absorption band. Integrated optics and photonics can take advantage of linear arrays of closely spaced nanoparticles which can transport electromagnetic energy below the diffraction limit.11 The guiding and amplification of the light can be realized at smaller scale compared with normal optical 3252
waveguides, due to the near-field interaction between the metal nanoparticles. The oscillating dipole field can be expressed through the three terms29 ED)EF+EM+ER
(1)
In the quasistatic limit, R , λ, the Fo¨rster field EF, which has a d-3 distance dependence, is dominant and represents the interaction between two close dipoles. Brongersma et al. developed an analytical model that describes these interactions in the dipole limit showing the dispersion relation for coupled plasmon modes and the propagation of electromagnetic energy through corners and tees.30 Every oscillating dipole in the chain produces an electric field Ei,m(t) at neighboring locations given by Ei,m(t) )
γi pi,m(t) 4πε0n2d3
(2)
where γi is a polarization dependent constant, pi,m(t) is the magnitude of the induced dipole, ε0 is the free space permittivity, n the refractive index of the medium, and d is the center-tocenter distance between the particles. Through the model, an estimate of the group velocity Vg and the attenuation coefficient R can be obtained. The group velocity is equal to Vδ,i )
γiω21d sin(kd) ω
(3)
where ω21 determines the coupling strength and ω is the resonance frequency. In the regime of small damping, the attenuation cofficient is Nano Lett., Vol. 8, No. 10, 2008
R)
Γi 2Vg,i
(4)
Γi being the electronic relaxation frequency due to interactions with electrons, phonons, defects, impurities etc. The application of this model to nanostructures similar to those we grew experimentally (linear arrays of 15 nm large particles with a center-to-center distance of 20 nm) provides an estimate of the group velocity for the longitudinal plasmon equal to 1.3 × 109m/s. The attenuation coefficient for the propagating wave in the same direction is then 4.3 × 104 m-1 corresponding to a decay length of 25 µm. This value is in the same range as reported for metal nanowires with propagation distances that go over 10 µm and increase to 20 µm at a wavelength of 500 nm.6,31 In reality, although silver is the metal with the lowest losses in the visible spectrum, the decay length could be lower since the small volumes of the particles and the surface roughness can give rise to a higher scattering probability and defects, resulting in an increased damping of the plasma oscillation and greater energy losses.11,32 On the other hand the high proximity of the nanoparticles to each other could give rise to a better coupling and a stronger near-field interaction with enhanced propagation. Also, the interparticle distance over particle radius ratio is 2.7, close to the optimum value of 3 for which the minimum transmission loss is observed according to Quinten et al.11 Unfortunately an exact quantitative comparison with the experimental results cannot be done for various reasons. First,
in order to verify the propagation length of the plasmons only the first particle of the chain should be irradiated by the light field with the coupling being responsible for the oscillation of the rest of the chain. The experimental spectra we show were obtained by irradiating all the particles at the same time and cannot offer experimental evidence for transporting energy. Nevertheless the shift of the resonance peak proves that strong near-field coupling, which in turn is the mechanism for energy transport, is present. Assuming the validity of the model, we propose an effective way to realize aligned nanostructures which can operate as transmission lines for electromagnetic energy. Second, in the real experimental case the interchain distance is smaller than the wavelength of light and this could give rise to crosstalk between adjacent chains. However, even considering the interplay between parallel chains as a near-field interaction, the interparticle distance inside the same chain is much lower than the distance between different chains and since the nearfield shows a d-3 dependence the particle-particle interaction inside the chain is expected to be dominant. Finally, a quick estimate of the attenuation coefficient and the related signal loss can be obtained from far-field measurements evaluating the peak splitting and the line width.33 However, the experimental spectra do not allow for an estimation of the plasmon damping and the oscillation decay time since statistical effects play a substantial role and the particle size distribution is responsible for generating an inhomogeneous broadening of the absorption line.
Figure 11. Optical spectra with longitudinal (thick line) and transversal (dashed line) components for silver nanoparticles samples (a) as deposited and after annealing at (b) 200 °C, (c) 400 °C, and (d) 800 °C. Nano Lett., Vol. 8, No. 10, 2008
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A general solution of the diffraction problem of a single sphere of arbitrary material is provided within the framework of the Mie theory.34 However, although the Mie theory offers a complete exact solution of Maxwell’s equations, it is quite limited in application since it holds only for single spherical noninteracting nanoparticles in the quasi-static approximation, and it does not provide a good description for systems of interacting nanoparticles or nonspherical shapes. Effective medium (EM) theories have been developed for the evaluation of the optical properties of composite materials where the main objective is the calculation of properties of the composite from the known properties of its constituents. EM theories try to determine the dielectric function which describe the electrodynamic response of the nanoparticle ensembles in the quasi-static limit. The topology is controlled by means of the filling factor f ) Vnanoparticles/Vsample, which provides only an average value, and the further the real topology is removed from an isotropic arrangement the more the filling factor gives only a rough average. When f is very small, the optical properties of the sample equals the sum of the contributions of the individual nanoparticles as they are separated by large distances and do not interact: this is the case treated by Mie’s theory. The most used effective dielectric function is given by the Maxwell-Garnett (MG) formula, and it is limited to low filling factors.35 It gives reasonable results inside this limit and the peak shifts with increasing f but it fails for an anisotropic distribution of interacting particles. In Figure 5 the resonance wavelength is reported for different filling factors. For low f the resonance peak approaches the value consistent with Mie’s theory for nanoparticles of radius equal to 7.5 nm but the overall range of wavelength is significantly removed from the experimental results due to the difference between the real case and the approximated model. Since exact solutions to Maxwell’s equations are available only for a limited number of shapes, numerical methods have been developed in the past few years for describing nanoparticle arrays and aggregates with complex structures such as T-matrix,36 finite difference domain method (FDTD),37 and discrete dipole approximation (DDA).38,39 To better understand the nature of the resonance shift, we performed computer simulations using the DDA. The DDA method is a powerful technique that enables calculation of absorption and scattering of nanoparticles. The optical properties are obtained by representing the target as an array of polarizable point dipoles which acquire dipole moments in response to the external and local electric field. The accuracy is strictly related to the number of dipoles used to describe the target. The main drawback is the significant computational time required when the number of dipoles increases. In order to reach an acceptable compromise, we used a number of dipoles higher than 15 000 for each simulation with a wavelength resolution of 0.5 nm. AFM analysis shows that the width of the nanoparticles is much greater than their height. In particular, Sa23, the sample we propose to model, has an average particle width of 15 nm and height of around 1.5 nm; thereby it cannot be suitably represented either by a sphere or an ellipsoid. The 3254
most appropriate shape to consider is a spheroid. Geometrically two kinds of spheroids can be identified: prolate spheroids have two short and one long axes with the revolution axis parallel to one of the major axes while oblate spheroids have two long and one short axes with the revolution axis along the short axis. Since oblate spheroids resemble more closely the shape of the experimental nanoparticles, we simulated the absorption spectra of silver oblate and noninteracting nanoparticles through DDA using this configuration with the field parallel to the long axis. For all the calculations, the bulk dielectric constant for silver as measured by Johnson and Christy was used.40 The results for different ratios are reported in Figure 6a. The axes ratio resulting from AFM analysis corresponds to 0,1. The corresponding simulation shows a resonance peak above 600 nm. When the ratio of thickness to width is increased, the particle is ideally deflattened and the peak blueshifts to higher frequencies. In particular the resonance wavelength corresponding to a ratio of 0.2 is 480 nm, and this value is located in between the two experimentally observed peaks. One can expect that ideal oblate noninteracting nanoparticles would generate a peak in this area. This result suggests that the axes ratio for the experimental sample is closer to 0.2 than 0.1 and consequently the particle size assessed by AFM is lacking in accuracy. It is actually known that AFM tends to overestimate the particle size due to tip convolution. The real nanoparticle width is likely to be around 12-13 nm with a height of 2-2.5 nm. As previously stated, in principle the peak splitting can occur even though the nanoparticles do not interact with each other. Shape effects strongly influence the number of plasmon modes and the position of the resonance peak so that for spheroidal or ellipsoidal particles the ratio between the axes is a fundamental parameter. Noninteracting oblate spheroids have two plasmon modes due to the presence of long inplane axes and a short out-of-plane axis. Since the experimental setup used does not allow for exciting the perpendicular mode (the light is shone normally to the surface) and both in-plane directions have the same mode (the two inplane axes are equal), a mere oblate shape does not account for the peak split. The same conclusion is arrived at when considering prolate spheroids. As for the oblate case, noninteracting prolate spheroids have two resonance modes which can both be excited at normal incidence and Figure 6b shows DDA spectra of prolate spheroids with different axes ratio. The simulation results show that a larger ratio corresponds to a larger shift but the wavelength values are significantly blue-shifted compared to the experimental ones. Thus the experimentally observed splitting cannot be assigned to shape effects of noninteracting nanoparticles and the optical properties are determined by the electrodynamic interaction between the particles. When the light is polarized along different directions it stimulates direction-dependent interactions that give rise to different optical responses. This is shown in Figure 7 where DDA is applied to arrays of spherical particles with a diameter of 15 nm and a separation along the chain of about 4 nm. An increase in the number of nanoparticles, from 1 to 10, creates an enhanced collective Nano Lett., Vol. 8, No. 10, 2008
behavior responsible for the red- (longitudinal polarization) and blue-shifts (transversal polarization). The mismatch in the resonance wavelength is due to the difference between the model assumed and the real sample: size, shape, particle size dispersions and interparticle separation dispersion play an important role. Nevertheless the model is able to qualitatively depict the system and reproduce the experimental features. Since the presence of defects inside the array could affect the overall optical response compared to a regularly spaced array, we simulated a linear array of 10 nanoparticles where two of them inside the chain are separated by different distances. The results are reported in Figure 7b. The difference in the optical response is due to a d-3 distance dependence: the increased (or decreased) proximity of the two particles affects the peak position as a result of the enhanced (or reduced) near-field interaction. However, there is a maximum distance after which the interaction is no longer significant and the response does not change. In order to explain the polarization dependence of the extinction peaks, a simple dipole-dipole interaction model can be recalled.19 When polarized light strikes the sample, the electromagnetic field excites the electron oscillation generating surface charges in every particle. In the case of longitudinal polarization, the closely spaced particles will be oriented with attractive electrostatic interaction and this will weaken the internal forces bringing charges to equilibrium and resulting in a lower resonance frequency and a strong red-shift of the plasmon peak. Conversely, in the transverse case the charge displacement by the electromagnetic wave brings like charges closer increasing the repulsive interaction along the chain and increasing the resonance frequency with a consequent blue-shift of the band. In Figure 8, the difference in resonance frequency between two different polarization directions is reported as a function of the particle size as obtained from the experimental results; as a result of the enhanced interaction, the difference between the resonance frequencies increases. Finally the volume dependence of the resonance peak was simulated. Figure 9a shows the optical response of oblate spheroids with different effective radii. As the volume changes, the resonance wavelength seems almost unaffected suggesting that the volume effects are not as strong as the shape effects. In Figure 9b, absorption and scattering components are compared for the different volumes considered. As expected for nanoparticles with a small radius, the extinction is due almost exclusively to the absorption with the scattering component barely visible only for the widest radii. We also studied the evolution of the optical response when the silver nanoparticles are annealed in air. The annealing time was 30 min, and the annealing temperature was in the range from 200 to 800 °C. The annealing causes a change in surface morphology (Figure 10) and relative change in the optical response (Figure 11). After 30 min at 200 °C, the nanoparticles start to coalesce and overcome the steps creating a slight loss of asymmetry with a reduced splitting of the peaks. At 400 °C anneal temperature, the particles become larger than 100 nm and no longer ordered along the Nano Lett., Vol. 8, No. 10, 2008
chains; the sample becomes more isotropic as confirmed by the near absence of peak splitting. Increasing the temperature to 600 °C levels the resonance peak, which eventually disappears after annealing at 800 °C with the silver film being completely oxidized. In conclusion, we have studied the plasmon coupling in ordered silver nanoparticles chains. The nanoarrays were grown on vicinal sapphire substrates by ATLAS technique, which allows tailoring of particle features by modulating the growth parameters. We studied the dependence of the optical response on the polarized light for longitudinal and transversal component as a function of the particle size. We showed that the peak can be tuned and the resonance position is strictly related to the nanoparticles size and their proximity to each other as well as their organization on the substrate. Such structures could find application in subwavelength energy transport for a new generation of photonic circuits. Acknowledgment. The financial support of the Science Foundation Ireland, Contract No. 06/IN.1/I91, is gratefully acknowledged. References (1) Kreibig, U.; Vollmer, M. Optical Properties of Metal Clusters; Springer: Berlin, 1995. (2) Pendry, J. B. Phys. ReV. Lett. 2000, 85, 3966. (3) Grigorenko, A. N.; Geim, A. K.; Gleeson, H. F.; Zhang, Y.; Firsov, A. A.; Khrushchev, I. Y.; Petrovic, J. Nature 2005, 438, 335. (4) Haynes, C. L.; Van Duyne, R. P. J. Phys. Chem. B. 2001, 105, 5599. (5) Krenn, J. R. Nat. Mater. 2003, 2, 210. (6) Barnes, W. L.; Dereux, A.; Ebbesen, T. W. Nature 2003, 424, 824. (7) Bozhevolnyi, S. I.; Volkov, V. S.; Devaux, E.; Laluet, J. Y.; Ebbesen, T. W. Nature 2006, 440, 508. (8) de Waele, R.; Koenderink, A. F.; Polman, A. Nano Lett. 2007, 7, 070807. (9) Maier, S. A.; Brongersma, M. L.; Kik, P. G.; Meltzer, S.; Requicha, A. A. G.; Atwater, H. A. AdV. Mater. 2001, 13, 1501. (10) Maier, S. A.; Kik, P. G.; Atwater, H. A.; Melyzer, S.; Harel, E.; Koel, B.; Requicha, A. A. G. Nat. Mater. 2003, 2, 229. (11) Quinten, M.; Leitner, A.; Krenn, J. R.; Ausseneg, F. R. Opt. Lett. 1998, 23, 1331. (12) Krenn, J. R.; Dereux, A.; Weeber, J. C.; Bourillot, E.; Lacroute, Y.; Goudonnet, J. P.; Schider, G.; Gotschy, W.; Leitner, A.; Aussenegg, F. R.; Girard, C. Phys. ReV. Lett. 1999, 82, 2590. (13) Salakhutdinov, I.; Thakur, J. S.; Leosson, K. J. Appl. Phys. 2007, 102, 123110. (14) Gademann, A.; Shvets, I. V.; Durkan, C. J. Appl. Phys. 2004, 95, 3988. (15) Durkan, C.; Shvets, I. V. J. Appl. Phys. 1998, 83, 1837. (16) Kneipp, K.; Wang, Y.; Kneipp, H.; Perelman, L. Y.; Itxkan, I.; Dasari, R. R.; Feld, M. S. Phys. ReV. Lett. 1997, 78, 1667. (17) Choi, B.; Lee, H.; Jin, S.; Chun, S.; Kim, S. Nanotechnology 2007, 18, 075706. (18) Tamaru, H.; Kuwata, H.; Miyazaki, H.; Miyano, K. Appl. Phys. Lett. 2002, 80, 1826. (19) Rechberger, W.; Hohenau, A.; Leiner, A.; Krenn, J. R.; Lamprecht, B.; Ausseneg, F. R. Opt. Commun. 2003, 220, 137. (20) Fort, E.; Ricolleau, C.; Sau-Pueyo, J. Nano Lett. 2003, 3, 65. (21) Oates, T. W. H.; Keller, A.; Facsko, S.; Ma¨ucklich, A. Plasmonics 2007, 2, 47. (22) Camelio, S.; Babonneau, D.; Lantia, D.; Simonot, L. Europhys. Lett. 2007, 79, 47002. (23) Shvets, I. V.; Wu, H. C.; Usov, V.; Cuccureddu, F.; Arora, S. K.; Murphy, S. Appl. Phys. Lett. 2008, 92, 023106. (24) Cuccureddu, F.; Usov, V.; Murphy, S.; O’Coileain, C.; Shvets, I. V. ReV. Sci. Instrum. 2008, 79, 053907. (25) Sapphire crystals substrates; MTI Corporation, 860 South 19th Street, Richmond, CA 94804, (www.mtixtl.com). (26) Heffelfinger, J. R.; Bench, M. W.; Carter, C. B. Surf. Sci. 1997, 370, L168. (27) Pham Van, L.; Kurnosikov, O.; Cousty, J. Surf. Sci. 1998, 411, 263. 3255
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