Correlating Electron Tomography and Plasmon Spectroscopy of

Dec 14, 2011 - Electron tomography allows segmentation of the particles into core and shell ... TEM images of individual nanoparticles taken in the br...
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Correlating Electron Tomography and Plasmon Spectroscopy of Single Noble Metal Core−Shell Nanoparticles Lev Chuntonov,† Maya Bar-Sadan,‡ Lothar Houben,‡ and Gilad Haran*,† †

Department of Chemical Physics, Weizmann Institute of Science, 76100, Rehovot, Israel Ernst Ruska-Centre for Microscopy and Spectroscopy with Electrons, Research Centre Jülich, 52425, Jülich, Germany

‡

S Supporting Information *

ABSTRACT: The 3D structure reconstruction of gold core−silver shell nanoparticles by electron tomography is combined with optical dark-field spectroscopy. Electron tomography allows segmentation of the particles into core and shell subvolumes and facilitates avoiding Bragg diffraction artifacts inherent in 2D images. This advantage proves essential for accurate correlation of plasmon spectra and structure. We find that for the nanoparticles of near-spherical shape studied here the plasmon resonances depend on the relative size of the core and shell, rather than on their exact shapes and concentricity. A remarkable dependence of the spectral shape on the permittivity of the surrounding medium is also demonstrated, suggesting that core−shell nanoparticles can be used as ratiometric sensors with a very high dynamic range. KEYWORDS: Electron tomography, dark-field spectroscopy, bimetallic core−shell nanoparticles, nanoplasmonics

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The average diameter of the nanoparticles was 50−60 nm, and the core−shell size ratio was systematically varied. TEM images of individual nanoparticles taken in the bright-field mode on an FEI Tecnai F20 microscope at 200 kV acceleration voltage demonstrated the presence of a gold core with a darker contrast than the surrounding silver shell. However, these images did not allow accurate determination of core and shell dimensions. In particular, the boundary between the gold core and the silver shell was found to be quite difficult to trace because of the 2D projection. A further and even more intractable complication was Bragg diffraction by crystalline lattice planes at certain viewing directions in the TEM. Bragg diffraction produces sharp contrast stripes in the image of a crystalline particle that may be falsely interpreted as material boundaries. Many forms of electron tomography can be used to provide three-dimensional information of materials across a range of length scales; the majority of these techniques use 2D projection images.35 In the basic form of electron tomography, a set of 2D images of a 3D object is taken at a sequence of sample tilt angles. Then the images are “back-projected” to reconstruct the object, e.g., by applying the inverse Radon transform.38 In this procedure each image out of the 40−60 images in the set contributes in an additive way to the overall intensity of the 3D reconstruction. In such a way, the signal-tobackground ratio improves and the structural features are enhanced against the background. Artifacts such as lowintensity Bragg diffraction stripes in a few images of the tilt series will account for only a minor change in the overall intensity and will not smear the structural features. In the case

oble metal nanoparticles are of broad scientific and technological interest due to the way they interact with light via strong plasmon resonances in the visible and nearinfrared region.1,2 They find application in a broad range of fields from nano-optics3,4 and spectroscopy5,6 to sensing7 and biomedicine.8 The optical properties of metal nanoparticles strongly depend on their shape.9−15 Accurate knowledge of the shape becomes especially important when composite nanoparticles are considered. The optical properties of core−shell nanoparticles can be tuned over a wide range by controlling their composition and geometric parameters, in particular the relative dimensions and shapes of the core and the shell.16−23 Bimetallic nanoparticles with a gold core and a silver shell (or vice versa) provide a remarkable example within this category.24−31 While qualitative understanding of the optical properties of such nanoparticles has been achieved,32,33 the heterogeneity of many preparations makes the quantitative interpretation of plasmon spectra challenging.24−26 By correlating single particle spectroscopy and high-resolution transmission electron microscope (TEM), it is possible to study the effect of shape and size on plasmonic properties without resorting to ensemble averaging.9,34 Electron tomography has been recently recognized as an emerging technique for 3D characterization.15,35,36 It is particularly useful for the study of composite nanoparticles, as it can in principle obtain an accurate map of their internal structure. In this paper, we combined electron tomography with single-particle plasmon spectroscopy and numerical electromagnetic calculations in order to provide a quantitative correlation of structure and spectrum. We studied metal nanoparticles with gold cores and silver shells that were synthesized using methods described before.37 © 2011 American Chemical Society

Received: September 14, 2011 Published: December 14, 2011 145

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of high-intensity stripes due to the Bragg diffraction, single images may be eliminated from the tilt series, but in general it is preferred to avoid acquiring tilt series of particles oriented with strongly reflecting planes. Once the Bragg artifacts are avoided, the reconstruction produces tomograms with high contrast between the heavy Au and the much lighter Ag, which allows for a reliable determination of the threshold for core−shell segmentation. In addition, acquiring data at low dose conditions allows completing the tilt series without noticeable changes to the core−shell structure due to radiation damage. The quality of the reconstructed tomogram depends on parameters such as the tilt range, the tilt increment, and the back-projection algorithm. In the current research, images were collected at a tilt range of +70° to −70° with incremental steps of 3°. Standard electron tomography methods are generally time-consuming in both acquisition and reconstruction. Therefore there are only a few examples in the literature of high-resolution tomograms for the 3D characterization of nanoparticles.15,36 A key issue for the successful reconstruction of 3D structure is the elimination of displacements between consecutive projections caused by the tilt, which are unavoidable in high-magnification imaging. Image alignment procedures based on cross-correlation between series of tilted images usually cannot account for the rotation around a common axis in the three-dimensional space, which results in the accumulation of alignment errors, reduced resolution of the tomogram, and failure to reconstruct fine details of the sample. The commonly used introduction of fiducial markers in close vicinity to the imaged nanoparticles is difficult experimentally and may prohibit correlation with optical spectroscopy because the presence of the markers may alter the optical signal. To overcome these complications, we used a recently developed iterative alignment algorithm39 that is especially suited for studies of correlation between the optical plasmon spectra and explicit shape of the nanostructures. This is because it offers an efficient use of the information from a series of tilt images and allows detailed reconstruction of the sample structure, while not relying on laborious calibration of the tilt geometry using fiducial markers.39−43 An important advantage of the new alignment procedure is its robustness and effectiveness, which is essential in order to produce multiple tomograms in a reasonable time frame. The effectiveness of the alignment procedure enables a successful generation of highquality tomograms for 90% of the series acquired. The correlation between the structure and the optical properties requires multiple tomograms for statistics, and the new alignment procedure enables such an analysis. The algorithm is based on repeated optimization by trial tomograms.39 A set of translational displacements is applied to each image in the series, usually in the range of 5−10 pixels in each direction. Then a specific region of interest out of the full tomogram is chosen and reconstructed to produce a trial tomogram, the contrast of which is used to determine a figure of merit. An optimal alignment of the tilt images is obtained by iteratively maximizing this figure of merit, and the final tomogram is then calculated. In contrast to common reconstruction algorithms, this iterative reconstruction results in an image alignment with subpixel precision, which optimizes the contrast of the tomogram and the 3D resolution.43 By calculating the full set of trial tomograms, the procedure prevents optimization to a local minimum while the overall procedure is still within a reasonable investment of computing time (30−60 min for each tilt series).

Figure 1. Electron tomography reconstructs the structure of core− shell nanoparticles. Three leftmost columns: TEM images taken at tilt angles of −70°, 0°, and +70°. The scale bar is 50 nm. Middle column (in color): cross sections of the reconstructed nanoparticles. Right column: reconstructed nanoparticles with their volume divided into core (red) and shell (cyan) domains as described in text. The values of R corresponding to each nanoparticle are shown on the right.

Overall, we reconstructed the structures of ∼20 nanoparticles, four of which are presented in Figure 1. Universal threshold values for the core and shell domains were derived from the intensity profiles of the nanoparticles (Supporting Information Figure S1). Using these threshold values, we were able to segment the particles into the core and shell substructures, as shown in the right column of Figure 1. This procedure allowed us to accurately calculate the volume ratios R = Vcore/Vtot, where Vcore is the volume of the core and Vtot is the total nanoparticle volume. The R values obtained for nanoparticles I−IV presented in Figure 1 are 0.63, 0.46, 0.32, and 0.14, respectively. It was found that within one synthetic batch of nanoparticles R varied by 10−20%. Significantly, values of R calculated from the zero-tilt images alone showed systematic deviations with respect to those of the tomographic reconstructions. These deviations (see Supporting Information Figure S2) grew as the core size decreased, reaching as much as ∼100%. The deviations could be attributed both to the ambiguity in determination of the core−shell border in the zero-tilt images and to information missing in a single projection of the structure. TEM imaging of each core−shell nanoparticle was preceded by a measurement of its plasmon spectrum using a dark-field microscope coupled to a spectrograph and a back-illuminated thermoelectrically cooled CCD camera. After subtraction of the background measured in the neighborhood of each nanoparticle, the spectrum was corrected using the excitation spectral profile of a 75 W Xe lamp and the optical transfer function of the detection system. A quantitative understanding of the plasmon spectra was facilitated by accurate knowledge of the relative size and geometry of the core and shell of each particle, derived from the tomographic structural reconstructions. The reconstructed shapes were used to simulate the corresponding plasmon spectra, assuming excitation with nonpolarized light (as in the experiment). The numerical 146

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simulations were performed with the program DDSCAT,44,45 which accounts for the actual physical dimensions and shape of the nanoparticles and has been shown to provide accurate solutions for spheres, ellipsoids, prisms, and other nanoparticle geometries.11,12 Here, the volume of each nanoparticle was discretized into cubic cells of ∼0.6 nm3, each having the optical constants of either gold or silver. The dielectric constants of ref 46 for silver and ref 47 for gold were used, and it was assumed that the nanoparticles are surrounded by water due to a condensation layer on the sample. A very good agreement was obtained between the experimental and simulated results, confirming the superiority of electron tomography over standard TEM imaging in reconstructing the internal structure of each core−shell nanoparticle. A sample comparison between the core−shell assignment based on standard TEM images and electron-tomography reconstructions is shown in Figure 2 (see Figure 3. Plasmon spectra and the corresponding zero-tilt TEM images of the core−shell nanoparticles of Figure 1. The scale bar is 50 nm. Left column: experimental results; middle column: TEM images; right column: numerical simulations based on the tomographic reconstructions. The shifts of the resonance positions between spectra are traced by dotted lines. Spectra and images of pure gold and silver nanoparticles are shown in rows a and f, respectively.

nanoparticles decreases with increasing shell thickness, whereas the intensity of the high-energy resonance peak increases. Clearly, the plasmon modes of core−shell nanoparticles strongly interact and cannot be viewed as additive individual contributions of core and shell modes. The plasmon resonance energies of all the core−shell nanoparticles we analyzed are shown as a function of their R values in Figure 4a and the corresponding resonance energies obtained from simulations are shown in Figure 4b. In order to determine the exact positions of the resonance peaks, we fitted each spectrum to a sum of two Lorentzian functions. The general trend observed is in agreement with earlier reports based on bulk measurements of core−shell nanoparticles:1,17,24−29 the low-energy resonance shifts to the red as R increases (the shell thickness decreases), while the highenergy resonance does not show a significant change in its spectral position. The agreement between the experimental and simulated results is very good, especially for the low-energy resonance. In the case of the high-energy resonance, while the experimental and numerical results show the same trend, the numerical results are systematically blue-shifted. Such a blue shift is also found in calculated plasmon resonance energies of pure silver particles and is due to inaccuracies in the dielectric functions used in the calculations48 (see Supporting Information Figure S4 for further analysis). We performed analysis of two factors affecting the plasmon spectra: the deviation of the shape of a core−shell nanoparticle from spherical and the concentricity of the core and shell. The effect of shape was studied by comparing spectra simulated based on the exact reconstructions of Figure 1 with spectra simulated for concentric spherical nanoparticles of the same size and R. The results are shown in Supporting Information Figure S5. Only small differences in the relative intensities of the plasmon resonances and their spectral positions were found. Indeed, the nanoparticles studied in the present work are multicrystalline and have a close-to-spherical shape. A stronger effect of the shape on the spectrum is expected for nanoparticles having, for example, polyhedral shapes with well-

Figure 2. Electron tomography facilitates quantitative prediction of plasmon spectra. (a) Standard TEM image of the core−shell nanoparticle whose plasmon spectrum is shown in panel d. (b) Core−shell assignment based on the TEM image of panel a, suggesting R = 0.66. The corresponding simulated plasmon spectrum is shown in panel e. (c) Electron-tomography reconstruction of the nanoparticle, which gives R = 0.4. The corresponding simulated plasmon spectrum is shown in panel f and agrees much better with the experimental spectrum.

Supporting Information Figure S3 for an additional example). The dark contrast that appears in the standard TEM image inside the nanoparticle (panel a) arises mainly from dynamically diffracted electrons and leads to a significant overestimation of the core dimensions, with R = 0.66 as shown in panel b. Consequently, the plasmon spectrum simulated based on this structure (panel e) qualitatively differs from the experimentally measured spectrum shown in panel d: the highenergy plasmon resonance does not appear in the spectrum at all. On the other hand, the tomography-reconstructed shape shown in panel c gives R = 0.4, and the high-energy resonance is successfully recovered in the corresponding simulated spectrum shown in panel f. Plasmon spectra of the nanoparticles from Figure 1 are presented in Figure 3, left column (panels b−e). To these we added the plasmon spectrum of a pure gold nanoparticle, with a resonance at 540 nm (Figure 3a), and that of a pure silver nanoparticle, with a resonance at 440 nm (Figure 3f). The right column shows the spectra calculated based on the tomograms. The effect of the shell on the plasmon spectrum is manifested by a blue shift of the low-energy plasmon resonance and the appearance of an additional high-energy resonance peak near 440 nm that converges to the resonance of a pure silver nanoparticle when the shell becomes thicker. The intensity of the low-energy plasmon resonance peak of the core−shell 147

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Figure 4. Plasmon resonances of core−shell nanoparticles as a function of volume ratio. The low-energy resonances are shown in red and highenergy resonances in blue. (a) Experimental results. (b) Numerical results. (c) Results based on the long-wavelength approximation of eq 1. Note the different abscissa scale in each panel.

defined facets9,12−14,20 or, alternatively, ellipsoidal and rodlike shapes with high aspect ratios.18 The effect of the core−shell concentricity on the plasmon spectrum was examined by a numerical comparison between the spectra of concentric spherical nanoparticles and those with core and shell origins displaced by Δ ≃ 0.5(a2 − a1), where a1 is the radius of the core and a2 the outer radius of the shell. The most prominent effect observed in the plasmon spectra of the nonconcentric nanoparticles (Supporting Information Figure S5) is an increase in the high-energy peak intensity relative to that of the low-energy peak. This effect resembles the increase in the intensity of the antibonding plasmon mode of off-centered nanoshells22 and suggests an antisymmetric charge distribution within the nanoparticles. The above results show that for multicrystalline core−shell nanoparticles of the current range of dimensions the plasmon spectra depend mostly on the relative sizes of the core and shell, rather than on their exact shapes and concentricity. We further tested numerically the possibility that a diffuse boundary region between the core and shell of a nanoparticle, due to atomic diffusion from one phase to the other, may have an effect on the spectrum. For this purpose we simulated a hypothetical nanoparticle with volume cells in the boundary region having alternatively gold and silver dielectric constants. Comparison between the simulated spectrum and the one obtained with a sharp boundary (Supporting Information Figure S6) shows that a diffuse boundary increases the spectral broadening, while it does not change the plasmon resonance energies. We anticipate that wisely engineered boundary region can add an additional dimension of control over the optical properties of the nanoparticles. However, in the present study the diffusion of boundary atoms, if existing, is estimated to have a negligible effect on the optical spectrum. The physical origin for the change in the plasmon spectra as a function of core−shell ratio is analyzed below based on a simplified model for the dipolar polarizabilty. For the nanoparticles studied here the long wavelength approximation holds: ka2 ≪ 1, where k is the scattering wavenumber. Within this limit, the light scattering cross section of a core−shell nanoparticle is proportional to the squared absolute value of the nanoparticle polarizability, which is given by49

izability strongly depends on the volume ratio R, the parameter precisely determined in our tomography experiments. In Figure 4c, we demonstrate the dependence of the plasmon resonance energies calculated from eq 1 on R. When the size of the core vanishes (R → 0), the expression converges to the case of a silver sphere with a plasmon resonance at 400 nm. For values of R between 0 and 1, the denominator of eq 1 has two poles: a high-energy resonance corresponding to a gold sphere embedded in silver and a low-energy resonance corresponding to a silver sphere embedded in a dielectric medium. When the size of the core approaches the size of the shell (R → 1), the expression converges to the case of a gold sphere, with the corresponding resonance at 525 nm. This behavior agrees qualitatively with the experimental results in Figure 4a. However, this simple theory cannot describe satisfactorily the actual shape of the plasmon spectrum, since it does not account for effects like retardation and radiation damping, which have been shown to affect the shape of the spectra of 50−60 nm nanoparticles.1,11,12 Therefore, the exact reconstruction of the nanoparticle structure by means of electron tomography correlated with full electrodynamic simulations is essential for a quantitative description of the experimental results. As a final point, we note an interesting consequence of the core−shell plasmon interaction, which is the dramatic response of the nanoparticle spectrum to a change in the dielectric environment. An experimental example of such a response is shown in Figure 5a,b, where the spectrum of a core−shell nanoparticle of ∼60 nm in size immobilized on a glass coverslip is measured first in air and then after covering it with a drop of immersion oil of εm = 2.3. Upon a change in the surrounding medium permittivity, the high-energy plasmon resonance of the nanoparticle shifts from 420 to ∼470 nm, while the low-energy resonance shifts from 510 to 550 nm. In addition, the ratio between the peak intensities of the low- and high-energy resonances changes dramatically from I510 nm/I420 nm ≃ 0.5 to I550 nm/I470 nm ≃ 2, which corresponds to a change of 400%. The numerically simulated spectra for a spherical concentric core− shell nanoparticle of R = 0.3 shown in Figure 5c,d capture qualitatively this change. This striking result suggests a possible use of core−shell nanoparticles as efficient ratiometric sensors with a larger dynamic range than in typical plasmonic devices. In conclusion, a correlative study of the 3D shape and plasmon spectra of individual nanoparticles was used to demonstrate the correspondence between resonances and volumetric properties of gold core−silver shell nanoparticles. Electron tomography can accurately reconstruct the structure of such particles and facilitates quantitative interpretation of their plasmonic spectra. This is yet another demonstration of the important contribution of sophisticated correlative optical and

α = (4πa2 3)[(ε2 − εm)(ε1 + 2εm) + R(ε1 − ε2) (εm + 2ε2)]/[(ε2 + 2εm)(ε1 + 2εm) + R(ε1 − ε2)(2ε2 − 2εm)] (1) where ε1, ε2, and εm are the permittivities of the core, shell, and surrounding medium, respectively. The nanoparticle’s polar148

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Figure 5. Effect of the dielectric environment on the spectrum of core−shell nanoparticles. (a) A nanoparticle of ∼60 nm immobilized on a glass coverslip in air. (b) Same nanoparticle as in (a), but covered with a drop of oil with εm = 2.3. (c, d) Numerical simulation results for a core−shell sphere with R = 0.3 and εm = 1.8 and 2.3, respectively.

electron microscopy studies of nanoplasmonic structures, which we expect to grow in coming years.

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ASSOCIATED CONTENT

S Supporting Information *

Figures S1−S6. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION Corresponding Author *E-mail: [email protected].

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ACKNOWLEDGMENTS This work was supported by the Gerhard M. J. Schmidt Minerva Center of Supramolecular Architecture of the Weizmann Institute of Science and by Grant 450/10 from the Israel Science Foundation to G.H.

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