Chromatic Aberration Short-Wave Infrared Spectroscopy: Nanoparticle

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Chromatic Aberration Short-wave Infrared Spectroscopy: Nanoparticle Spectra without a Spectrometer Jason K. Streit, Sergei M. Bachilo, and R. Bruce Weisman Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/ac303713z • Publication Date (Web): 03 Jan 2013 Downloaded from http://pubs.acs.org on January 6, 2013

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Analytical Chemistry

Chromatic Aberration Short-wave Infrared Spectroscopy: Nanoparticle Spectra without a Spectrometer Jason K. Streit, Sergei M. Bachilo, and R. Bruce Weisman* Department of Chemistry and Richard E. Smalley Institute for Nanoscale Science and Technology, Rice University, 6100 Main Street, Houston, TX 77005 USA * Corresponding author e-mail: [email protected] Submission date:

Abstract A new method is described for measuring the short-wave infrared (SWIR) emission wavelengths of numerous individual nanoparticles without using a dedicated spectrometer. Microscope objectives designed for use at visible wavelengths often show severe axial chromatic aberration in the SWIR. This makes coplanar objects emitting at different SWIR wavelengths appear to focus at different depths. After this aberration has been calibrated for a particular objective lens, the depth at which an emissive nanoparticle appears brightest and best focused can be used to deduce its peak emission wavelength. The method is demonstrated using a dilute, structurally polydisperse sample of single-walled carbon nanotubes deposited onto a microscope slide. Discrete emission centers in this sample have different peak wavelengths corresponding to specific nanotube structural species. A set of images was recorded at stepped focus settings and analyzed to find the sharpest focus depth of each nanotube. The chromatic aberration calibration curve converted these depths into peak emission wavelengths with a spectral resolution better than 3 nm, allowing identification of each nanotube's structure. Chromatic aberration spectroscopy is a practical tool for using existing microscopic equipment to extract significant spectral information on coplanar nanoparticle samples that emit or scatter light.

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Fluorescence microscopy of luminescent nanoparticles has become a powerful tool for physical, chemical, and biological researchers.1-7 It is often important to supplement microscope images of nanoparticles with their individual emission spectra, which can convey valuable structural and environmental information.8-10 One challenge for such microscopy measurements is the fact that the emission or scattering of many nanoparticles occurs at short-wave infrared (SWIR) wavelengths beyond 1000 nm. This not only prevents the use of common imagers and detectors, but also places unusual demands on conventional microscope optics that are typically designed for use only in the visible region. When used in the SWIR, visible-optimized objective lenses typically show reduced transmission and contrast because of reflections from numerous optical surfaces whose anti-reflection coatings are effective only over a limited range. In addition, lenses that are highly corrected for chromatic aberration (CA) at visible wavelengths may show severe axial chromatic aberration in the SWIR. This effect causes samples of nanoparticles located in the same plane but emitting at different SWIR wavelengths to give sharp images at different focus positions. Although strong CA can disqualify objective lenses for some SWIR applications, it has previously been exploited for chromatic confocal microscopy,11 in which three-dimensional bright-field images are constructed by deducing depth from spectral content. We describe here a novel method that conceptually reverses this idea: the spectral content of objects is instead deduced from focus depth information. We illustrate this chromatic aberration spectroscopy with measurements on samples of single-walled carbon nanotubes (SWCNTs).


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Experimental Methods Sample Preparation. Our (6,5)-enriched SWCNT sample was prepared by dispersing ~5 mg of raw HiPco SWCNTs (Rice University batch HPR 188.4) in 10 mL of 2% aqueous sodium cholate using 1 h of bath sonication followed by 30 min of tip sonication at 7 W. The nanotube suspension was then centrifuged for 1 h at 13,300 ×g. The supernatant was then diluted to an absorbance value of ~10 per cm at 984 nm and used as the starting material for structural sorting by nonlinear density gradient ultracentrifugation, following the protocol of Ghosh et al.12 Fractionation of the centrifuged tube contents provided the purified (6,5) sample. Selectively extracted samples were prepared by suspending approximately 1 mg of raw HiPco SWCNTs (Rice University batch HPR 161.12) in 8 mL of toluene containing 8 mg of poly(9,9-di-n-octylfluorenyl-2,7-diyl), or PFO.13 Dispersion was achieved with 30 min of bath sonication (Sharpertek Stamina XP) followed by 20 min of tip sonication (Misonix Microson XL) at 7 W. The suspension was then centrifuged at 13,300 ×g for 20 min to remove nanotube bundles and residual iron catalyst. Bulk Fluorescence Spectroscopy. Bulk fluorescence measurements were made with a model NS2 NanoSpectralyzer (Applied NanoFluorescence) and a Fluorolog 3-211 (Horiba J-Y) equipped with a liquid nitrogen cooled InGaAs detector. Near-IR Fluorescence Microscopy. We prepared microscope samples by drop casting 1 µL of diluted SWCNT suspension onto a glass coverslip. The solution was allowed to dry and the coverslip was fastened (nanotube side down) with Scotch tape to a PMMA microscope slide. Dilution factors were chosen to give approximately 40 nanotubes in each 160 x 128 µm image frame.


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As described previously,14 wide-field images of static SWCNTs were acquired using an inverted Nikon TE-2000U microscope equipped with a Nikon PlanApo 60x/1.4 NA oil immersion objective lens. A dichroic beamsplitter and 950 nm long-pass filter selected emission in the desired SWIR wavelength range, which was detected using a liquid nitrogen cooled InGaAs camera (Roper Scientific OMA-V 2D). We used 730 nm and 784 nm outputs from a tunable continuous wave Ti:Sapphire laser (Del Mar Photonics) and the 664 nm output of a fixed wavelength diode laser to excite the microscope samples. The excitation beams were converted to circular polarization using an achromatic λ/4 retardation plate. Their intensities at the sample position were approximately 1 kW/cm2. Nearly all of the nanotubes in our samples had lengths below the optical diffraction limit and gave images that were approximately circular in shape. We used a Nikon Remote Focus Accessory to image the SWCNT samples at selected focus depths. In each sample, the nanotube species with the shortest emitting wavelength was used as the reference point, and the sample was scanned through sequential focus settings in increments of 0.5 µm until the best focus was found for all nanotubes in the frame. At each depth, image sequences of 50 frames were recorded with a 250 ms exposure time and a 5 MHz readout rate. To test the effects of higher image quality, we performed an additional analysis using 750 ms exposures and a 1 MHz readout rate. Ten different regions of the sample were analyzed for each spectral measurement. This data acquisition required approximately 50 min and typically gave spectral data on approximately 400 nanotubes. Image Analysis. We have written custom image analysis software, using Matlab 2011a (Mathworks) and Labview 2009 (National Instruments), to locate the positions of all SWCNTs in the image field and to determine the optimum focus depth of each nanotube. The software begins by averaging the 50 image frames recorded at each specific focus depth. The set of these


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averaged frames shows the SWCNT sample at sequential focus positions. For each averaged frame, the software determines the centroid position of every distinct nanotube in the field and connects its positions in consecutive averaged frames using a nearest-neighbor algorithm. Images of individual SWCNTs that can be detected for at least five consecutive frames are then analyzed by simulation to quantify their apparent sharpness and locate the optimum focus position. Our algorithm simulates each nanotube's image as the sum of two-dimensional Gaussians of the form:

( x − xo ) + ( y − yo )  f ( x , y ) = A ⋅ exp  − 2σ 2   2

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where A is the common amplitude, xo and yo are center coordinates, and σ is the common width parameter. Each pixel is first divided into a 5 x 5 array of smaller pixels with the same intensity value, and the nanotube image is analyzed to find its major symmetry axis and estimate the positions of the end points along that axis, which define the length parameter, L. Then starting estimates for A and σ are entered and the image is simulated by summing a set of 10 L σ Gaussian intensity profiles of the form shown above, with their centers evenly spaced along the line connecting the end points. The algorithm re-pixelates the simulated image back to the density of the raw data and computes the sum over all pixels of squared differences between data and simulation (SSD). Then the set of six parameters (A, σ, and four end point coordinates) are varied using a simplex algorithm to minimize the SSD value and obtain an accurate simulation of the SWCNT image. Length and orientation information was determined from the end point coordinates for some of the observed nanotubes but was not used in the present spectral analysis. The σ values deduced from this fitting procedure reflect image sharpness. For each nanotube, σ is computed as a function of focus depth and the position of sharpest focus is found


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from the minimum in a smooth (hyperbolic) fit through the points, as shown in Figure 1. For our apparatus and analysis method, the uncertainty in sharpest focus depth is typically 50 nm. Results and Discussion The first step in implementing chromatic aberration spectroscopy is determining the calibration curve that relates focus depth to emission wavelength. For this we prepared a sample of SWCNTs extracted with the organic dye PFO and measured the focus depths of 500 individual nanotubes representing (6,5) plus the five (n,m) species ((7,5), (7,6), (8,6), (8,7), and (9,7)) that are known to predominate in PFO-extracted samples.13 The (n,m) identity of each nanotube was easily deduced by reference to the simple spectral pattern of the bulk sample. We then plotted the average focus depth for each species vs. the peak emission wavelength of that species in the bulk sample to obtain the calibration data shown in Figure 2. Here the zero of our focus depth scale was set to the position for (6,5) SWCNTs. The smooth curve in Figure 2 is a quadratic best fit, with parameters 2.296 ×10 −5 λ 2 − 0.03271 λ + 9.969 (λ expressed in nm). To demonstrate our CA spectroscopy method, we began with a structurally sorted sample of nearly pure (6,5) SWCNTs excited at 784 nm. The focus depths of a total of 475 emissive objects in 10 image fields were measured and converted to wavelength using the calibration curve of Figure 2. These results may be compiled to give two different types of spectral histograms. In one, the data are presented as a plot with wavelength bins along the x-axis and the number of observed objects (nanotubes) within each bin on the y-axis. This gives a spectral counting histogram similar in spirit to the size counting distributions found from AFM or TEM analyses of nanoparticles. In the alternative treatment, the y-axis instead shows the summed emission intensities of all objects having emission wavelengths within that spectral bin. This alternative treatment gives a spectral intensity histogram, which is more closely related to bulk


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emission spectra and is therefore better suited to validating our CA spectra. Figure 3 shows the spectral intensity histogram obtained for the (6,5) sample and a smooth curve representing the normalized bulk emission spectrum of the sample. The fine general agreement between the two spectra confirms the validity of our approach. The main discrepancy seen in Figure 3 is a difference in the apparent spectral widths, which must reflect differences in the measurement processes. In our CA-SWIR spectroscopy, increased homogeneous broadening in the emission spectrum of an individual nanotube will broaden its focus curve (Figure 1) but will not change the position of the minimum. The corresponding contribution to the spectral histogram will therefore remain unchanged and will not show the homogeneous width. By contrast, inhomogeneous broadening among nanoparticles in a sample will give a distribution of focus positions and a correspondingly broadened spectral histogram. Conventional bulk spectra contain both homogenous and inhomgeneous broadening. The greater width of the bulk spectrum in Figure 3 may reflect the homogeneous line width component in the sample. It is necessary to validate the CA-SWIR method with more spectrally complex specimens. For this purpose we used a PFO-extracted sample of SWCNTs and monitored the five predominant (n,m) species that emit between 1000 and 1400 nm.13 We selected three laser wavelengths to provide differing excitation efficiencies for the five species and performed a complete focus depth scan for each excitation wavelength. The wavelength scale of these CA spectra was calibrated by identifying the shortest wavelength emitters as (7,5) nanotubes and assigning their mean position in the CA spectra to the (7,5) emission wavelength measured in bulk spectra of the sample. We then used the chromatic aberration curve of Figure 2 to deduce the emission wavelengths of all observed nanoparticles. Figure 4 shows the resulting spectral


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intensity histograms along with the corresponding bulk emission spectra. The characteristic spectral patterns of the bulk sample are clearly revealed by the CA-SWIR histograms, and the valleys between peaks are significantly lower in CA-SWIR than in the bulk spectra, perhaps because of the homogeneous broadening effect discussed above. Finally, we have investigated the effects of image quality on CA-SWIR spectral resolution. The (6,5)-enriched sample used for Figure 3 was re-measured with a tripled exposure time and a reduced digitization rate to provide enhanced images with higher signals and lower noise. The resulting data, processed using the same method described earlier, gave the spectral intensity histogram shown in Figure 5. The emission width clearly appears narrower than in Figure 3 (10 nm FWHM vs. 14 nm FWHM), showing that the CA-SWIR method is similar to conventional scanning spectroscopy in its ability to trade scan speed for spectral resolution. Spectral resolution in the CA-SWIR approach equals the uncertainty in focus depth divided by the slope of the calibration curve at that wavelength. For the particular objective lens used in this work, the slope factor ranges from 13 at 1000 nm to approximately 29 at 1350 nm, whereas the focus depth uncertainty is typically near 50 nm under our standard image acquisition conditions. These values predict FWHM spectral resolutions ranging from 7.3 to 3.3 nm, which are comparable to the resolutions of many conventional spectrometers used in the SWIR. Still higher spectral resolutions would be possible using objective lenses with poorer correction for chromatic aberration. However, image analysis of nanoparticles with dim emission or broad spectra will give less precise focus depths, and thus coarser spectral resolution. CA-SWIR spectroscopy is restricted to samples in which all observed particles lie in a single plane perpendicular to the observation axis. Also, because it is challenging to reproducibly position the height of that plane to ~50 nm precision, one must calibrate the focus depth axis for


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each sample. We suggest that the easiest calibration method is to add a small quantity of broadly scattering nanoparticles to the specimen and capture their images when illuminated with monochromatic light within the covered spectral range. A further disadvantage is the need for significant sample photostability, as the imaged nanoparticles must be irradiated during many minutes of data acquisition. Photobleaching or blinking will compromise data sets and limit the spectral analysis. The CA-SWIR approach should be usable for a variety of samples other than SWCNTs. SWIR-emissive semiconductor quantum dots such as PbSe and PbS are good candidates (if adequately photostable), and it should also be possible to analyze the structured scattering spectra from gold nanoparticles, nanoshells, etc.15-17 Samples with broad homogeneous spectra will give blurred focus curves showing reduced curvatures and larger minimum values of σ. Modified versions of our CA-SWIR method might be developed to estimate the spectral widths of such particles. Finally, it can be useful to compare the spectral intensity histogram with the spectral counting histogram derived from the same CA-SWIR data set (for example, see the counting histograms corresponding to Figure 4 in Supporting Information). If the nanoparticle emission intensity is correlated with emission wavelength, then the two spectra will show different shapes and peak positions. Also, in SWCNT samples containing multiple (n,m) species, the ratios of intensity peak heights to corresponding counting peak heights should reveal the mean relative fluorimetric brightness of those species, given equivalent length distributions. Such fluorimetric brightness data are needed to advance SWCNT analytical spectroscopy.18-20


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Conclusion We demonstrate how axial chromatic aberration, an imaging defect of a microscope objective lens, can be used to efficiently measure the peak emission wavelengths of many individual nanoparticles without a spectrometer. This form of hyperspectral imaging allows the capture of images and spectra with a single detector. Such information allows structural identification of individual semiconducting carbon nanotubes and characterization of quantum dot samples. Although the approach can be applied in any spectral region, it is particularly useful for the SWIR range because of the large chromatic aberration often present in microscope objectives used outside of their design ranges and the high cost of separate SWIR spectrometer detectors. We find that the SWIR spectral resolution obtained with a standard objective is similar to that of many spectrometers designed for use in this region. The new method is limited to samples in which all particles lie in the same plane and have good photostability. Internal wavelength calibration is also needed for each specimen. However, because this method determines peak wavelengths rather than entire spectral profiles, it can readily display inhomogenous spectral broadening in nanoparticle ensembles. We expect that chromatic aberration spectroscopy will prove a useful and cost-effective tool for research involving optical microscopy of emissive or scattering nanoparticles. Supporting Information The spectral counting histograms corresponding to Figure 4. This material is available free of charge via the Internet at http://pubs.acs.org. Author Information Corresponding Author Email: [email protected], Phone 713-348-3709, Fax 713-348-5155


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Acknowledgments This research was supported by grants from the National Science Foundation (CHE-1112374) and the Welch Foundation (C-0807). We are grateful to S. Ghosh for providing (6,5)-sorted SWCNT samples.


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References (1) Michalet, X.; Pinaud, F. F.; Bentolila, L. A.; Tsay, J. M.; Doose, S.; Li, J. J.; Sundaresan, G.; Wu, A. M.; Gambhir, S. S.; Weiss, S. Science 2005, 307, 538-544. (2) Chen, P.; Zhou, X.; Shen, H.; Andoy, N. M.; Choudhary, E.; Han, K. S.; Liu, G.; Meng, W. Chem. Soc. Rev. 2010, 39, 4560-4570. (3) Huang, H.; Zou, M.; Xu, X.; Liu, F.; Li, N.; Wang, X. TrAC - Trends in Analytical Chemistry 2011, 30, 1109-1119. (4) Leeuw, T. K.; Reith, R. M.; Simonette, R. A.; Harden, M.; Cherukuri, P.; Tsyboulski, D. A.; Beckingham, K. M.; Weisman, R. B. Nano Lett. 2007, 7, 2650-2654. (5) Streit, J. K.; Bachilo, S. M.; Naumov, A. V.; Khripin, C.; Zheng, M.; Weisman, R. B. ACS Nano 2012, 6, 8424-8431. (6) Hoshino, A.; Hanaki, K. I.; Suzuki, K.; Yamamoto, K. Biochemical and Biophysical Research Communications 2004, 314, 46-53. (7) Alivisatos, A. P.; Gu, W.; Larabell, C. Annu. Rev. Biomed. Eng. 2005, 7, 55-76. (8) Micic, O. I.; Cheong, H. M.; Fu, H.; Zunger, A.; Sprague, J. R.; Mascarenhas, A.; Nozik, A. J. J. Phys. Chem. B 1997, 101, 4904-4912. (9) Bachilo, S. M.; Strano, M. S.; Kittrell, C.; Hauge, R. H.; Smalley, R. E.; Weisman, R. B. Science 2002, 298, 2361-2366. (10) Barone, P. W.; Yoon, H.; Ortiz-Garcia, R.; Zhang, J.; Ahn, J. H.; Kim, J. H.; Strano, M. S. ACS Nano 2009, 3, 3869-3877. (11) Tiziani, J. J.; Uhde, H.-M. Applied Optics 1994, 33, 1838-1843. (12) Ghosh, S.; Bachilo, S. M.; Weisman, R. B. Nature Nanotech. 2010, 5, 443-450. (13) Nish, A.; Hwang, J. Y.; Doig, J.; Nicholas, R. J. Nature Nanotech. 2007, 2, 640-646. (14) Tsyboulski, D. A.; Bachilo, S. M.; Weisman, R. B. Nano Lett. 2005, 5, 975-979. (15) Nehl, C. L.; Grady, N. K.; Goodrich, G. P.; Tam, F.; Halas, N. J.; Hafner, J. H. Nano Lett. 2004, 4, 2355-2359. (16) Pietryga, J. M.; Schaller, R. D.; Werder, D.; Stewart, M. H.; Klimov, V. I.; Hollingsworth, J. A. J. Am. Chem. Soc. 2004, 126, 11752-11753. (17) Huang, X.; El Sayed, I. H.; Qian, W.; El Sayed, M. A. J. Am. Chem. Soc. 2006, 128, 2115-2120. (18) Weisman, R. B. Anal. Bioanal. Chem. 2010, 396, 1015-1023.


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(19) Rocha, J.-D. R.; Bachilo, S. M.; Ghosh, S.; Arepalli, S.; Weisman, R. B. Anal. Chem. 2011, 83, 7431-7437. (20) Tsyboulski, D.; Rocha, J.-D. R.; Bachilo, S. M.; Cognet, L.; Weisman, R. B. Nano Lett. 2007, 7, 3080-3085.


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Focus depth (µm) Figure 1. Solid symbols show size parameter σ found by analyzing the images of a single nanotube captured at various focus positions. Four such images are shown in the insets above the data. The solid curve is a best fit to the experimental data, and its minimum corresponds to the sharpest imaging.


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Wavelength (nm) Figure 2. SWIR axial chromatic aberration as a function of wavelength measured with the Nikon objective lens described in the text. Points were determined by imaging SWCNTs of known structural species and correlating their sharpest focus positions with peak emission wavelengths of bulk samples. The solid curve is a quadratic best fit to the data.


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Emission wavelength (nm) Figure 3. Comparison of the normalized bulk emission spectrum of a (6,5)-enriched SWCNT sample (solid curve) with the spectral intensity histogram constructed from focus depth measurements on 475 nanotubes, as described in the text. Both spectra were obtained with 784 nm excitation. Images were acquired with a 250 ms exposure time and 5 MHz readout rate.


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Emission wavelength (nm) Figure 4. Comparison of the bulk emission spectra of a PFO-extracted SWCNT sample (solid curves) with the spectral intensity histograms constructed from focus depth measurements, as described in the text. All spectra have been normalized. Excitation wavelengths were 659 nm (top frame), 730 nm (center frame), and 784 nm (bottom frame).


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Emission wavelength (nm) Figure 5. Comparison of the normalized bulk emission spectrum of a (6,5)-enriched SWCNT sample (solid curve) with the spectral intensity histogram constructed from focus depth measurements, as described in the text. Both spectra were obtained with 784 nm excitation. Images were acquired with a 750 ms exposure time and 1 MHz readout rate.


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Chromatic Aberration Short-Wave Infrared Spectroscopy: Nanoparticle

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