Parallel Three-Dimensional Tracking of Quantum Rods Using

Keywords: Quantum rods, superresolution microscopy, single particle tracking, ... (3D), polarization-sensitive, spectroscopic photon localization micr...
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Parallel Three-Dimensional Tracking of Quantum Rods Using Polarization-Sensitive Spectroscopic Photon Localization Microscopy Biqin Dong, Brian Soetikno, Xiangfan Chen, Vadim Backman, Cheng Sun, and Hao F. Zhang ACS Photonics, Just Accepted Manuscript • DOI: 10.1021/acsphotonics.7b00294 • Publication Date (Web): 28 Jun 2017 Downloaded from http://pubs.acs.org on June 30, 2017

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Parallel Three-Dimensional Tracking of Quantum Rods Using Polarization-Sensitive Spectroscopic Photon Localization Microscopy Biqin Dong1,2, Brian T. Soetikno1, Xiangfan Chen2, Vadim Backman1, Cheng Sun2,*, and Hao F. Zhang1,†

1

Biomedical Engineering Department, Northwestern University, Evanston, IL 60208, USA

2

Mechanical Engineering Department, Northwestern University, Evanston, IL 60208, USA

Keywords: Quantum rods, superresolution microscopy, single particle tracking, polarimetric imaging, spectroscopy

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ABSTRACT: Semiconductor nanocrystals and their variants are widely used in biological research as fluorescent probes. Their unique characteristics, such as intense brightness, tunable emission properties, and resistance to photo-bleaching, make them ideal candidates for single-molecule imaging and tracking with localization precision far beyond the diffraction limit. Their fluorescence polarization states and emission spectra can be further utilized to probe changes in their mechanical properties and residing nano-environments. We developed a three-dimensional (3D), polarization-sensitive, spectroscopic photon localization microscopy (3D-Polar-SPLM) that enables parallel 3D tracking of individual quantum rods (QRs) while simultaneously capturing their fluorescence spectra and polarization states. Using 3D-Polar-SPLM, we spatially localized individual QRs with a lateral localization precision of 8 nm and an axial localization precision of 35 nm. In addition, we achieved a spectral resolution of 2 nm and a polarization angle measuring precision of 8 degrees. The spectral profile of the fluorescence emission provided a particle-specific signature for identifying individual QRs among the heterogeneous population, which significantly improved the fidelity in parallel 3D tracking of multiple QRs. We envision that this technology will provide new possibilities to reveal the real-time molecular dynamics of biological processes.

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Semiconductor nanocrystals, such as quantum dots and quantum rods, have been widely used as fluorescent contrast agents in biological imaging and sensing1-4. Their brightness, photostability, size-dependent photoluminance characteristics, and multiplexing capabilities have been exploited for a broad range of applications, including energy transfer–based sensing1, in vitro diagnostics2, and in vivo imaging3-4. In addition, changes in their polarization states and emission spectra provide valuable information of biological processes by revealing the biomechanical properties and biochemical microenvironments4-6. These properties make semiconductor nanocrystals ideal candidates for super-resolution imaging7-9 and single particle tracking10-12. In particular, fluorescence-based photon localization microscopy (PLM) can determine threedimensional (3D) probabilistic locations of single nanocrystals from their ensemble8-9. However, imaging and analysis tools have yet to simultaneously take advantage of all the unique properties of single nanocrystals beyond their location and size. Commonly used spectroscopic methods and image analysis techniques remain diffraction-limited and cannot quantitatively analyze individual particles from their ensemble average. In contrast, PLM provides sub-diffraction-limited localization of fluorescent molecules and particles by utilizing their stochastic radiation to isolate them from the ensemble13-15. More importantly, PLM does not perturb the native fluorescent emission process, which enables possibilities in achieving wide-field spectroscopic analysis of individual molecules and particles from far field16-18. This potentially provides powerful tools for elucidating structural organization and electronic characteristics of single particles by characterizing their fluorescence polarization anisotropy19-22 and emission spectra23-25. Inspired by this concept, we developed 3D, polarization-sensitive, spectroscopic PLM (3D-Polar-SPLM) for single quantum rod (QR) imaging and tracking. Whereas conventional 3 ACS Paragon Plus Environment

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PLM only analyzes the spatial location of QRs, 3D-Polar-SPLM simultaneously captures the associated polarization anisotropy and emission spectra from the stochastic fluorescence emissions of single QRs. Therefore, 3D-Polar-SPLM can access unique properties of QRs and provide nanoscopic imaging and comprehensive analysis of their electronic and structural properties at the single-particle level. Using 3D-Polar-SPLM, we observed the distinct spectral heterogeneity among QRs, which allowed us to identify individual QRs with high specificity and track them in parallel in 3D. The working principle of 3D-Polar-SPLM is illustrated in Fig. 1. The experimental setup contains an inverted optical microscope (Eclipse Ti-U with perfect-focus system, Nikon), equipped with a 445 nm laser illumination and a high magnification objective lens (100x, NA1.49, Nikon CFI apochromat TIRF), and a home-built detection optical assembly (see details in Supporting Information and Fig. S1). As shown in Fig. 1(a), the detection optical assembly was designed to simultaneously capture three properties of the fluorescence emission: (1) the 3D spatial location, (2) the polarization state, and (3) the fluorescence spectra. We used a collimating lens (f=50 mm) to couple the image to a blazed transmission grating (150 grooves/mm, 54005TF07-500R, Richardson grating). The grating separated the collected fluorescence emission at an approximate 1:1 ratio between the zeroth and the first diffraction orders. We placed a Wollaston prism (20° beam separation, WP10P, Thorlabs) into the zeroorder diffraction path, spatially separating the orthogonal polarization components (P∥ and P ). In addition, we used a cylindrical lens (f=1000 mm, width=8 mm, K&S optics) to introduce astigmatism in the zero-order diffraction. As a result, the ellipticity and orientation of the PSF varies along the z direction, which can be used to provide 3D imaging capability. After passing through a projection lens, both the zero- and first-order diffraction photons were collected by a 4 ACS Paragon Plus Environment

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high-sensitivity electron multiplying charge-coupled device (EMCCD, proEM, Princeton Instruments). Since the zero-order and the first-order images are spatially separated, they can be recorded simultaneously using the same EMCCD camera. We then used the zero-order images to achieve 3D spatial localization and polarization analysis, and used the first-order image to achieve spectral analysis. In this study, all images were acquired at the frame rate of 100 frames per second with a 10-ms exposure time for each frame. Figure 1(b) shows a representative frame that consists of both zero-order and first-order images from 3D-Polar-SPLM. This frame captured five stochastic radiation events, which are numbered 1 to 5. The zero-order images consist of two images corresponding with the two orthogonally polarized states, which are labeled as P∥ and P , respectively. To achieve more precise 3D localization, we combined the collected photons from both P∥ and P images by aligning with their common centroids extracted from the PSFs. We used a standard localization algorithm (ThunderSTORM, ImageJ plug-in)26 to determine the positions and ellipticities of individual blinking events, similar to the process commonly used in 3D PALM/STORM13-15. Here, we calibrated the 3D astigmatism using z-stacks of single emitters acquired with 25-nm stepsize over a 2-µm scan range, and then analyzed with the 3D calibration module in ThunderSTORM. Using the centroid positions in the zero-order images, we established reference points to the corresponding emission spectra in the first-order image (the numbered crosses in Fig. 1(b)). Then, we determined the spectrum of each emission by considering the dispersion of the grating and the focal length of the projection lens. Similar to PALM/STORM, we considered stochastic emissions originating from single molecules and treated them as spatially confined point sources. This allowed us to achieve a spectral resolution of ~2 nm without using an additional narrow 5 ACS Paragon Plus Environment

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entrance slit, which is required in the conventional imaging spectrometer. This method is particularly beneficial in enabling the simultaneous acquisition of stochastic emissions and the associated fluorescent spectra over a wide FOV25. The polarization angle of individual stochastic emission was determined by the ratio of photon counts collected in the P∥ and P images in Fig. 1(b). We defined the total photon counts of a single emission from the same molecule in the two orthogonal polarization states P∥ and P as N∥ and N , respectively. To obtain a correction factor C between the || and ⊥ channels, the polarization-dependent transmissions of each channels were experimentally quantified using an unpolarized white light illumination with the entrance aperture nearly closed. We then defined C as the ratio of the transmissions in the two channels. Finally, the polarization factor P is calculated as P=

N∥ − CN . N∥ + CN

Considering the influence of a high-NA collection, the in-plane polarization angle ρ can be calculated using P = 0.935 × cos2ρ when the out-of-plane (x-y plane) tilt angle is negligible27-28 (see details in Supporting information). Here, we can only determine ρ within the range of [0°, 90°) because ρ and π − ρ cannot be unambiguously distinguished based on current measurements. Future developments to remove the 90-degree ambiguity and fully access the 3D orientation of QRs can be potentially achieved by simultaneously acquiring imaging from three unique polarization axes29. To validate the multi-contrast imaging capabilities of 3D-Polar-SPLM, we imaged phantom samples consisting of commercially available CdSe/CdS core/shell QRs (CANdots®, Strem Chemicals, 590 nm peak emission) with diameter of 4

7 nm and length of 15

30 nm, as

shown in Fig. 2(a). Strongly polarized emissions can be observed with the electrical field 6 ACS Paragon Plus Environment

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polarized preferentially along the long axis of the QRs (see details in Supporting information and Fig. S2), which are attributed to the optical anisotropy caused by the intrinsic asymmetry of the wurtzite lattice structure30. We first imaged the immobilized QRs on a coverslip (#1.5, VWR), which is prepared by spin coating of their suspension (~100 ng/mL) and the concurrent drying process. When excited (445 nm laser illumination, 5 kW/cm2), stochastic fluorescence emission from QRs was observed. We acquired a movie containing 5,000 consecutive image frames to quantitatively evaluate the 3D localization precision a single QR using 3D-Polar-SPLM (Fig. 2(b)), which, consequently, gives a full-width-at-half-maximum (FWHM) of 8 nm in x-y and of 35 nm in z (Fig. 2(c)). Meanwhile, the precision of the relative polarization angle measurements was estimated to be 8 degrees. Fig. 2(d) shows a serial of fluorescence spectra simultaneously acquired from an individual QR. Their spectral centroids (SCs) were calculated by λ = ∑ λIλ⁄∑ Iλ and plotted as circles on the spectra31. The histogram of SCs shows that an individual QR produces a consistent emission spectra during stochastic switching, with the measured spectral fluctuation less than 1.5 nm, as indicated by the FWHM of the SC distribution in Fig. 2(e). This is likely due to the improved photo- and thermo-stability of QRs by efficient shielding through an outer organic shell and the oxygen-deficient environment being used in our experiments which provides additional protection to prevent oxidation. In contrast, Fig. 3(a) illustrates a series of fluorescence spectra simultaneously acquired from multiple QRs. For a fair comparison, we intentionally chose the stochastic emission event with the emitting photon counts of 2,800±100 (from the marked region in Fig. 3(b)). It clearly shows spectral heterogeneity among individual QRs which can only be seen on the single nanocrystal level, which is likely due to variations the size of the quantum rods and their local environment32. The distribution of photon counts with respect to the SCs of 10,023 stochastic 7 ACS Paragon Plus Environment

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emission events shows a predominant peak around the wavelength of 583 nm (Fig. 3(b)), which matches closely to the emission peak of the ensemble spectrum at 590 nm. In addition, Fig. 3(c) shows the distribution of photon counts detected from each stochastic emission event. The histogram of SC distribution shown in Fig. 3(d) suggests the spectral heterogeneity of QRs can be larger than 16 nm (indicated by the FWHM in Fig. 3(d)), which is well beyond the system spectral resolution, further facilitating spectral discrimination among QRs. To verify the imaging capability of 3D-Polar-SPLM using QRs, we imaged QRs deposited onto a patterned surface with well-defined 3D morphology. Specifically, using a nanoimprinting process, we fabricated a polymeric grating structure with a periodicity of 300 nm and grating height of 100 nm (see the detailed fabrication method in Supporting Information), as shown in Fig. 4(a). Conformal deposition of QRs on the surface of the polymeric grating structure was accomplished using a quick dip-coating process. The surface was then pressed onto a coverslip coated with a thin layer of UV-curable polymer (NOA63, Norland), which was subsequently cured to ensure that the QRs were fully encapsulated and immobilized. We acquired 5,000 consecutive image frames using 3D-Polar-SPLM to analyze the 3D locations of individual QRs and the corresponding SC and polarization states. Fig. 4(b) shows the 3D spatial distribution of imaged QRs and Fig. 4(c) shows its projection view in x-z plane, which clearly demonstrate that the spatial distribution of QRs is consistent with the surface morphology of the grating structure. Fig. 4(d) shows the top projection, multi-contrast image of the volume highlighted in Fig. 4(b), where each point represents a single QR and the color of the point denotes its SC. The polarization angle of each QR is illustrated by the arrow direction. Notably most of the QRs are nearly orthogonal to the direction of the grooves, which is likely caused by

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the preferential self-assembly of QRs along the air-water interface during the dip-coating process we used to prepare the sample. Because the emission spectrum from individual QRs remains highly consistent (Fig. 2), the heterogeneous spectral differences between QRs seen in Fig. 3(b) can be used as unique identifiers for QRs in the population. This enables us to precisely track the dynamic changes of multiple QRs in parallel within the optical FOV. To demonstrate parallel tracking, we monitored the Brownian motions of QRs suspended in a solvent (toluene, Sigma-Aldrich). Fig. 5(a) shows the results of tracking 12 QRs in 3D within a volume of 3×3×1 µm3. The SC of each QR at each single frame is obtained from the measured spectrum and further represented by the color of the point. For clear illustration, we only show the tracking results in a 200-ms duration with a 10-ms time interval (20 consecutive frames), while QRs are within the system’s depth of field (~1 µm). The 3D trajectories show the random movements of QRs driven by Brownian motion. Moreover, gravitation forces all the QRs to settle. Since the diffusivity D of Brownian motion can be """"""""" ! /2$, expressed as the mean squared displacement of each step in the time interval:  = , the averaged D among 12 QRs was calculated to be 3.7×10-12 m2/s. This is comparable with the result calculated from spherical particles with a diameter of 21.2 nm in toluene33, which matches with the length of the QRs (15-30 nm) been used in the experiment. The result reveals that each single QR can be explicitly identified by its distinct fluorescence spectrum. In Fig. 5(b), the position of each QR is projected onto the x-y plane to better illustrate their relative positions. We magnified the region where two entangled QRs traces are presented (region 1, marked by dashed square in Fig. 5(b)). As shown in Fig. 5(c), two QRs can be clearly identified in 3D by their distinct fluorescence spectra even when they are in close proximity to each other.

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Figs. 5(d-e) provide more details of tracking multiple signatures of QRs in the highlighted region 2 in Fig. 5(b). Fig. 5(d) shows the time trajectory of a single QR with respect to its position in 3D and the evolution of its SC. We found that its fluorescent emission had stable SC with the variation less than 1.6 nm, which is consistent with that observed in Fig. 2(d). The result further reinforces that tracking the fluorescent spectrum provides unique identification of individual QRs with high specificity. Fig. 5(e) shows the polarization angles with respect to its positions in 3D. We found that the change in the polarization angle appears discrete and mostly random. This is reasonable in Brownian motion with limited temporal resolution. In 3D-PolarSPLM, the temporal resolution is limited by the frame rate of the EMCCD. It can be potentially improved by either reducing the FOV or using a scientific CMOS camera to achieve a higher acquisition frame rate34. Since photon counts acquired in each frame should be sufficient for spectral and polarization analysis, the maximum frame rate can be achieved further relies on photochemical properties of the nanoparticle. In summary, we developed 3D-Polar-SPLM that can simultaneously measure optical spectra and the polarization states of individual QRs in 3D with a localization accuracy far beyond the diffraction-limited resolution. We observed and quantified the spectral heterogeneity of QRs in their fluorescence emission. Taking advantage of this unique identification signature, we were able to identify individual QRs with high specificity and track them in parallel in 3D. While the organic solvent is used in this study for the main purpose of the proof-of-concept, the reported unique multi-contrast imaging capability of 3D-Polar-SPLM can be readily applied to the future biology studies by using the water-soluble probes. We envision that this technique will bring the new possibilities to reveal the real-time molecular dynamics of biological processes.

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3D-Polar-SPLM can be extended to synthetic fluorescence molecules widely used in biological imaging, adding strength to single-molecule imaging and spectroscopy when applied to biological research35. Quantification of molecular interactions on the cellular and subcellular level at higher multiplexing dimensions (using PL intensity, lifetime, color, and polarization) is promising to further improve spatial and temporal resolution, sensitivity, and multiparameter detection. In addition, 3D-Polar-SPLM is compatible with existing photoactivated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM), further bringing an immediate impact to the broader physics, chemistry, material science, and biology research communities.

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Figures:

Figure 1. The imaging principle of 3D-Polar-SPLM. (a) Schematic of the detection optical assembly. (b) A representative frame showing the polarization-specific zero-order images and first-order spectral image. Images are cropped from the original FOV and the background has been removed.

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Figure 2. 3D polarization-sensitive spectroscopic analysis of a single QR. (a) Illustration of a QR and its projected orientation angle ρ. (b) Localization and orientation angle ρ of a single QR imaged by 3D-Polar-SPLM. (c) Histograms show localization precisions along the three spatial axes and the precision of the orientation angle ρ. (d) Fluorescence spectra of an individual QR captured over 100 blinking events. (e) Distribution of SCs extracted from (d).

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Figure 3. (a) Emission spectra of different QRs, whose emission photon counts are 2,800±100 as marked in (b). (b) Distribution of photon counts with respect to the SCs of 10,023 QRs, and histograms of photon counts (c) and SCs (d).

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Figure 4. Imaging QRs on a patterned surface. (a) SEM image of the nanofabricated polymeric pattern. Inset is the schematic of the sample that consists of a grating on top of a flat coverslip. (b) 3D image of QRs on the surface and (c) its rendered projection view. (d) The projected multicontrast image of the highlighted region in (b). The height map is calculated by interpolating positions of scattered QRs and is used as the background.

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Figure 5. Multi-contrast parallel QR tracking using 3D-Polar-SPLM. (a) Multi-particle tracking with a temporal resolution of 10 ms. Results were plotted from 20 consecutive frames. (b) The projection view in the x-y plane. (c) 3D positions of two moving QRs in Region 1 (as marked in (b)). (d) Emission spectra and (e) polarization angle with the respect to its position in 3D of a single moving QR in Region 2.

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ASSOCIATED CONTENT Supporting Information The Supporting Information is available free of charge. Detailed description of the optical setup, emission polarization dependence of quantum rods, measure the in-plane polarization angle with a high-numerical-aperture objective, fabrication of polymeric grating pattern (PDF)

AUTHOR INFORMATION Corresponding Author *

E-mail: [email protected]



E-mail: [email protected]

Funding We acknowledge support from National Science Foundation (DBI-1353952, CBET-1055379, and EEC-1530734); National Institutes of Health (R01EY026078, F30EY026472 and T32GM008152); A Research Catalyst Award by Northwestern McCormick School of Engineering, and a Northwestern University Innovative Initiative Incubator (I3) Award. Conflict of Interest C.S. and H.F.Z. have financial interests in Opticent Health. All other authors declare no competing financial interests.

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19. Gould, T. J.; Gunewardene, M. S.; Gudheti, M. V.; Verkhusha, V. V.; Yin, S. R.; Gosse, J. A.; Hess, S. T., Nanoscale imaging of molecular positions and anisotropies. Nat Methods 2008, 5, 1027-1030. 20. Larsson, A.; Carlsson, C.; Jonsson, M.; Albinsson, B., Characterization of the Binding of the Fluorescent Dyes Yo and Yoyo to DNA by Polarized-Light Spectroscopy. J Am Chem Soc 1994, 116, 8459-8465. 21. Cruz, C. A. V.; Shaban, H. A.; Kress, A.; Bertaux, N.; Monneret, S.; Mavrakis, M.; Savatier, J.; Brasselet, S., Quantitative nanoscale imaging of orientational order in biological filaments by polarized superresolution microscopy. P Natl Acad Sci USA 2016, 113, E820-E828. 22. Backer, A. S.; Lee, M. Y.; Moerner, W. E., Enhanced DNA imaging using superresolution microscopy and simultaneous single-molecule orientation measurements. Optica 2016, 3, 659-666. 23. Zhang, Z.; Kenny, S. J.; Hauser, M.; Li, W.; Xu, K., Ultrahigh-throughput singlemolecule spectroscopy and spectrally resolved super-resolution microscopy. Nat Meth 2015, 12, 935-938. 24. Mlodzianoski, M. J.; Curthoys, N. M.; Gunewardene, M. S.; Carter, S.; Hess, S. T., Super-Resolution Imaging of Molecular Emission Spectra and Single Molecule Spectral Fluctuations. Plos One 2016, 11. 25. Dong, B.; Almassalha, L.; Urban, B. E.; Nguyen, T. Q.; Khuon, S.; Chew, T. L.; Backman, V.; Sun, C.; Zhang, H. F., Super-resolution spectroscopic microscopy via photon localization. Nat Commun 2016, 7, 12290. 26. Ovesny, M.; Krizek, P.; Borkovec, J.; Svindrych, Z. K.; Hagen, G. M., ThunderSTORM: a comprehensive ImageJ plug-in for PALM and STORM data analysis and super-resolution imaging. Bioinformatics 2014, 30, 2389-2390. 27. Wei, C. Y. J.; Kim, Y. H.; Darst, R. K.; Rossky, P. J.; Vanden Bout, D. A., Origins of nonexponential decay in single molecule measurements of rotational dynamics. Phys Rev Lett 2005, 95. 28. Axelrod, D., Carbocyanine Dye Orientation in Red-Cell Membrane Studied by Microscopic Fluorescence Polarization. Biophys J 1979, 26, 557-573. 29. Hohlbein, J.; Hubner, C. G., Simple scheme for rapid three-dimensional orientation determination of the emission dipole of single molecules. Appl Phys Lett 2005, 86. 30. Chen, X.; Nazzal, A.; Goorskey, D.; Xiao, M.; Peng, Z. A.; Peng, X. G., Polarization spectroscopy of single CdSe quantum rods. Phys Rev B 2001, 64, 245304. 31. Lu, H. P.; Xie, X. S., Single-molecule spectral fluctuations at room temperature. Nature 1997, 385, 143-146. 32. Empedocles, S. A.; Neuhauser, R.; Shimizu, K.; Bawendi, M. G., Photoluminescence from single semiconductor nanostructures. Adv Mater 1999, 11, 1243-1256. 33. Einstein, A., Theory of Brownian Movement. Dover, New York, 1905. 34. Juette, M. F.; Terry, D. S.; Wasserman, M. R.; Altman, R. B.; Zhou, Z.; Zhao, H.; Blanchard, S. C., Single-molecule imaging of non-equilibrium molecular ensembles on the millisecond timescale. Nat Methods 2016, 13, 341-344. 35. Kusumi, A.; Tsunoyama, T. A.; Hirosawa, K. M.; Kasai, R. S.; Fujiwara, T. K., Tracking single molecules at work in living cells. Nat Chem Biol 2014, 10, 524-532.

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Title: Parallel Three-Dimensional Tracking of Quantum Rods Using Polarization-Sensitive Spectroscopic Photon Localization Microscopy Authors: Biqin Dong, Brian T. Soetikno, Xiangfan Chen, Vadim Backman, Cheng Sun, and Hao F. Zhang A three-dimensional (3D), polarization-sensitive, spectroscopic photon localization microscopy (3D-Polar-SPLM) enables parallel 3D tracking of individual quantum rods (QRs) with localization precisions of 8 nm and 35 nm in lateral and axial directions while simultaneously capturing their fluorescence spectra with a spectral resolution of 2 nm and polarization states with a polarization angle measuring precision of 8 degrees. The spectral profile of the fluorescence emission provided a particle-specific signature for identifying individual QRs among the heterogeneous population, which significantly improved the fidelity in parallel 3D tracking of multiple QRs.

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