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Optics Express

Optics Express

  • Editor: C. Martijn de Sterke
  • Vol. 19, Iss. 20 — Sep. 26, 2011
  • pp: 18885–18892
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Stimulated Raman scattering using a single femtosecond oscillator with flexibility for imaging and spectral applications

Hope T. Beier, Gary D. Noojin, and Benjamin A. Rockwell  »View Author Affiliations


Optics Express, Vol. 19, Issue 20, pp. 18885-18892 (2011)
http://dx.doi.org/10.1364/OE.19.018885


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Abstract

Stimulated Raman scattering (SRS) is a powerful tool for obtaining background-free chemical information about a material without extrinsic labeling. Background-free spectra are particularly important in the fingerprint region (~800 and 1800 cm−1) where peaks are narrow, closely-spaced, and may be in abundance for a particular chemical. We demonstrate a method for obtaining SRS spectra using a single femtosecond laser oscillator. A photonic crystal fiber is used to create a supercontinuum to provide a range of Stokes shifts from ~300 to 3400 cm−1. This SRS approach provides for collection capabilities that are easily modified between obtaining broadband spectra and single-frequency images.

© 2011 OSA

1. Introduction

Raman scattering is a useful technique to gain chemical-specific information about a sample without requiring extrinsic labels or destruction of the sample. By probing known vibrational modes or examining the vibrational content of a sample, high-resolution images with characterization of the molecular content of each pixel may be obtained. Of particular interest is the Raman fingerprint region, between ~800 and 1800 cm−1, in which Raman modes are more closely spaced and have more narrow linewidths. Because of the large number of resonances, chemical identification may be difficult from a single resonance; however, a range of frequencies may provide a wealth of information about the sample. This information has found applications for purposes such as characterizing biochemical information in individual cells [1

1. J. Chan, S. Fore, S. Wachsmann-Hogiu, and T. Huser, “Raman spectroscopy and microscopy of individual cells and cellular components,” Laser Photon. Rev. 2(5), 325–349 (2008). [CrossRef]

], differentiating tissue types [2

2. T. C. Bakker Schut, R. Wolthuis, P. J. Caspers, and G. J. Puppels, “Real-time tissue characterization on the basis of in vivo Raman spectra,” J. Raman Spectrosc. 33(7), 580–585 (2002). [CrossRef]

], analyzing polymer blends [3

3. M. D. Schaeberle, C. G. Karakatsanis, C. J. Lau, and P. J. Treado, “Raman chemical imaging—noninvasive visualization of polymer blend architecture,” Anal. Chem. 67(23), 4316–4321 (1995). [CrossRef]

], and component mapping within pharmaceuticals [4

4. B. D. Patel and P. J. Mehta, “An overview: application of Raman spectroscopy in pharmaceutical field,” Curr. Pharm. Anal. 6(2), 131–141 (2010). [CrossRef]

]. The broadband vibrational spectra for these applications are typically obtained through spontaneous Raman processes. However, this approach is limited by laser powers that approach the sample damage threshold and long acquisition times that can range from 250 ms to several minutes per pixel [1

1. J. Chan, S. Fore, S. Wachsmann-Hogiu, and T. Huser, “Raman spectroscopy and microscopy of individual cells and cellular components,” Laser Photon. Rev. 2(5), 325–349 (2008). [CrossRef]

,4

4. B. D. Patel and P. J. Mehta, “An overview: application of Raman spectroscopy in pharmaceutical field,” Curr. Pharm. Anal. 6(2), 131–141 (2010). [CrossRef]

].

Coherent Raman scattering (CRS) techniques have attracted interest as a means of overcoming the long acquisition times of spontaneous Raman. CRS techniques probe the chemical signature of a molecule by simultaneous excitation with multiple laser beams. At a Raman resonance, the pump (ωp) and Stokes (ωs) beams have a difference, ωp- ωs, which matches a vibrational frequency to result in an enhancement of the signal. The most common of these techniques, coherent anti-Stokes Raman scattering (CARS), uses spectral filtering to detect the generated anti-Stokes signal at ωas = 2ωp – ωs [5

5. A. Zumbusch, G. R. Holtom, and X. S. Xie, “Three-dimensional vibrational imaging by coherent anti-Stokes Raman scattering,” Phys. Rev. Lett. 82(20), 4142–4145 (1999). [CrossRef]

]. However, the CARS spectrum does not correspond to the spontaneous Raman spectrum due to large non-resonant background contributions that are present even when no vibrational resonance exists. Various detection methods have been used to suppress the non-resonant CARS signals [6

6. J. Cheng, A. Volkmer, L. D. Book, and X. S. Xie, “An epi-detected coherent anti-Stokes Raman scattering (E-CARS) microscopy with high spectral resolution and high sensitivity,” J. Phys. Chem. B 105(7), 1277–1280 (2001). [CrossRef]

8

8. F. Ganikhanov, C. L. Evans, B. G. Saar, and X. S. Xie, “High-sensitivity vibrational imaging with frequency modulation coherent anti-Stokes Raman scattering (FM CARS) microscopy,” Opt. Lett. 31(12), 1872–1874 (2006). [CrossRef] [PubMed]

], and computational techniques have been used to extract the resonant signal from the non-resonant background [9

9. E. M. Vartiainen, “Phase retrieval approach for coherent anti-Stokes Raman scattering spectrum analysis,” J. Opt. Soc. Am. B 9(8), 1209–1215 (1992). [CrossRef]

12

12. Y. X. Liu, Y. J. Lee, and M. T. Cicerone, “Broadband CARS spectral phase retrieval using a time-domain Kramers-Kronig transform,” Opt. Lett. 34(9), 1363–1365 (2009). [CrossRef] [PubMed]

]. These approaches sacrifice either the intensity of the resonant signal, or require an assumption about the non-resonant background. Stimulated Raman scattering (SRS) has recently emerged as the technique of choice for obtaining background-free coherent Raman scattering signals [13

13. C. W. Freudiger, W. Min, B. G. Saar, S. Lu, G. R. Holtom, C. He, J. C. Tsai, J. X. Kang, and X. S. Xie, “Label-free biomedical imaging with high sensitivity by stimulated Raman scattering microscopy,” Science 322(5909), 1857–1861 (2008). [CrossRef] [PubMed]

,14

14. P. Nandakumar, A. Kovalev, and A. Volkmer, “Vibrational imaging based on stimulated Raman scattering microscopy,” N. J. Phys. 11(3), 033026 (2009). [CrossRef]

]. In SRS, energy is transferred from the higher-frequency pump beam to the lower-frequency Stokes beam. This transfer of energy can only occur at a resonance, leaving the SRS spectra free from non-resonant background contributions.

Most CRS techniques use a pair of picosecond laser pulses to ensure that the narrow linewidth of the source matches or falls within typical Raman linewidths (~10-15 cm−1). However, femtosecond sources are more common in most microscopy laboratories. For CRS, the broad bandwidth of the femtosecond pulses is advantageous in that multiple vibrational frequencies may be probed simultaneously; however, the spectral resolution is correspondingly hindered. To enhance the spectral resolution in femtosecond-pulse techniques, a second-order spectral phase variation may be induced to reduce the instantaneous spectral bandwidth of the pulse [15

15. T. Hellerer, A. M. K. Enejder, and A. Zumbusch, “Spectral focusing: high spectral resolution spectroscopy with broad-bandwidth laser pulses,” Appl. Phys. Lett. 85(1), 25–27 (2004). [CrossRef]

]. The dispersion in the two paths is balanced so that the instantaneous frequency difference between the two pulses remains constant. The most simple of these approaches uses several centimeters of high-dispersion glass in each pathway. This approach has been successful in obtaining CARS images using a femtosecond oscillator and femtosecond OPO [16

16. I. Rocha-Mendoza, W. Langbein, and P. Borri, “Coherent anti-Stokes Raman microspectroscopy using spectral focusing with glass dispersion,” Appl. Phys. Lett. 93(20), 201103 (2008). [CrossRef]

], or using a supercontinuum produced through non-linear effects in a material such a photonic crystal fiber [17

17. A. F. Pegoraro, A. Ridsdale, D. J. Moffatt, Y. W. Jia, J. P. Pezacki, and A. Stolow, “Optimally chirped multimodal CARS microscopy based on a single Ti:sapphire oscillator,” Opt. Express 17(4), 2984–2996 (2009). [CrossRef] [PubMed]

].

Our goal is to acquire broadband SRS signals with the flexibility of single-frequency scanning that is suitable for biological and other soft-material imaging applications. While single-frequency approaches are useful for imaging applications that probe for chemicals such as lipids, proteins, and water in bulk, our system will be capable of quickly acquiring multiple frequencies as necessary to distinguish chemicals with similar structure, and thus subtle differences, in their Raman spectra. Toward this goal, we demonstrate a method of obtaining SRS spectra and images using a femtosecond oscillator in combination with supercontinuum generation through a photonic crystal fiber. This approach has been successfully applied for CARS; however, we are unaware of any report of SRS using a femtosecond oscillator [17

17. A. F. Pegoraro, A. Ridsdale, D. J. Moffatt, Y. W. Jia, J. P. Pezacki, and A. Stolow, “Optimally chirped multimodal CARS microscopy based on a single Ti:sapphire oscillator,” Opt. Express 17(4), 2984–2996 (2009). [CrossRef] [PubMed]

19

19. B. von Vacano, W. Wohlleben, and M. Motzkus, “Actively shaped supercontinuum from a photonic crystal fiber for nonlinear coherent microspectroscopy,” Opt. Lett. 31(3), 413–415 (2006). [CrossRef] [PubMed]

]. Unlike typical dual-laser or OPO-based approaches, the Raman frequency of interest may be altered rapidly by modifying the delay between the pump and Stokes beams. The frequency region can be scanned to provide a full spectrum in just a few seconds, or the delay can be adjusted to a specific resonance for rapid imaging applications. These alterations will require no modifications to the laser source or other optics.

2. Experimental setup

As illustrated in Fig. 1
Fig. 1 Diagram of our coherent Raman setup. FI is a Faraday isolator, HWP are achromatic half waveplates, Pol. are Glan-laser polarizers, BS is a plate beam splitter, PCF is the photonic crystal fiber, EOM is the electro-optical modulator.
, pulses from a femtosecond oscillator (750 nm, ~100 fs, 80 MHz, ~1.5 W), are split into a pump beam and a Stokes beam. About 250 mW average power in the Stokes beam are used to pump a photonic crystal fiber (NKT Photonics, Femtowhite) with zero dispersion wavelengths of 750 and 1260 nm to generate a supercontiuum with ~40% coupling efficiency. After filtering by three long-pass filters, the supercontinuum spans from 765 nm to 1200 nm, as determined by the second-harmonic signals generated in a beta barium borate (BBO) crystal. The filtered beam is then amplitude modulated at RF (1-5 MHz) with an electro-optical modulator. The rotation and therefore extinction of the modulation is wavelength dependent, thus, the bias and driving voltage are adjusted to provide the greatest contrast ratio of the wavelengths measured by a silicon detector (~765-1000 nm). This region corresponds to the range of wavelengths used for the Raman shifts in our experiments. The p-polarized pump beam is passed through two ZnSe windows (15.5 mm total pathlength), positioned at Brewster’s angle in opposite directions, to match the dispersion in the other pathway. The two beams are recombined using an 800-nm band pass filter positioned at 45 degrees and directed into a customized microscope, fitted with galvanometer scanning mirrors.

CRS signals are collected in transmission by a second objective lens (60X, oil 1.2 NA). Spectra are acquired by scanning the time delay of the pump beam in relation to the Stokes beam with a motorized stage. Raman-frequency differences are determined by the instantaneous frequency difference between the two beams. Zero pump delay is determined as the point at which the center frequencies of the pump and supercontinuum would be equal. CARS spectra are collected by a 20-MHz avalanche photodiode after two 750-nm and one 720-nm short-pass filters. SRS signals are filtered by a 750-nm band-pass filter and two 760-nm short-pass filters and are collected by a back-biased (12V) silicon photodiode. Signals are sent through an RF lock-in amplifier and recorded by a custom LabVIEWTM program, which also controls the positions of the motorized stage and galvanometer mirrors. Typical measured powers at the sample were ~12 mW of pump and ~1.5 mW of supercontinuum. Spectra were acquired as quickly as 0.8 sec at a resolution of ~1 cm−1/point. Faster acquisition times are theoretically possible but were currently limited by the time constant of the lock-in amplifier. Images were acquired at a size of 250 x 250 pixels with an acquisition time of 3 ms/pixel. A background threshold subtraction and normalization was applied to the images as a set.

3. Dispersion matching

Using the Sellmeier equations and coefficients [20

20. Refractive Index Database, http://refractiveindex.info.

] to obtain d2n/dλ2, the group velocity dispersion (GVD) was calculated [21

21. J.-C. Diels and W. Rudolph, Ultrashort Laser Pulse Phenomena (Elsevier Inc, 2006).

] for each element in the two optical pathways as k0"=λ32πcd2ndλ2. The total dispersion was determined and the necessary thickness of ZnSe windows in the pump beam path to match the dispersion between the two pathways was computed. A linearly chirped pulse, with a carrier frequency ω0 at time t, has an instantaneous frequency ω(t), that is dependent on the chirp parameter b by ω(t) = ω0 + 2bt. The pulse is stretched temporally by a stretching factor F to τ = Fτ0, where τ0, is the transform-limited (TL) pulse duration [15

15. T. Hellerer, A. M. K. Enejder, and A. Zumbusch, “Spectral focusing: high spectral resolution spectroscopy with broad-bandwidth laser pulses,” Appl. Phys. Lett. 85(1), 25–27 (2004). [CrossRef]

]. The instantaneous spectral bandwidth is then narrower than the TL spectral bandwidth by a factor of 1/F. In our setup, our initial 100-fs pulses were found to be stretched to ~600 fs at the sample. Thus, with a total bandwidth of 105 cm−1, our chirped pump pulse has approximate instantaneous bandwidth of 18 cm−1.

The high refractive index and second-order dispersion of the ZnSe allowed for much thinner pathlengths through the material than would be required with glass. This thinness allowed the windows to be aligned at Brewster’s angle to minimize Fresnel reflections off the high-index material to obtain high efficiency transmission (up to 94% total) without anti-reflective coatings. The efficiency of the dispersion material is especially a concern when additional chirp is necessary in the supercontinuum beam as available power may be limited and thus efficient transmission may be required. This approach proved to be a simple and effective method for adjusting the thickness of the material due to the commercial availability of ZnSe windows of various thicknesses and ease of alignment; however, its use is limited to wavelengths longer than 630 nm, due to absorption of shorter wavelengths.

4. CARS and SRS spectra

Fingerprint-region spectra, with trans-stilbene as a model chemical, are demonstrated in Fig. 2
Fig. 2 CARS (a, blue), ME phase (b, red), retrieved Raman (c, green), and SRS (d, black) fingerprint region spectra of trans-stilbene. The CARS signal suffers from a non-resonant background that distorts the spectrum, making peak identification difficult. Maximum entropy phase extraction and removal of the estimated background phase produce a retrieved signal similar to the spontaneous Raman spectrum (inset). The SRS spectrum is an even closer match to the spontaneous Raman spectrum. Peak labels on the SRS spectrum are known vibrational modes.
. Spectra are acquired by scanning the temporal delay between the pump beam and the Stokes (supercontinuum) beam to alter the instantaneous frequency difference between the two beams, and therefore the Raman resonance being probed. On the bottom, the SRS spectrum, which does not suffer from non-resonant background contributions, contains narrow features and is a close match to the spontaneous Raman spectrum (inset) of the molecule. Resonances labeled on the spectrum are the known spontaneous Raman frequencies [22

22. National Institute of Advanced Industrial Science and Technology, SDBSWeb, http://riodb01.ibase.aist.go.jp/sdbs/.

]. Resonances as close as 45 cm−1 (1641 and 1596 cm−1) are cleanly resolved in the SRS measurements. The SRS linewidths are broader than in the spontaneous Raman spectrum; however, the spectral resolution may be improved by increasing the temporal chirp of the two pulses, at a cost of signal intensity. In contrast, the raw CARS spectrum, on the top, is broadened due to non-resonant contributions, which makes the peaks more difficult to resolve. The resonances also are red-shifted as indicated by the dashed lines.

To obtain spectra free from non-resonant contributions, numerical approaches to retrieve the equivalent spontaneous Raman line-shapes from CARS spectra have been developed [9

9. E. M. Vartiainen, “Phase retrieval approach for coherent anti-Stokes Raman scattering spectrum analysis,” J. Opt. Soc. Am. B 9(8), 1209–1215 (1992). [CrossRef]

12

12. Y. X. Liu, Y. J. Lee, and M. T. Cicerone, “Broadband CARS spectral phase retrieval using a time-domain Kramers-Kronig transform,” Opt. Lett. 34(9), 1363–1365 (2009). [CrossRef] [PubMed]

]. Thus, to provide a fair comparison between the CARS and SRS spectra obtained with our system, the CARS spectrum is further analyzed using the maximum entropy (ME) method to extract the resonant portion of the Raman spectrum [9

9. E. M. Vartiainen, “Phase retrieval approach for coherent anti-Stokes Raman scattering spectrum analysis,” J. Opt. Soc. Am. B 9(8), 1209–1215 (1992). [CrossRef]

,10

10. E. M. Vartiainen, H. A. Rinia, M. Müller, and M. Bonn, “Direct extraction of Raman line-shapes from congested CARS spectra,” Opt. Express 14(8), 3622–3630 (2006). [CrossRef] [PubMed]

,23

23. M. Bonn and E. Vartiainen, “Maximum entropy method for phase retrieval of CARS data,” http://memcars.amolf.nl/.

]. The CARS signal is proportional to the squared modulus, |χ(ω)|2, of the complex third-order susceptibility as, |χ(ω)|2=|χR(ω)|2+|χNR(ω)|2+2χNR(ω)Re[χR(ω)], where χR(ω) is the resonant portion, and χNR(ω) is the non-resonant portion. The spectral information in the CARS signal is contained in the imaginary part, or phase function, of χR(ω). The ME approach extracts this phase function, and thus the equivalent spontaneous Raman spectrum, using a system of coupled linear equations. In this method, an error phase may be introduced to account for any spectral variations in the non-resonant background. This error phase may be estimated by a polynomial fit through the off-resonant points in the spectra [10

10. E. M. Vartiainen, H. A. Rinia, M. Müller, and M. Bonn, “Direct extraction of Raman line-shapes from congested CARS spectra,” Opt. Express 14(8), 3622–3630 (2006). [CrossRef] [PubMed]

]. By subtracting the background phase from the ME phase, the extracted Raman line-shapes may be obtained. The estimation of the error phase assumes that the non-resonant background contribution is, to some extent, spectrally smooth. However, in our case, due to the possibility of sharp, frequency-dependent variations in the supercontinuum, this assumption does not necessarily apply.

The ME phase obtained from the raw CARS data [23

23. M. Bonn and E. Vartiainen, “Maximum entropy method for phase retrieval of CARS data,” http://memcars.amolf.nl/.

] is shown as spectrum 2b. As a best-case estimation of the background phase, the known Raman resonances, which correspond to the areas of the spectrum with the greatest slope, are removed from the phase spectrum. The remaining off-resonant points are then segmented and fit to a series of cubic polynomials to obtain the error phase. The resulting retrieved Raman signal (spectrum 2c) is a decent match to the spontaneous Raman spectrum. However, the SRS spectrum, which required no signal extraction or estimation of the background, is a superior match to the spontaneous Raman spectrum. This feature makes SRS particularly advantageous for supercontinuum methods, as the supercontinuum may contain many sharp spectral features that vary with alterations in coupled power.

We then considered the potential that the high third-order dispersion from the ZnSe windows could limit the spectral resolution across the measured spectral range or make the identification of the specific Raman resonances difficult due to a non-linear correlation between the pump delay and probed vibrational frequency. However, in the fingerprint region, as demonstrated in Fig. 3a
Fig. 3 (a) Correlation between pump delay and vibrational frequency of known resonances demonstrating a linear dependence. (b) Lorenzian fit of several vibrational resonances to determine the spectral bandwidth.
, an excellent linear correlation is found between the time delay and vibrational frequency using the known spontaneous Raman frequencies of trans-stilbene. The feature allows for precise conversion from time delay to wavenumber, as demonstrated in Fig. 2. The frequency distribution as a function of delay time was found to deviate from the linear fit by a maximum of only 2.4 cm−1, less than typical Raman linewidths.

To determine the spectral resolution of our system, we fit Lorenzian distributions to several resonances, as demonstrated in Fig. 3b. The typical spectral resolution of our SRS signals were found to be 24 cm−1. This resolution is broader than our theoretical estimate but still significantly more narrow than our initial 105 cm−1 pulse. The broadening of the observed resolution may be due to inexact dispersion matching in our two beams or an inexact calculation of the final pulse width. In comparison, the typical pulse width of the phase-retrieved CARS spectrum, using the equivalent trans-stilbene peaks, was found to be 50 cm−1.

5. CARS and SRS images

In Fig. 4
Fig. 4 SRS and CARS images of polystyrene microspheres. a) and e) are at the maximum of the 1003 cm−1 resonance. b) and f) are red-shifted from the resonance peak by ~100 cm−1. c) and g) are blue-shifted to the minimum between resonances at 1003 and 1034 cm−1. d) and h) were recorded when the two beams were not temporally overlapped. Scale bar is 5 µm.
, images are shown of 7.4 µm polystyrene microspheres embedded in 2% agarose that were acquired using both SRS and CARS. In the top images (a, e) the delay between the pump and the probe was adjusted to provide the maximum signal of the polystyrene phenyl-ring breathing mode at 1003 cm−1. Four individual polystyrene microspheres are visible in both images, despite the potential non-resonant background contributions from the agarose.

In the center images (b, c, f, g), the pump delay has been adjusted to either side of the maximum of the Raman resonance to demonstrate the ability of the two techniques to resolve images from single resonances. In images b) and f) the delay is red-shifted from the maximum resonance intensity by 100 cm−1. In the SRS image, b), the microspheres appear as shadows; however, this appearance is a distinct improvement in spectral contrast over the CARS images. As demonstrated in the CARS image 3f, where the frequency was red-shifted from the maximum by the same value as in the SRS image, the microspheres are still highly visible.

In the images c) and g) the delay has been blue-shifted to the minimum between the 1003-cm−1 and 1034-cm−1 resonances. The microspheres disappear completely in the SRS images but are again highly visible in the CARS images. When the delay is shifted, so that the two beams are no longer temporally overlapped (d, h), the microspheres are not visible in either, indicating that signals are resulting from a mixing process.

These figures demonstrate the advantages of SRS and limitations of CARS microscopy in the fingerprint region for imaging materials with closely spaced resonances with chemical discrimination. While a phase-retrieval method may be used with CARS to obtain images similar to our SRS images, such an approach requires acquiring the spectrum around the frequency of interest for each pixel. For CARS applications probing only a single resonance, an intensity distribution acquired for a single frequency is not sufficient to resolve the features occurring only at the desired resonance. However, for SRS, the features in the images disappear as the probed frequency is shifted off the resonance frequency.

6. Discussion and conclusions

We view our approach as a hybrid between single-frequency and broadband approaches. Our approach provides comparable, if not superior, broadband spectral features as phase-retrieved CARS approaches. Neither post-processing of the spectra nor estimation of a background signal is required. The motorized stage can be set to rapidly record an image at a particular Raman frequency or adjusted to record the spectra, pixel by pixel, over range of interest without further modification to laser source or optics. Spectral resolution and acquisition speed can be easily modified by changing the speed of the motorized stage and/or sample recording rate. Additionally, ZnSe or other high dispersion material may simply be added to the two paths to improve the spectral resolution, or removed if the Raman linewidths are broader.

Our SRS system also has the advantage of a broad tuning range. Unlike methods using an ultrashort femtosecond pulse as the broadband source, where the bandwidth is limited to the bandwidth of the pulse, we can probe vibrational frequencies from 300 cm−1 (or lower) to at least 3400 cm−1 by adjusting the delay between the two beams. The broad tuning range of our system allows for imaging of bulk features such as CH2 and CH bonds at higher frequencies (2845 and ~2950 cm−1) while quickly tuning the resonance to look for more specific molecular bonds in the fingerprint region. Entire spectra are also acquired in a few seconds by continuously scanning the temporal delay between the two beams. This feature is advantageous over dual-laser or OPO-based systems that require retuning for each frequency, a process that can take seconds per frequency-step recorded. Thus, we believe our method to be an eloquent means of acquiring background-free coherent Raman spectra using a single femtosecond oscillator with flexibility for both imaging and spectral applications.

Acknowledgments

References and links

1.

J. Chan, S. Fore, S. Wachsmann-Hogiu, and T. Huser, “Raman spectroscopy and microscopy of individual cells and cellular components,” Laser Photon. Rev. 2(5), 325–349 (2008). [CrossRef]

2.

T. C. Bakker Schut, R. Wolthuis, P. J. Caspers, and G. J. Puppels, “Real-time tissue characterization on the basis of in vivo Raman spectra,” J. Raman Spectrosc. 33(7), 580–585 (2002). [CrossRef]

3.

M. D. Schaeberle, C. G. Karakatsanis, C. J. Lau, and P. J. Treado, “Raman chemical imaging—noninvasive visualization of polymer blend architecture,” Anal. Chem. 67(23), 4316–4321 (1995). [CrossRef]

4.

B. D. Patel and P. J. Mehta, “An overview: application of Raman spectroscopy in pharmaceutical field,” Curr. Pharm. Anal. 6(2), 131–141 (2010). [CrossRef]

5.

A. Zumbusch, G. R. Holtom, and X. S. Xie, “Three-dimensional vibrational imaging by coherent anti-Stokes Raman scattering,” Phys. Rev. Lett. 82(20), 4142–4145 (1999). [CrossRef]

6.

J. Cheng, A. Volkmer, L. D. Book, and X. S. Xie, “An epi-detected coherent anti-Stokes Raman scattering (E-CARS) microscopy with high spectral resolution and high sensitivity,” J. Phys. Chem. B 105(7), 1277–1280 (2001). [CrossRef]

7.

J. X. Cheng, L. D. Book, and X. S. Xie, “Polarization coherent anti-Stokes Raman scattering microscopy,” Opt. Lett. 26(17), 1341–1343 (2001). [CrossRef] [PubMed]

8.

F. Ganikhanov, C. L. Evans, B. G. Saar, and X. S. Xie, “High-sensitivity vibrational imaging with frequency modulation coherent anti-Stokes Raman scattering (FM CARS) microscopy,” Opt. Lett. 31(12), 1872–1874 (2006). [CrossRef] [PubMed]

9.

E. M. Vartiainen, “Phase retrieval approach for coherent anti-Stokes Raman scattering spectrum analysis,” J. Opt. Soc. Am. B 9(8), 1209–1215 (1992). [CrossRef]

10.

E. M. Vartiainen, H. A. Rinia, M. Müller, and M. Bonn, “Direct extraction of Raman line-shapes from congested CARS spectra,” Opt. Express 14(8), 3622–3630 (2006). [CrossRef] [PubMed]

11.

Y. X. Liu, Y. J. Lee, and M. T. Cicerone, “Fast extraction of resonant vibrational response from CARS spectra with arbitrary nonresonant background,” J. Raman Spectrosc. 40(7), 726–731 (2009). [CrossRef]

12.

Y. X. Liu, Y. J. Lee, and M. T. Cicerone, “Broadband CARS spectral phase retrieval using a time-domain Kramers-Kronig transform,” Opt. Lett. 34(9), 1363–1365 (2009). [CrossRef] [PubMed]

13.

C. W. Freudiger, W. Min, B. G. Saar, S. Lu, G. R. Holtom, C. He, J. C. Tsai, J. X. Kang, and X. S. Xie, “Label-free biomedical imaging with high sensitivity by stimulated Raman scattering microscopy,” Science 322(5909), 1857–1861 (2008). [CrossRef] [PubMed]

14.

P. Nandakumar, A. Kovalev, and A. Volkmer, “Vibrational imaging based on stimulated Raman scattering microscopy,” N. J. Phys. 11(3), 033026 (2009). [CrossRef]

15.

T. Hellerer, A. M. K. Enejder, and A. Zumbusch, “Spectral focusing: high spectral resolution spectroscopy with broad-bandwidth laser pulses,” Appl. Phys. Lett. 85(1), 25–27 (2004). [CrossRef]

16.

I. Rocha-Mendoza, W. Langbein, and P. Borri, “Coherent anti-Stokes Raman microspectroscopy using spectral focusing with glass dispersion,” Appl. Phys. Lett. 93(20), 201103 (2008). [CrossRef]

17.

A. F. Pegoraro, A. Ridsdale, D. J. Moffatt, Y. W. Jia, J. P. Pezacki, and A. Stolow, “Optimally chirped multimodal CARS microscopy based on a single Ti:sapphire oscillator,” Opt. Express 17(4), 2984–2996 (2009). [CrossRef] [PubMed]

18.

S. H. Parekh, Y. J. Lee, K. A. Aamer, and M. T. Cicerone, “Label-free cellular imaging by broadband coherent anti-Stokes Raman scattering microscopy,” Biophys. J. 99(8), 2695–2704 (2010). [CrossRef] [PubMed]

19.

B. von Vacano, W. Wohlleben, and M. Motzkus, “Actively shaped supercontinuum from a photonic crystal fiber for nonlinear coherent microspectroscopy,” Opt. Lett. 31(3), 413–415 (2006). [CrossRef] [PubMed]

20.

Refractive Index Database, http://refractiveindex.info.

21.

J.-C. Diels and W. Rudolph, Ultrashort Laser Pulse Phenomena (Elsevier Inc, 2006).

22.

National Institute of Advanced Industrial Science and Technology, SDBSWeb, http://riodb01.ibase.aist.go.jp/sdbs/.

23.

M. Bonn and E. Vartiainen, “Maximum entropy method for phase retrieval of CARS data,” http://memcars.amolf.nl/.

OCIS Codes
(290.5910) Scattering : Scattering, stimulated Raman
(300.6230) Spectroscopy : Spectroscopy, coherent anti-Stokes Raman scattering
(180.4315) Microscopy : Nonlinear microscopy

ToC Category:
Spectroscopy

History
Original Manuscript: July 19, 2011
Revised Manuscript: August 25, 2011
Manuscript Accepted: August 25, 2011
Published: September 14, 2011

Virtual Issues
Vol. 6, Iss. 10 Virtual Journal for Biomedical Optics

Citation
Hope T. Beier, Gary D. Noojin, and Benjamin A. Rockwell, "Stimulated Raman scattering using a single femtosecond oscillator with flexibility for imaging and spectral applications," Opt. Express 19, 18885-18892 (2011)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-19-20-18885


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