Raman spectra provide a rich and powerful label-free probe of biological systems. While the narrow spectral features make Raman spectroscopy extremely attractive, the weak strength of Raman scattering makes it difficult to deeply in many situations. Low frequency Raman scattering spectroscopy provides the potential for probing macromolecular and local material properties. Until recently, the acquisition of such low frequency Raman spectra has been limited by technical challenges. We will discuss newly developed tools that allow for high-speed time-domain Raman spectroscopy of low and fingerprint region Raman spectra. Imaging performance and robustness of the signal to scattering will also be discussed.
Raman microscopy is a valuable approach to label-free chemical imaging. Recent advances have enabled the development of rapid methods for hyperspectral microscopy using impulsive stimulated Raman scattering (ISRS) that focus on low-frequency Raman modes of materials. The persistent challenge with Raman spectroscopic methods is low signal due to the relatively weak Raman scattering. ISRS microscopy allows for high quality hyperspectral imaging of low and fingerprint Raman vibrational frequencies but is normally subject to poor performance in the presence of optical scattering. We will present methods that solve this issue and allow for high-quality imaging when strong optical scattering is present.
Low frequency vibrations (< 200cm^(-1)) contain the structural information of molecules or the crystal lattice - making low frequency Raman imaging an ideal candidate to analyze heavy molecules, crystal formation etc. The longer integration times of spontaneous Raman spectroscopy, however, limits the study of dynamic structural changes.
In our work, we have built a stimulated Raman scattering (SRS) pump probe scheme combining impulsive excitation with a fast acousto-optics delay line. With a pixel dwell time of 25μs, we have acquired, on a shot noise limited detection system, sub second low frequency (< 200cm^(-1)) hyper-spectral SRS images of various samples.
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