Vibrational chemical imaging based on broadband laser pulses
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Coherent anti-Stokes Raman scattering (CARS) microscopy allows fast, label-free and chemically selective imaging of condensed-phase samples thanks to its high signal sensitivity. It also offers several other advantages such as intrinsic three-dimensional sectioning capability, longer penetration depth and high spatial resolution. In conventional CARS microscopy, two synchronized narrowband laser pulses are typically used to generate signals at a single vibrational resonance, from which vibrational images are constructed. Although this type of CARS methods has been proven to be an excellent visualizing tool for lipid in biological samples, it has two serious problems. First, the ubiquitous nonresonant background smears out vibrational signals, which makes quantitative image analysis very difficult. Second, the chemical information obtained in this method is seriously limited since only a single vibrational resonance is measured, which is far less information than full vibrational spectrum can offer. In the past few years, we have developed several novel CARS imaging techniques that can overcome these issues. All our methods require only a single broadband laser and produce background-free vibrational spectrum by combining the laser pulse shaping and various signal detection schemes. The first one obtains a vibrational spectrum over 800 ~ 1800 cm-1 in a single measurement by simultaneous excitation of multiple vibrational resonances and analysis of spectral interferences between the resonant and nonresonant signals. The second method adopts the spectral focusing mechanism, where stretched broadband pulses are used to excite a single vibrational resonance with great sensitivity. A novel frequency modulation (FM) scheme is invented to eliminate the non-resonant background. Complimentary spectral analysis algorithm is also developed to obtain quantitative CARS signals at the CH stretching region (2800 ~ 3100 cm-1). In this dissertation, the fundamental mechanisms, experimental implementations and various imaging applications of the above CARS methods are described in detail.