MOTIVATION
Optical, non-intrusive diagnostic methods such as Raman spectroscopy offer the advantage of providing spatially and temporally resolved information about processes through the interaction of light and matter without disturbing them. For example, the chemical composition and temperature in the sample volume can be measured. This only requires optical access to couple the laser in and couple out the measurement signal. However, one challenge is to reduce the partially broadband background, which is caused by thermal radiation or unwanted laser-induced fluorescence in high-temperature processes, for example. This otherwise overlays the weak Raman signal and makes quantification difficult or impossible.
A promising approach to dealing with this problem is offered by shifted-excitation Raman difference spectroscopy (SERDS), in which two Raman spectra are recorded with slightly shifted excitation wavelengths. This utilises the fact that the background remains comparatively constant at slightly different excitation wavelengths and only the Raman signal shifts spectrally with the excitation wavelength. By forming a difference spectrum, it is then ideally possible to completely eliminate the background. This approach has already produced promising results in the literature when analysing solids and liquids.
OBJECTIVE
The research question is to what extent concentration and temperature information in highly background-polluted gas phase flows can be quantitatively investigated and analysed using SERDS. For this purpose, the method is to be extended to processes in the gas phase in the vicinity of solid surfaces, which has so far remained unexplored for the spatially/temporally resolved 1D-SERDS. In order to realise this, it is necessary to adapt both the excitation and detection side of the dual-track test rig. Since the generated data is in the form of a difference spectrum, which differs from the standard form of a Raman spectrum, it is necessary to implement an evaluation routine to allow comparison of the experimentally generated data with the existing species databases.
