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arXiv · 2007.06428

Analyzing Raman Spectral Data without Separability Assumption

Konstantin Fackeldey·Jonas Röhm·Amir Niknejad·Surahit Chewle·Marcus Weber
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Abstract

Raman spectroscopy is a well established tool for the analysis of vibration spectra, which then allow for the determination of individual substances in a chemical sample, or for their phase transitions. In the Time-Resolved-Raman-Sprectroscopy the vibration spectra of a chemical sample are recorded sequentially over a time interval, such that conclusions for intermediate products (transients) can be drawn within a chemical process. The observed data-matrix $M$ from a Raman spectroscopy can be regarded as a matrix product of two unknown matrices $W$ and $H$, where the first is representing the contribution of the spectra and the latter represents the chemical spectra. One approach for obtaining $W$ and $H$ is the non-negative matrix factorization. We propose a novel approach, which does not need the commonly used separability assumption. The performance of this approach is shown on a real world chemical example.

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Konstantin Fackeldey, Jonas Röhm, Amir Niknejad, Surahit Chewle, Marcus Weber. 2020-07-13. Analyzing Raman Spectral Data without Separability Assumption. https://arxiv.org/abs/2007.06428

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