Using separable non-negative matrix factorization techniques for the analysis of time-resolved Raman spectra
This work addresses the challenge of analyzing time-resolved Raman spectra for chemists and spectroscopists, offering a simultaneous estimation of spectra and kinetics, though it is an incremental improvement over existing NMF-based approaches.
The authors present a method using separable non-negative matrix factorization to simultaneously determine component spectra and rate constants from time-resolved Raman spectra, demonstrating its effectiveness on synthetic data with varying spectral interference and noise levels.
The key challenge of time-resolved Raman spectroscopy is the identification of the constituent species and the analysis of the kinetics of the underlying reaction network. In this work we present an integral approach that allows for determining both the component spectra and the rate constants simultaneously from a series of vibrational spectra. It is based on an algorithm for non-negative matrix factorization which is applied to the experimental data set following a few pre-processing steps. As a prerequisite for physically unambiguous solutions, each component spectrum must include one vibrational band that does not significantly interfere with vibrational bands of other species. The approach is applied to synthetic "experimental" spectra derived from model systems comprising a set of species with component spectra differing with respect to their degree of spectral interferences and signal-to-noise ratios. In each case, the species involved are connected via monomolecular reaction pathways. The potential and limitations of the approach for recovering the respective rate constants and component spectra are discussed.