Using separable non-negative matrix factorization techniques for the analysis of time-resolved Raman spectra

TL;DR

This paper introduces a non-negative matrix factorization method tailored for analyzing time-resolved Raman spectra, enabling simultaneous extraction of component spectra and reaction kinetics from experimental data.

Contribution

It presents a novel separable NMF algorithm that can determine spectra and rate constants simultaneously, even with spectral interference and noise.

Findings

Successfully applied to synthetic spectra with different interference levels

Able to recover rate constants accurately in model reaction pathways

Discusses the method's potential and limitations in spectral analysis

Abstract

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.