A1 Journal article (refereed), original research

Bayesian Quantification for Coherent Anti-Stokes Raman Scattering Spectroscopy


Open Access hybrid publication

Publication Details
Authors: Härkönen Teemu, Roininen Lassi, Moores Matthew T., Vartiainen Erik
Publisher: American Chemical Society
Publication year: 2020
Language: English
Related Journal or Series Information: Journal of Physical Chemistry B
Volume number: 124
Issue number: 32
Start page: 7005
End page: 7012
Number of pages: 8
ISSN: 1520-6106
eISSN: 1520-5207
JUFO-Level of this publication: 1
Open Access: Open Access hybrid publication

Abstract

We propose a Bayesian statistical model for analyzing coherent anti-Stokes Raman scattering (CARS) spectra. Our quantitative analysis includes statistical estimation of constituent line-shape parameters, underlying Raman signal, error-corrected CARS spectrum, and the measured CARS spectrum. As such, this work enables extensive uncertainty quantification in the context of CARS spectroscopy. Furthermore, we present an unsupervised method for improving spectral resolution of Raman-like spectra requiring little to no a priori information. Finally, the recently-proposed wavelet prism method for correcting the experimental artefacts in CARS is enhanced by using interpolation techniques for wavelets. The method is validated using CARS spectra of adenosine mono-, di-, and triphosphate in water, as well as equimolar aqueous solutions of D-fructose, D-glucose, and their disaccharide combination sucrose.


Last updated on 2020-28-08 at 13:16