Exploring Image Processing Tools To Unravel Complex ~1H-~(13)C Heteronuclear Single-Quantum Correlation Nuclear Magnetic Resonance Spectra: A Demonstration for Pyrolysis Liquids

摘要

Pyroiysis liquids are very complex and heterogeneous in composition. This makes them hard to comprehensively analyze, which is one of the hurdles that could hinder further advances in science and technology toward their valorization. Recently, renewed interest grew for quantitative recording of two-dimensional ~1H-~(13)C heteronuclear single-quantum correlation (HSQC) nuclear magnetic resonance (NMR). This makes ~1H-~(13)C HSQC NMR a valuable tool to fingerprint and quantitatively assess these complex liquids. However, data analysis of complex ~1H-~(13)C HSQC spectra lacks behind on these recent experimental developments. That is, ~1H-~(13)C HSQC spectra are often manually and ad hoc analyzed. This work, therefore, seeks to automate data analysis from ~1H-~(13)C HSQC spectra. We explored the use of image processing tools and identified their much underestimated potential. Indeed, many of the existing tools (often built-in software) were found to be applicable for noise detection/removal, generation/comparison of regions of interest, etc. Moreover, pseudo-Voigt peaks were fitted to the ~1H-~(13)C HSQC spectra, with an average R~2 of 0.94. These fitted spectral peaks allowed for the generation of a peak list, as an input for multivariate analysis. This allowed for pinpointing differences in the chemical composition of the samples. Overall, a new echelon for easy analysis of ~1H-~(13)C HSQC spectra has been explored and demonstrated.