TY - JOUR
T1 - Exploring Image Processing Tools To Unravel Complex 1H-13C Heteronuclear Single-Quantum Correlation Nuclear Magnetic Resonance Spectra
T2 - A Demonstration for Pyrolysis Liquids
AU - Ghysels, Stef
AU - Verwaeren, Jan
AU - Heeres, Hero Jan
AU - Rohrbach, Léon
AU - Backx, Simon
AU - Mangelinckx, Sven
AU - Ronsse, Frederik
N1 - Publisher Copyright:
© 2023 American Chemical Society.
PY - 2023/3/16
Y1 - 2023/3/16
N2 - Pyrolysis 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-13C heteronuclear single-quantum correlation (HSQC) nuclear magnetic resonance (NMR). This makes 1H-13C HSQC NMR a valuable tool to fingerprint and quantitatively assess these complex liquids. However, data analysis of complex 1H-13C HSQC spectra lacks behind on these recent experimental developments. That is, 1H-13C HSQC spectra are often manually and ad hoc analyzed. This work, therefore, seeks to automate data analysis from 1H-13C 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-13C HSQC spectra, with an average R2 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-13C HSQC spectra has been explored and demonstrated.
AB - Pyrolysis 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-13C heteronuclear single-quantum correlation (HSQC) nuclear magnetic resonance (NMR). This makes 1H-13C HSQC NMR a valuable tool to fingerprint and quantitatively assess these complex liquids. However, data analysis of complex 1H-13C HSQC spectra lacks behind on these recent experimental developments. That is, 1H-13C HSQC spectra are often manually and ad hoc analyzed. This work, therefore, seeks to automate data analysis from 1H-13C 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-13C HSQC spectra, with an average R2 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-13C HSQC spectra has been explored and demonstrated.
UR - http://www.scopus.com/inward/record.url?scp=85149760745&partnerID=8YFLogxK
U2 - 10.1021/acs.energyfuels.2c04100
DO - 10.1021/acs.energyfuels.2c04100
M3 - Article
AN - SCOPUS:85149760745
SN - 0887-0624
VL - 37
SP - 4446
EP - 4459
JO - Energy and Fuels
JF - Energy and Fuels
IS - 6
ER -