2021
DOI: 10.1002/cmtd.202100028
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Identification and Classification of Technical Lignins by means of Principle Component Analysis and k‐Nearest Neighbor Algorithm

Abstract: The characterization of technical lignins is a key step for the efficient use and processing of this material into valuable chemicals and for quality control. In this study 31 lignin samples were prepared from different biomass sources (hardwood, softwood, straw, grass) and different pulping processes (sulfite, Kraft, organosolv). Each lignin was analyzed by attenuated total reflectance Fourier transform infrared (ATR-FT-IR) spectroscopy. Statistical analysis of the ATR-FT-IR spectra by means of principal comp… Show more

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Cited by 4 publications
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“…However, some differences must be highlighted. Lignosulfonate reduced the peaks at 1685 and 1150 cm − 1 , corresponding to the C = O vibration in non-conjugated moieties [43,44]. Lignosulfonate presented a peak in the region of 1373 cm − 1 , attributed to the vibration of in-plane deformation of phenolic hydroxyl, according to Sameni et al [45].…”
Section: Production and Application Of Lignosulfonatementioning
confidence: 88%
“…However, some differences must be highlighted. Lignosulfonate reduced the peaks at 1685 and 1150 cm − 1 , corresponding to the C = O vibration in non-conjugated moieties [43,44]. Lignosulfonate presented a peak in the region of 1373 cm − 1 , attributed to the vibration of in-plane deformation of phenolic hydroxyl, according to Sameni et al [45].…”
Section: Production and Application Of Lignosulfonatementioning
confidence: 88%