Non-targeted analysis strategy for the identification of phenolic compounds in complex technical lignin samples
(2020) In ChemSusChem 13(17). p.4605-4612- Abstract
Lignin is the second most abundant biopolymer in nature and a promising renewable resource for aromatic chemicals. For the understanding of different lignin isolation and conversion processes, the identification of phenolic compounds is of importance. However, due to the vast number of possible chemical transformations, the prediction of produced phenolic structures is challenging, and a non-targeted analysis method is therefore needed. In this study, we present a non-targeted analysis method for the identification of phenolic compounds using ultra-high-performance supercritical fluid chromatography/high-resolution multiple stage tandem mass spectrometry combined with a Kendrick mass defect-based classification model. The method was... (More)
Lignin is the second most abundant biopolymer in nature and a promising renewable resource for aromatic chemicals. For the understanding of different lignin isolation and conversion processes, the identification of phenolic compounds is of importance. However, due to the vast number of possible chemical transformations, the prediction of produced phenolic structures is challenging, and a non-targeted analysis method is therefore needed. In this study, we present a non-targeted analysis method for the identification of phenolic compounds using ultra-high-performance supercritical fluid chromatography/high-resolution multiple stage tandem mass spectrometry combined with a Kendrick mass defect-based classification model. The method was applied to a Lignoboost Kraft lignin (LKL), a sodium Lignosulphonate lignin (SLS) and a depolymerised Kraft lignin (DKL) sample. In total, 260 tentative phenolic compounds were identified in the LKL sample, 50 in the SLS sample and 77 in the DKL sample.
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- author
- Prothmann, Jens LU ; Li, Kena LU ; Hulteberg, Christian LU ; Spégel, Peter LU ; Sandahl, Margareta LU and Turner, Charlotta LU
- organization
- publishing date
- 2020-09-07
- type
- Contribution to journal
- publication status
- published
- subject
- in
- ChemSusChem
- volume
- 13
- issue
- 17
- pages
- 8 pages
- publisher
- John Wiley & Sons Inc.
- external identifiers
-
- pmid:32468723
- scopus:85087315395
- ISSN
- 1864-564X
- DOI
- 10.1002/cssc.202000951
- language
- English
- LU publication?
- yes
- id
- e60f457c-ca6f-4656-bb0d-c5a62522703d
- date added to LUP
- 2020-06-03 06:13:24
- date last changed
- 2024-09-18 23:42:04
@article{e60f457c-ca6f-4656-bb0d-c5a62522703d, abstract = {{<p>Lignin is the second most abundant biopolymer in nature and a promising renewable resource for aromatic chemicals. For the understanding of different lignin isolation and conversion processes, the identification of phenolic compounds is of importance. However, due to the vast number of possible chemical transformations, the prediction of produced phenolic structures is challenging, and a non-targeted analysis method is therefore needed. In this study, we present a non-targeted analysis method for the identification of phenolic compounds using ultra-high-performance supercritical fluid chromatography/high-resolution multiple stage tandem mass spectrometry combined with a Kendrick mass defect-based classification model. The method was applied to a Lignoboost Kraft lignin (LKL), a sodium Lignosulphonate lignin (SLS) and a depolymerised Kraft lignin (DKL) sample. In total, 260 tentative phenolic compounds were identified in the LKL sample, 50 in the SLS sample and 77 in the DKL sample.</p>}}, author = {{Prothmann, Jens and Li, Kena and Hulteberg, Christian and Spégel, Peter and Sandahl, Margareta and Turner, Charlotta}}, issn = {{1864-564X}}, language = {{eng}}, month = {{09}}, number = {{17}}, pages = {{4605--4612}}, publisher = {{John Wiley & Sons Inc.}}, series = {{ChemSusChem}}, title = {{Non-targeted analysis strategy for the identification of phenolic compounds in complex technical lignin samples}}, url = {{http://dx.doi.org/10.1002/cssc.202000951}}, doi = {{10.1002/cssc.202000951}}, volume = {{13}}, year = {{2020}}, }