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Updated: Apr 14, 2026

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Extraction of Lignin with High β-O-4 Content by Mild Ethanol Extraction and Its Effect on the Depolymerization Yield
Published on: January 7, 2019
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Catalytic and Inhibitory Effects Induced by Noncovalent Interactions between Cellulose and Lignin during Fast
Fuat Sakirler1, M Doga Tekbas1, Hsi-Wu Wong1
1Department of Chemical Engineering, University of Massachusetts Lowell, One University Avenue, Lowell, Massachusetts 01854, United States.
Summary
Understanding biomass fast pyrolysis requires examining cellulose-lignin interactions. Specific lignin structures influence cellulose decomposition products, enabling targeted bio-oil chemical production.
Area of Science:
- Biomass conversion and renewable energy technologies.
- Chemical kinetics and reaction mechanisms.
- Materials science and bio-based chemical production.
Background:
- Biomass fast pyrolysis is a key technology for renewable fuels and chemicals.
- Process complexity and biomass heterogeneity limit bio-oil selectivity and commercialization.
- Molecular-level understanding of cellulose-lignin interactions is crucial for process optimization.
Purpose of the Study:
- To investigate the impact of lignin structures on cellulose-derived product yields during pyrolysis.
- To elucidate the molecular mechanisms governing cellulose-lignin interactions in biomass pyrolysis.
- To provide insights for engineering biomass feedstocks for selective chemical production.
Main Methods:
- Microreactor experiments to analyze pyrolysis product yields.
- Density functional theory (DFT) calculations to model molecular interactions.
- Analysis of specific lignin linkages (β-O-4 and 5-5) and their effects on cellulose pyrolysis products.
Main Results:
- Lignin's β-O-4 linkages inhibit levoglucosan and catalyze glycolaldehyde formation.
- Lignin's 5-5 linkages catalyze levoglucosan and inhibit glycolaldehyde formation.
- Both lignin linkages inhibit 5-hydroxymethylfurfural formation, driven by noncovalent cellulose-lignin interactions.
Conclusions:
- Noncovalent interactions between cellulose and lignin dictate pyrolysis product selectivity.
- Tailoring lignin structures via genetic engineering can enhance targeted bio-oil chemical production.
- Machine learning can correlate biomass structures with product yields for optimized pyrolysis.
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