The DOI matches its Crossref record; 60 of the 60 references it cites were found in a registry or an index.
A mechanistic model of fast pyrolysis of glucose-based carbohydrates to predict bio-oil composition
Abstract
Bio-oil obtained from fast pyrolysis of biomass has the potential to be upgraded to renewable, drop-in fuel intermediates. The quality of bio-oil produced is critical to downstream process development and is determined by a number of factors like reaction timescale, extent of primary and secondary reactions, and the presence of minerals. In this work, we provide a mechanistic understanding of the various competing reactions in fast pyrolysis of cellulose and other glucose-based carbohydrates through a unified microkinetic model. The model incorporates the reactions of the cellulose chain and of the glucose intermediate to form a variety of bio-oil components, which are confirmed by either experiments or theoretical calculations reported in the literature. The majority of the Arrhenius rate parameters were based on existing studies, while a small number were fitted to match the experimental product distribution over a wide range of temperatures. The model yields of all the major primary fast pyrolysis products, viz., levoglucosan, formic acid, glycolaldehyde, 5-hydroxymethyl furfural, furfural and char, match reasonably well with the experimental data over the temperature range of 400–550 °C. The model predicted that the time required for complete conversion corresponds to 2.5–3 s. Net rate analysis identified key pathways to levoglucosan via either mid-chain initiation, or depropagation and end-chain initiation that were dominant over the timescales of 0–100 ms and 100–1000 ms, respectively, at 500 °C. Unlike the existing lumped kinetic models, our model provides a detailed picture of levoglucosan formation that involves mid-chain glycosidic bond cleavage followed by unzipping of levoglucosan from the chain ends. The model, utilizing the same set of rate coefficients, was able to predict the dominant products of fast pyrolysis of maltohexaose, cellobiose and glucose that also are in good agreement with experimental data. The initial chain length of cellulose was found to have a profound effect on the product yields for chain lengths shorter than 50, while it had no effect on the total reaction time.
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Cites
Synthesis of Transportation Fuels from Biomass: Chemistry, Catalysts, and Engineering
Huber, G. W., Iborra, S., & Corma, A. (2006) · Chemical Reviews · doi:10.1021/cr068360d · Cited by 7,664
Pyrolysis of Wood/Biomass for Bio-oil: A Critical Review
Mohan, D., Pittman, C. U., & Steele, P. H. (2006) · Energy & Fuels · doi:10.1021/ef0502397 · Cited by 5,663
Renewable Chemical Commodity Feedstocks from Integrated Catalytic Processing of Pyrolysis Oils
Vispute, T. P., Zhang, H., Sanna, A., Xiao, R., & Huber, G. W. (2010) · Science · doi:10.1126/science.1194218 · Cited by 1,088
The mechanism for thermal decomposition of cellulose and its main products
Shen, D. K., & Gu, S. (2009) · Bioresource Technology · doi:10.1016/j.biortech.2009.06.095 · Cited by 994
Cellulose Pyrolysis Kinetics: The Current State of Knowledge
Antal, M. J. J., & Varhegyi, G. (1995) · Industrial & Engineering Chemistry Research · doi:10.1021/ie00042a001 · Cited by 859
Characterization of biochar from fast pyrolysis and gasification systems
Brewer, C. E., Schmidt‐Rohr, K., Satrio, J. A., & Brown, R. C. (2009) · Environmental Progress & Sustainable Energy · doi:10.1002/ep.10378 · Cited by 833
Chemical Kinetics of Biomass Pyrolysis
Ranzi, E., Cuoci, A., Faravelli, T., Frassoldati, A., Migliavacca, G., Pierucci, S., & Sommariva, S. (2008) · Energy & Fuels · doi:10.1021/ef800551t · Cited by 757
Kinetics and Mechanism of Cellulose Pyrolysis
Lin, Y.-C., Cho, J., Tompsett, G. A., Westmoreland, P. R., & Huber, G. W. (2009) · The Journal of Physical Chemistry C · doi:10.1021/jp906702p · Cited by 698
Biomass as renewable feedstock in standard refinery units. Feasibility, opportunities and challenges
Melero, J. A., Iglesias, J., & Garcia, A. (2012) · Energy & Environmental Science · doi:10.1039/c2ee21231e · Cited by 470
Product distribution from fast pyrolysis of glucose-based carbohydrates
Patwardhan, P. R., Satrio, J. A., Brown, R. C., & Shanks, B. H. (2009) · Journal of Analytical and Applied Pyrolysis · doi:10.1016/j.jaap.2009.08.007 · Cited by 469
Cited by
Development of biochar-based functional materials: toward a sustainable platform carbon material
Liu, W.-J., Jiang, H., & Yu, H.-Q. (2015) · Chemical Reviews · doi:10.1021/acs.chemrev.5b00195 · Cited by 1,754
Catalytic fast pyrolysis of lignocellulosic biomass
Liu, C., Wang, H., Karim, A. M., Sun, J., & Wang, Y. (2014) · Chem. Soc. Rev. · doi:10.1039/c3cs60414d · Cited by 1,117
Catalytic co-pyrolysis of lignocellulosic biomass with polymers: a critical review
Zhang, X., Lei, H., Chen, S., & Wu, J. (2016) · Green Chemistry · doi:10.1039/c6gc00911e · Cited by 497
A mechanistic model of fast pyrolysis of hemicellulose
Zhou, X., Li, W., Mabon, R., & Broadbelt, L. J. (2018) · Energy & Environmental Science · doi:10.1039/c7ee03208k · Cited by 240
Self-citationRecent Progress in Quantum Chemistry Modeling on the Pyrolysis Mechanisms of Lignocellulosic Biomass
Hu, B., Zhang, B., Xie, W.-L., Jiang, X.-Y., Liu, J., & Lu, Q. (2020) · Energy & Fuels · doi:10.1021/acs.energyfuels.0c01948 · Cited by 161
Metadata
- Authors
- Vinu, R., & Broadbelt, L. J.
- Venue
- Energy & Environmental Science
- Publisher
- Royal Society of Chemistry (RSC)
- Published
- 2012
- Volume
- 5
- Issue
- 12
- Pages
- 9808
- ISSN
- 1754-5692 (ISSN-L)
- 1754-5706
- OpenAlex
- W2025770802
- Cited by
- 364
- References
- 60
- FWCI
- 11.34
- Type
- journal article
- Language
- en
- Open access
- closed
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