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Towards first-principles based kinetic modeling of biomass fast pyrolysis

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Abstract

Biomass conversion to chemicals and fuels through fast pyrolysis shows great potential but requires a more fundamental approach for its deployment. To this end, molecular-based kinetic modeling is starting to play a central role in the prediction of the molecular composition of bio-oil. A molecular-level representation of biomass provides the start point for the generation of detailed pyrolysis reaction networks for both the condensed and the gas phases. Significant progress has been made for cellulose, glucose-based carbohydrates, and lignin, together with the incorporation of the catalytic effects of minerals. Ab initio techniques are widely used to discriminate between reaction mechanisms and to calculate kinetic parameters. Automatic kinetic model generation is expected to play an even more important role in fast pyrolysis as it does already today. Experimental techniques enabled to obtain intrinsic kinetics and to decouple the timescales between reaction kinetics and analytic techniques. This greatly benefits the improvement of detailed kinetic models. The prospects for achieving a first-principles based kinetic model of biomass fast pyrolysis are promising. However, significant work is still needed to couple condensed- and gas-phase reaction networks.

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Abbreviations

ARM:

Attribute reaction modeling

CDK:

Continuous distribution kinetics

CPD:

Chemical percolation devolatilization

DFT:

Density functional theory

E a :

Activation energy (J mol−1)

FT-NIR:

Fourier-transform near infrared

GENESYS:

Generation of reacting systems

GPC:

Gel permeation chromatography

GSVR:

Gas-solid vortex reactor

HPLC:

High-performance liquid chromatography

INGen:

Interactive network generator

k :

Reaction pre-exponential factor (s−1)

LFER:

Linear free energy relationship

MMD:

Molar mass distribution

M n :

Number average molar mass (g mol−1)

M w :

Weight-average molar mass (g mol−1)

NMR:

Nuclear magnetic resonance

PDF:

Probability distribution function

PHASR:

Pulse-heated analysis of solid reactions

PLS:

Partial least square

RING:

Rule input network generator

RMG:

Reaction mechanism generator

SVUV-PIMS:

Synchrotron vacuum ultraviolet photoionization mass spectrometry

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Acknowledgements

The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme FP7/2007-2013/ERC grant agreement no. 290793 and the “Long Term Structural Methusalem Funding by the Flemish Government.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 664876. The SBO proposal “Bioleum” supported by the Institute for Promotion of Innovation through Science and Technology in Flanders (IWT) is acknowledged.

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  1. Laboratory for Chemical Technology, Ghent University, Technologiepark-Zwijnaarde 914, 9052, Ghent, Belgium

    Arturo Gonzalez-Quiroga, Kevin M. Van Geem & Guy B. Marin

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  1. Arturo Gonzalez-Quiroga
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  2. Kevin M. Van Geem
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Correspondence to Kevin M. Van Geem.

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Gonzalez-Quiroga, A., Van Geem, K.M. & Marin, G.B. Towards first-principles based kinetic modeling of biomass fast pyrolysis. Biomass Conv. Bioref. 7, 305–317 (2017). https://doi.org/10.1007/s13399-017-0251-0

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