Mathematical modelling of lignin pyrolysis

Avni, E.; Coughlin, Robert W.; Solomon, P.R.; King, Hsiang Hui

doi:10.1016/0016-2361(85)90362-x

Cited by 72 publications

(54 citation statements)

References 6 publications

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“…15). The literature gives a vast range of rates for biomass pyrolysis: for lignin, activation energies ranging from 20 [36] to 46 [37] to 250 [38] kJ/mol have been given, while for cellulose recent studies have cited E = 120 to 210 [39] kJ/mol. For this work rate parameters E = 200 kJ/mol, A = 1.0@10 s were selected based on the 15 -1 amount of residue remaining after experiments at different temperatures (see later).…”

Section: Fuel Propertiesmentioning

confidence: 99%

“…However, at 673 K it is initially equal to that at 573 K and then drops to the char value with longer exposure, indicating that pyrolysis occurs slowly at 673 K but does not occur at all at 573 K. This observation together with the time scales for pyrolysis from the experiments was used to roughly choose the rate parameters. The activation energy selected (E = 200 kJ/mol) is at the upper end of the range given by the literature [36][37][38][39], but lower values such as the 50 kJ/mol used by Grønli et al [37] gave excessively long pyrolysis times at high temperature or too rapid pyrolysis at low temperature, depending on the value 20 of pre-exponential K used. Since the "lignin" in pyrolysis oil is chemically different from the lignin in wood, it is not surprising that its decomposition kinetics should be different.…”

Section: Residuesmentioning

confidence: 99%

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A model for the evaporation of biomass pyrolysis oil droplets

Hallett¹,

Clark²

2006

Fuel

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This paper presents a numerical model for the evaporation and pyrolysis of a single droplet of pyrolysis oil derived from biomass. Continuous thermodynamics theory for multicomponent droplet evaporation is used, with the fuel being represented by four fractions: organic acids, aldehydes/ketones, water, and pyrolytic lignin, each of which is described by a separate distribution function. Pyrolysis of the lignin fraction is included, and detailed properties for all fractions are presented. The model is compared with the results of suspended droplet experiments, and is shown to give good predictions of the times of the major events in the lifetime of a droplet.

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Section: Fuel Propertiesmentioning

confidence: 99%

Section: Residuesmentioning

confidence: 99%

A model for the evaporation of biomass pyrolysis oil droplets

Hallett¹,

Clark²

2006

Fuel

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“…19 Distributed activation energy models (DAEM) have been used for biomass pyrolysis kinetics since 1985, when Avni et al applied a DAEM for the formation of volatiles from lignin. 20 Later this type of research was extended to a wider range of biomasses and materials derived from plants, including several studies on tobacco devolatilization. [21][22][23][24][25][26][27][28][29][30][31][32] Despite the complicated mathematics of this type of modeling, the works based on DAEM kinetics have frequently employed more than one parallel reaction.…”

Section: Introductionmentioning

confidence: 99%

Thermogravimetric Study of Biomass Pyrolysis Kinetics. A Distributed Activation Energy Model with Prediction Tests

et al. 2010

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ABSTRACT. The pyrolysis of four biomasses (corn stalk, rice husk, sorghum straw and wheat straw) was studied at different temperature -time functions in inert gas flow by thermogravimetric analysis (TGA). Linear and stepwise heating programs were employed. A distributed activation energy model (DAEM) with three pools of reactant (three pseudocomponents) was used due to the complexity of the biomass samples of agricultural origin. Compensation effects were observed between the kinetic parameters similarly to the works of other investigators. The compensation effects result in ambiguous parameter values hence they were eliminated by decreasing the number of the unknown parameters. For this purpose part of the kinetic parameters was assumed to be the same for the four biomasses. This approach also helps to express the similarities of the samples in the model. The sixteen experiments were evaluated simultaneously by the method of least squares to obtain dependable kinetic parameters. 2The resulting models described well the experimental data and were suitable for predicting experiments at higher heating rates. The checks on the prediction capabilities were considered to be an essential part of the model verification.

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“…A handful of researchers have estimated lumped kinetic parameters of lignin pyrolysis. 16,44- 58 Jiang et al 52 summarized the global kinetic parameters from the literature for lignin pyrolysis and estimated by Kissinger's method. 59 The Kissinger method is commonly used to estimate global reaction parameters of biomass pyrolysis by fitting the maximal decomposition temperatures in DTG curves to temperature ramps.…”

Section: Introductionmentioning

confidence: 99%

Kinetics and reaction chemistry for slow pyrolysis of enzymatic hydrolysislignin and organosolv extracted lignin derived from maplewood

et al. 2012

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The kinetics and reaction chemistry for the pyrolysis of Maplewood lignin were investigated using both a pyroprobe reactor and a thermogravimetric analyser mass spectrometry (TGA-MS). Lignin residue after enzymatic hydrolysis and organosolv lignin derived from Maplewood were used to measure the kinetic behaviours of lignin pyrolysis and to analyse pyrolysis product distributions. The enzymatic lignin residue pyrolyzed at lower temperature than that of organosolv lignin. The differential thermogravimetric (DTG) peaks for pyrolysis of the enzymatic residue were more similar to the DTG peaks for pyrolysis of the original Maplewood than DTG of the organosolv lignin. The condensable liquid volatile products were collected from a Pyroprobe reactor with a liquid nitrogen trap. The primary monomeric phenolic compounds were guaiacol, syringol, and vanillic acid. However, only 14-36 carbon% of the sample could be detected by GC-MS. Over 60 carbon% of the condensable products were heavy tar molecules that are not detectable by GC-MS. These heavy tar molecules are the primary products from pyrolysis of lignin. Intermediate solid samples were also collected at various pyrolysis temperatures and characterized by elemental analysis, FT-IR, DP-MAS 13 C NMR, and TOC. The methoxy groups and ether linkages decreased and the non-protonated aromatic carbon-carbon bonds increased in the solid residues as the pyrolysis temperature increased. The carbon content of the initial lignin feed (derived from enzymatic hydrolysis) and the solid polyaromatics residue (obtained at 773 K) was 58 wt% and 74 wt% respectively. This polyaromatic residue contained about 69 wt% of the original lignin feed. The solid polyaromatics undergo further slow decomposition accompanied by a constant release of carbon dioxide as the pyrolysis reaction continues. The pyrolysis of the enzymatic lignin residue was modelled by two reactions in series. In the first pyrolysis step the lignin was decomposed with an apparent activation energy of 74 kJ mol -1 and a heat of reaction of -8,780 kJ kg -1 . The second pyrolysis step had an apparent activation energy of 110 kJ mol -1 and a heat of reaction of -2,819 kJ kg -1 . Lignin pyrolysis has lower activation energies and higher heats of reaction than cellulose pyrolysis.

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Mathematical modelling of lignin pyrolysis

Cited by 72 publications

References 6 publications

A model for the evaporation of biomass pyrolysis oil droplets

A model for the evaporation of biomass pyrolysis oil droplets

Thermogravimetric Study of Biomass Pyrolysis Kinetics. A Distributed Activation Energy Model with Prediction Tests

Kinetics and reaction chemistry for slow pyrolysis of enzymatic hydrolysislignin and organosolv extracted lignin derived from maplewood

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