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Madhawa Jayathilake and Souman Rudra Department of Engineering Sciences, University of Agder, Grimstad, Norway E-mail: [email protected] Hydrothermal Liquefaction modeling of lignin Using A Modified Multistage Shrinking-Core Model Design and Model development 1. Shrinking-core concept 2. Design of the model 3. Reactions and kinetics RESULTS 2. Impact of particle size 1. Impact of Temperature 3. Impact of heating rate CONCLUSIONS REFERENCES 1. Abstract INTRODUCTION 3. Hydrothermal Liquefaction Investigating the effect of process parameters on product yields Modeling the particle decomposition as a shrinking core system and developing a new hydrolysis reaction rate constant Integrating the hydrolysis model with a kinetic model to model the complete liquefaction process and determining the output yields To develop a mathematical relationship between operating parameters and their effects on HTL yields using shrinking core concept, reaction kinetics by giving importance to hydrolysis reactions The calculated results showed a reasonable agreement to the experimentally obtained data in the literature. The used parameters for the calculation also gave a good correlation to those reported in the literature With this model, time for complete decomposition of the particle can be easily predicted. Appropriate heating rates, particle sizes and operating temperatures for optimum product yields can be determined using this model At different conditions, decomposition of the lignin particle can be studied with this model. Effect of heating rate is evident only at shorter residence times and that could support the fact that heating rate is a vital parameter in fast liquefaction Operating temperature plays a vital part in changing the product composition significantly Simplified scheme of the proposed shrinking core model 1.Yong TL-K, Matsumura Y. Kinetic Analysis of Lignin Hydrothermal Conversion in Sub- and Supercritical Water. Ind Eng Chem Res 2013;52:562 639. doi:10.1021/ie400600x. 2.Pińkowska H, Wolak P, Złocińska A. Hydrothermal decomposition of alkali lignin in sub- and supercritical water. Chem Eng J 2012;187:4104. d oi:10.1016/j.cej.2012.01.092. 3. Zhang B, Huang H-J, Ramaswamy S. Reaction kinetics of the hydrothermal treatment of lignin. Appl Biochem Biotechnol 2008;147:11931. do i:10.1007/s12010-007-8070-6. 4.Galgano A, Blasi CD. Modeling Wood Degradation by the Unreacted-Core-Shrinking Approximation. Ind Eng Chem Res 2003;42:210111. doi: 10.1021/ie020939o. Hydrothermal liquefaction is a thermal depolymerization method which can convert wet bio mass into an output consist of a crude like oil, an aqueous phase with valuable compound s, a gas phase and a solid residue Reaction pathways used in the model Incorporated reactions in the model Impact of heating rate on lignin liquefaction in a wide rang e of temperature variation Validation of the model (Yong and Matsumara) + 2 ՜ 1 ՜ 2 L + 2 ՜ 3 2 L + 2 ՜ 4 L + 2 ՜ 5 G + 2 ՜ 6 G + 2 ՜ 7 + 2 ՜ 8 Cℎ + 2 ՜ 9 Cℎ + 2 10 + 2 11 + 2 12 + 2 13 + 2 14 2 ℎ + 2 15 ℎ + 2 16 Development process of the model Hydrolysis of lignin particle using shrinking core concept Lignin characteristics and loading conditions (Lignin, Water) Stoichiometry for reactions And Kinetic data Development of deferential equations Calculations by MATLAB Outputs and analysis Validating the outputs with Yield values from literature Char Gas Phase Aqueous Phase Biocrude phase 2. Aim 3. Objectives Subcri tical Condit ions HTL PROCESS Supercri tical Conditi ons HTL Bio-Crude HTL Advantages No feed drying No reducing gas Suitable for all kind of biomasses 95%+ carbon efficient upgrading step Recycle of aqueous Byproduct Footprint is less than other biological conversion process Confirmed 1- stage Upgrading Process is robust and non- biological = 3 1 3 0 ( 1 + 1 = rate coefficient for lignin particle hydrolysis = bulk water monomer concentration = concentration of lignin 0 = radius of the lignin particle = density of the lignin particle =stoichiometry value of water in hydrolysis reaction =mass transfer coefficient of the lignin particle =hydrolysis rate constant hydrolysis reaction rate constant Effect of temperature on TOC and gas yields Effect of temperature on char and Aromatic compound yields Effect of temperature on the lignin hydrolysis With increasing temperature lignin particle shows a faster decomposition. Maximum TOC yield is obtained at 573K, which is the lowest temperature investigated here. Meanwhile, Aromatic compounds ha ve shown the same pattern as TOC. Therefore lower temperatures have produced more TOC and Aromatic compounds. Highest char yield is obtained at 638K while highest gas yield is also obtained at 638K. Thus, when the operating temperature is c losed to critical temperature, higher char and gas yields are obtained Bigger particle radius has result in a slower decomposition of the lignin particle and it has caused a decrease in the product yields . Thus with a smaller particle a higher product yields are obtained with the same residence time. Slower heating rates have resulted in a faster product yield increase. Ultimately when the temperature value reaches 647K(critical point) Product yields have become almost the same value. Therefore, Impact of heating rate is important only at shorter residenc e times. Therefore, heating rate could be an important aspect in the fast liquefaction concept. Model is validated with the experimental data available in the literature (Yong and Matsumara) and shows a good agreement with the data. When calculating the stoichiometry, carbon balance has been considered and the elementa l balance for H and O is only an approximation. All the compounds were normalized to1ato m C per molecule for simplifying the calculations. In order to determine the stoichiometry for each reaction, set of stoichiometric coefficients f or each reaction is calculated which has a minimum of residual sum of squares particle is considered as a spherical particle with a given radius It is submerged in a huge water volume, which is much larger than the radius of the particle Dilution of the hydrolysis products is assumed to be infinite at a given distance from the particle center Particle decomposition is assumed only in the radial direction Thermophysical properties are presumed to be constant throughout the process Temperature of the particle is always supposed to be equals to the temperature of the fluid surrounding it No mass transfer is considered and no accumulation of products from the hydrolysis in the particle is considered It is assumed that all the products from hydrolysis leave the particle surface and does not form a layer on the outside of the wood particle Hydrolysis is assumed only happen at the surface of the particle Building a sustainable European biofuel industry. Nov 4-6, 2019, Gothenburg, Sweden Impact of particle size on the lignin hydrolysis ( using 0.08 mm and 0.2 mm particles) Currently lignin is under utilized as a low value-added fuel or to produce aromatics or macromolecule products, which is a costly process. However HTL can give a cheaper option to produce a biocrude with phenolics and aromatic hydrocarbons as well as an aqueous phase rich in phenolic compounds. Since the liquefaction process itself a complex process, the research into the aqueous phase and biocrude phase needs more investigations. A new hydrolysis reaction rate constant is developed using the shrinking core concept to model the hydrolysis effect on the lignin particle. Diffusion of water monomers to the particle surface to initiate hydrolysis and dissolution of the products in water is given importance during the modeling process. After the particle decomposition, dissolved compounds behave according to a kinetic model. In the modified shrinking core model, lignin particle is hydrolyzed, and in different stages different compounds are released to the water medium. Initially, lignin is decomposed into guaiacol, aromatic hydrocarbons, total organic carbon (TOC), Char, and Gas. In further hydrolysis reactions, catechol and phenolic compounds are also formed along with some more inter reactions among the compounds.
Transcript
Page 1: Hydrothermal Liquefaction modeling of lignin Using A ... · 4.Galgano A, Blasi CD. Modeling Wood Degradation by the Unreacted-Core-Shrinking Approximation. Ind Eng Chem Res 2003;42:2101–11.

Madhawa Jayathilake and Souman Rudra

Department of Engineering Sciences, University of Agder, Grimstad, Norway E-mail: [email protected]

Hydrothermal Liquefaction modeling of lignin Using A Modified Multistage

Shrinking-Core Model

Design and Model development

1. Shrinking-core concept 2. Design of the model 3. Reactions and kinetics

RESULTS

2. Impact of particle size1. Impact of Temperature 3. Impact of heating rate

CONCLUSIONS REFERENCES

1. Abstract

INTRODUCTION 3. Hydrothermal Liquefaction

• Investigating the effect of process parameters on product yields

• Modeling the particle decomposition as a shrinking core system

and developing a new hydrolysis reaction rate constant

• Integrating the hydrolysis model with a kinetic model to model

the complete liquefaction process and determining the output

yields

To develop a mathematical relationship between operating

parameters and their effects on HTL yields using shrinking core

concept, reaction kinetics by giving importance to hydrolysis

reactions

❑ The calculated results showed a reasonable agreement to the experimentally obtained data in the literature.

❑ The used parameters for the calculation also gave a good correlation to those reported in the literature

❑ With this model, time for complete decomposition of the particle can be easily predicted.

❑ Appropriate heating rates, particle sizes and operating temperatures for optimum product yields can be determined using this model

❑ At different conditions, decomposition of the lignin particle can be studied with this model.

❑ Effect of heating rate is evident only at shorter residence times and that could support the fact that heating rate is a vital parameter in fast liquefaction

❑ Operating temperature plays a vital part in changing the product composition significantly

Simplified scheme of the proposed shrinking core model

1.Yong TL-K, Matsumura Y. Kinetic Analysis of Lignin Hydrothermal Conversion in Sub- and Supercritical Water. Ind Eng Chem Res 2013;52:562

6–39. doi:10.1021/ie400600x.

2.Pińkowska H, Wolak P, Złocińska A. Hydrothermal decomposition of alkali lignin in sub- and supercritical water. Chem Eng J 2012;187:410–4.

d oi:10.1016/j.cej.2012.01.092.

3. Zhang B, Huang H-J, Ramaswamy S. Reaction kinetics of the hydrothermal treatment of lignin. Appl Biochem Biotechnol 2008;147:119–31. do

i:10.1007/s12010-007-8070-6.

4.Galgano A, Blasi CD. Modeling Wood Degradation by the Unreacted-Core-Shrinking Approximation. Ind Eng Chem Res 2003;42:2101–11. doi:

10.1021/ie020939o.

Hydrothermal liquefaction is a thermal depolymerization method which can convert wet bio

mass into an output consist of a crude like oil, an aqueous phase with valuable compound

s, a gas phase and a solid residue

Reaction pathways used in the model

Incorporated reactions in the model

Impact of heating rate on lignin liquefaction in a wide rang

e of temperature variation

Validation of the model (Yong and Matsumara)

𝑙𝑖𝑔𝑛𝑖𝑛 + 𝐻2𝑂 ՜𝑘1𝑔𝑢𝑎𝑖𝑎𝑐𝑜𝑙

𝑙𝑖𝑔𝑛𝑖𝑛 ՜𝑘2𝑐ℎ𝑎𝑟

L𝑖𝑔𝑛𝑖𝑛 + 𝐻2𝑂 ՜𝑘3𝐶𝑂2

L𝑖𝑔𝑛𝑖𝑛 + 𝐻2𝑂 ՜𝑘4𝑇𝑂𝐶

L𝑖𝑔𝑛𝑖𝑛 + 𝐻2𝑂 ՜𝑘5𝐴𝑟𝑜𝑚𝑎𝑡𝑖𝑐𝑠

G𝑢𝑎𝑖𝑎𝑐𝑜𝑙 + 𝐻2𝑂 ՜𝑘6𝐶𝑎𝑡𝑒𝑐ℎ𝑜𝑙

G𝑢𝑎𝑖𝑎𝑐𝑜𝑙 + 𝐻2𝑂 ՜𝑘7𝑇𝑂𝐶

𝐺𝑢𝑎𝑖𝑎𝑐𝑜𝑙 + 𝐻2𝑂 ՜𝑘8𝑃ℎ𝑒𝑛𝑜𝑙

C𝑎𝑡𝑒𝑐ℎ𝑜𝑙 + 𝐻2𝑂 ՜𝑘9𝑇𝑂𝐶

C𝑎𝑡𝑒𝑐ℎ𝑜𝑙 + 𝐻2𝑂𝑘10

𝑃ℎ𝑒𝑛𝑜𝑙

𝐴𝑟𝑜𝑚𝑎𝑡𝑖𝑐𝑠 + 𝐻2𝑂𝑘11

𝑐ℎ𝑎𝑟

𝑇𝑂𝐶 + 𝐻2𝑂𝑘12

𝑐ℎ𝑎𝑟

𝑇𝑂𝐶 + 𝐻2𝑂𝑘13

𝐴𝑟𝑜𝑚𝑎𝑡𝑖𝑐𝑠

𝑇𝑂𝐶 + 𝐻2𝑂𝑘14

𝐶𝑂2

𝑃ℎ𝑒𝑛𝑜𝑙 + 𝐻2𝑂𝑘15

𝑇𝑂𝐶

𝑃ℎ𝑒𝑛𝑜𝑙 + 𝐻2𝑂𝑘16

𝐶ℎ𝑎𝑟

Development process of the model

Hydrolysis of lignin particle

using shrinking core concept

Lignin characteristics

and loading conditions

(Lignin, Water)

Stoichiometry for reactions

And Kinetic data

Development of

deferential equations

Calculations by MATLAB

Outputs and analysis

Validating the outputs with

Yield values from literature

Char

Gas Phase

Aqueous Phase

Biocrude phase

2. Aim

3. Objectives Subcritical

Conditions

HTL PROCESS

Supercritical

Conditions HTL Bio-Crude

HTL Advantages

No feed drying

No reducing gas

Suitable for all kind of

biomasses

95%+ carbon efficient

upgrading step

Recycle of aqueous

ByproductFootprint is less than other

biological conversion

process

Confirmed 1-stage

Upgrading

Process is robust and

non-biological

𝑘𝑥 =3𝐶𝑏𝐶𝑙𝑖𝑔

13

൰𝑟0𝛽𝜌(1𝑘𝐴

+1𝑘𝐻

𝑘𝑥 = rate coefficient for lignin particle hydrolysis𝐶𝑏 = bulk water monomer concentration𝐶𝑙𝑖𝑔 = concentration of lignin

𝑟0 = radius of the lignin particle𝜌 = density of the lignin particle𝛽 =stoichiometry value of water in hydrolysis reaction𝑘𝐴 =mass transfer coefficient of the lignin particle𝑘𝐻 =hydrolysis rate constant

hydrolysis reaction rate constant

Effect of temperature on TOC and gas yields

Effect of temperature on char and Aromatic compound yields

Effect of temperature on the lignin hydrolysis

❑With increasing temperature lignin particle shows a faster decomposition.

❑Maximum TOC yield is obtained at 573K, which is the lowest temperature investigated here. Meanwhile, Aromatic compounds ha

ve shown the same pattern as TOC. Therefore lower temperatures have produced more TOC and Aromatic compounds.

❑ Highest char yield is obtained at 638K while highest gas yield is also obtained at 638K. Thus, when the operating temperature is c

losed to critical temperature, higher char and gas yields are obtained

❑ Bigger particle radius has result in a slower decomposition of the lignin particle and it has caused a decrease in the product yields

. Thus with a smaller particle a higher product yields are obtained with the same residence time.

❑ Slower heating rates have resulted in a faster product yield increase. Ultimately when the temperature value reaches 647K(critical

point) Product yields have become almost the same value. Therefore, Impact of heating rate is important only at shorter residenc

e times. Therefore, heating rate could be an important aspect in the fast liquefaction concept.

❑Model is validated with the experimental data available in the literature (Yong and Matsumara) and shows a good agreement with

the data.

❑ When calculating the stoichiometry, carbon balance has been considered and the elementa

l balance for H and O is only an approximation. All the compounds were normalized to1ato

m C per molecule for simplifying the calculations.

❑ In order to determine the stoichiometry for each reaction, set of stoichiometric coefficients f

or each reaction is calculated which has a minimum of residual sum of squares

❑ particle is considered as a spherical particle with a given radius ❑ It is submerged in a huge water volume, which is much larger than the radius

of the particle❑ Dilution of the hydrolysis products is assumed to be infinite at a given

distance from the particle center❑ Particle decomposition is assumed only in the radial direction❑ Thermophysical properties are presumed to be constant throughout the

process❑ Temperature of the particle is always supposed to be equals to the

temperature of the fluid surrounding it❑ No mass transfer is considered and no accumulation of products from the

hydrolysis in the particle is considered❑ It is assumed that all the products from hydrolysis leave the particle surface

and does not form a layer on the outside of the wood particle❑ Hydrolysis is assumed only happen at the surface of the particle

Building a sustainable European biofuel industry. Nov 4-6, 2019, Gothenburg, Sweden

Impact of particle size on the lignin hydrolysis ( using 0.08

mm and 0.2 mm particles)

Currently lignin is under utilized as a low value-added fuel or to

produce aromatics or macromolecule products, which is a costly

process. However HTL can give a cheaper option to produce a

biocrude with phenolics and aromatic hydrocarbons as well as an

aqueous phase rich in phenolic compounds. Since the liquefaction

process itself a complex process, the research into the aqueous

phase and biocrude phase needs more investigations.

A new hydrolysis reaction rate constant is developed using the

shrinking core concept to model the hydrolysis effect on the lignin

particle. Diffusion of water monomers to the particle surface to

initiate hydrolysis and dissolution of the products in water is given

importance during the modeling process. After the particle

decomposition, dissolved compounds behave according to a kinetic

model.

In the modified shrinking core model, lignin particle is hydrolyzed,

and in different stages different compounds are released to the

water medium. Initially, lignin is decomposed into guaiacol,

aromatic hydrocarbons, total organic carbon (TOC), Char, and Gas.

In further hydrolysis reactions, catechol and phenolic compounds

are also formed along with some more inter reactions among the

compounds.

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