A general reaction network and kinetic model of the hydrothermal liquefaction of microalgae Tetraselmis sp

•Systematic study of HTL conditions using microalga Tetraselmis sp.•A general reaction network and a quantitative kinetic model was applied for the HTL.•Kinetic parameters and activation energies were determined for each reaction pathway.•Model prediction of HTL product yields according to reaction...

Full description

Saved in:
Bibliographic Details
Published inBioresource technology Vol. 241; pp. 610 - 619
Main Authors Vo, The Ky, Kim, Seung-Soo, Ly, Hoang Vu, Lee, Eun Yeol, Lee, Choul-Gyun, Kim, Jinsoo
Format Journal Article
LanguageEnglish
Published England Elsevier Ltd 01.10.2017
Subjects
Biotechnology
Chlorophyta
Hydrothermal liquefaction
Kinetic model
Kinetics
Microalgae
Model prediction
Reaction network
Temperature
Tetraselmis sp
Model prediction
Kinetic model
Microalgae
Tetraselmis sp
Hydrothermal liquefaction
Reaction network
Online AccessGet full text

Cover

More Information
Summary:•Systematic study of HTL conditions using microalga Tetraselmis sp.•A general reaction network and a quantitative kinetic model was applied for the HTL.•Kinetic parameters and activation energies were determined for each reaction pathway.•Model prediction of HTL product yields according to reaction time and temperature. In this work, the hydrothermal liquefaction (HTL) of microalgal Tetraselmis sp. was conducted at various reaction temperatures (250–350°C) and reaction times (10–60min). A general reaction network and a quantitative kinetic model were proposed for the HTL of microalgae. In this reaction network, the primary decomposition of lipids, proteins, and carbohydrates generated heavy oil (HO), light oil (LO), and aqueous-phase (AP) products. Then, reversible interconversions and further decomposition of these product fractions to produce gas product were followed. The model accurately captures the trends observed in the experimental data. Analyses of the kinetic parameters (reaction rate constants and activation energies) suggested the dominant reaction pathways as well as the contribution of the biochemical compositions to the bio-oil yield. Finally, the kinetic parameters calculated from the model were utilized to explore the parameter space in order to predict the liquefaction product yields depending on the reaction time and temperature.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0960-8524
1873-2976
DOI:10.1016/j.biortech.2017.05.186