Advanced models for the prediction of product yield in hydrothermal liquefaction via a mixture design of biomass model components coupled with process variables
Jie Yang,
He, Quan (Sophia),
Kenneth Corscadden,
Haibo Niu,
Jianan Lin and
Tess Astatkie
Applied Energy, 2019, vol. 233-234, 906-915
Abstract:
Hydrothermal liquefaction (HTL) has recently attracted great interest as a thermochemical conversion technique for biofuels production, however, suffers a lack of broadly applicable models for the prediction of product yield. This study developed a unique model for the prediction of HTL products yield via a mixture design of biomass model components coupled with process variables. The model compounds used in this study were soya protein for a protein representative, a mixture of cellulose and xylan for a saccharide representative, alkaline lignin for a lignin representative and soybean oil for a lipid representative. Reaction temperature (270–320 °C), time (5–20 min) and mass ratio of water/feedstocks (6:1–12:1) were chosen as the process variables of interest. The developed predictive models for biocrude yield and solid residue yield showed accuracy of (R2adj 94.6% and 93.2%, respectively), and were further validated using modelled feedstock and actual feedstock. These models can be used either to optimize HTL conditions when feedstock is known, or to optimize the composition of feedstock when reaction conditions are given. It was also observed that within the experimental design range, relatively mild HTL conditions eliminated alkaline lignin-lipid interaction and protein-lipid interaction, and thus enhanced biocrude formation; while more severe HTL conditions were preferred to reduce solid residue formation through promoting protein-saccharide interaction and saccharide-alkaline lignin interaction.
Keywords: Hydrothermal liquefaction; Quantitative prediction model; Bio-oil; Biomass model compounds; Mixture design (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261918315903
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:233-234:y:2019:i::p:906-915
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic
DOI: 10.1016/j.apenergy.2018.10.035
Access Statistics for this article
Applied Energy is currently edited by J. Yan
More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().