relation: https://khub.utp.edu.my/scholars/16932/
title: Statistical analysis of microalgae supercritical water gasification: Reaction variables, catalysis and reaction pathways
creator: Tiong, L.
creator: Komiyama, M.
description: Despite the large number of research performed on the supercritical water gasification (SCWG) of microalgae, majority of them are specific to feed microalgae species and certain range of reaction conditions, obscuring the general understanding of the reaction. Here reported data on SCWG of microalgae are compiled and analyzed using multiple linear regression multivariate analysis, in an attempt to comprehensively understand the reaction. It is found that for non-catalytic reactions, variables such as reaction temperature, reaction time and feed concentration exert strong positive effect toward carbon gasification efficiency (CGE) of microalgae SCWG, while reaction pressure, water density, nitrogen content of feed microalgae (representing the proportion of protein in the feed), sulfur content and ash content show limited influence. Over Ru-based catalysts, the effect of feed concentration is weak but water density seems to show apparent correlation with CGE. The present analyses indicate that non-catalytic SCWG of microalgae is positive order on feed concentration with weak effect of water density, while with Ru-based catalysts the reaction is likely to be positively influenced by water density with weak effect of feed concentration. Based on these findings, reaction path differences between non-catalytic and Ru-catalyzed microalgae SCWG are discussed. © 2022 Elsevier B.V.
publisher: Elsevier B.V.
date: 2022
type: Article
type: PeerReviewed
identifier:   Tiong, L. and Komiyama, M.  (2022) Statistical analysis of microalgae supercritical water gasification: Reaction variables, catalysis and reaction pathways.  Journal of Supercritical Fluids, 183.   ISSN 08968446     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126102881&doi=10.1016%2fj.supflu.2022.105552&partnerID=40&md5=60e2bde035a74464f6d7be79fe7901cc
relation: 10.1016/j.supflu.2022.105552
identifier: 10.1016/j.supflu.2022.105552