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Article . 2019 . Peer-reviewed
License: Elsevier TDM
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Effects analysis on the gasification kinetic characteristics of food waste in supercritical water

Authors: Yi Fan; Jinke Gong; Jiaqiang E; Wen Cao; Feng Zhang; Wenwen Xu; Guanlin Liu; +1 Authors

Effects analysis on the gasification kinetic characteristics of food waste in supercritical water

Abstract

Abstract The gasification kinetic characteristics of food waste (FW) gasification by supercritical water (SCW) were investigated by examining the SCW gasification (SCWG) of FW in a quartz tube reactor, and the experimental results were investigated by using a series of kinetic models. The experimental results show that the carbon gasification efficiency increases with reaction temperature at the same residence time, and reactivity increases sharply at the early stage of gasification and then decreases with reaction time. The simulation results show that all the classical kinetic models underestimate the experimental results, similar to the models used in previous work on coal gasification by SCW. The underestimation of the models results from the catalytic effect of alkaline earth metals (AAEMs), which can notably increase the active sites of gasification reaction without changing the gasification kinetic mechanism. To solve the above problem, the catalytical effect to describe the kinetic behavior of the SCWG of FW is considered and a semiempirical modified random pore model (MRPM) is developed based on the RPM model. The simulation results of the MRP models are close to experimental findings, indicating that MRP model can be used to predict the entire process of SCWG under different conditions without dividing gasification into different stages of reaction. The MRP model can also be used for the prediction of SCWG of coal, biomass, and organic wastes and is crucial to reactor optimization and scaling up.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
120
Top 1%
Top 10%
Top 1%