Highly efficient reforming of toluene to syngas in a gliding arc plasma reactor

Mei, Danhua, Zhang, Peng, Liu, Shiyun, Ding, Liang, Ma, Yichen ORCID: 0000-0002-4404-8714, Zhou, Renwu, Gu, Haochi, Fang, Zhi, Cullen, Patrick J and Tu, Xin ORCID: 0000-0002-6376-0897
(2021) Highly efficient reforming of toluene to syngas in a gliding arc plasma reactor. JOURNAL OF THE ENERGY INSTITUTE, 98. pp. 131-143.

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Plasma reforming is a promising technology to transform tars from biomass gasification into valuable fuels and chemicals. However, the key performance (tar conversion, gas yield and energy efficiency) of the plasma tar reforming process can be significantly influenced by operating conditions such as the gas composition. In this study, the effect of CO2, steam and O2 on the plasma reforming of toluene, a model tar compound, was investigated in a gliding arc (GA) reactor. Compared to the plasma reforming of toluene with N2, the presence of oxidative gases (CO2, H2O and O2) can generate a highly reactive plasma environment, thus creating new reaction pathways in the plasma conversion of toluene. The optimal content of CO2, H2O and O2 to balance the toluene conversion, syngas yield and energy efficiency in the plasma reforming was 2 vol%, 4 vol% and 2 vol%, respectively, suggesting that the presence of an appropriate amount of oxidative gas (CO2, H2O and O2) is important to maximize the key performance of the plasma reforming process. The highest toluene conversion of 78.3%, syngas yield of 73.9% and energy efficiency of 69.5 g/kWh were achieved simultaneously in the plasma reforming of toluene containing 4 vol% steam. The reaction pathways in the plasma reforming of toluene have been proposed through the analysis of gas and liquid products coupled with optical emission spectroscopic diagnostics.

Item Type: Article
Uncontrolled Keywords: Non-thermal plasma, Gliding arc discharge, Tar reforming, Syngas, Biomass gasification
Divisions: Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science
Depositing User: Symplectic Admin
Date Deposited: 03 Jun 2021 15:35
Last Modified: 18 Jan 2023 22:36
DOI: 10.1016/j.joei.2021.06.005
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3125023