Mei, Danhua, Zhang, Peng, Duan, Gehui, Liu, Shiyun, Zhou, Ying, Fang, Zhi and Tu, Xin 
ORCID: 0000-0002-6376-0897
(2022)
CH4 reforming with CO2 using a nanosecond pulsed dielectric barrier discharge plasma.
JOURNAL OF CO2 UTILIZATION, 62.
p. 102073.
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Abstract
Non-thermal plasma reforming of CH4 with CO2 into value-added fuels and chemicals is very promising but challenging due to the low energy efficiency of the reforming process. One of the most important factors influencing energy efficiency is plasma power supply, and nanosecond pulsed power sources are gaining increasing interest in enhancing the energy efficiency of plasma chemical processes. Here, we investigate plasma-assisted CH4 reforming with CO2 using a nanosecond pulsed dielectric barrier discharge (DBD) plasma. Both electrical characteristics and reaction performance were investigated under different operating parameters, including applied voltage, total flow rate, CH4/CO2 molar ratio, and discharge length. Increasing applied voltage (from 20 to 28 kV) and discharge length (from 6 to 14 cm) enhanced the total gas conversion by 53.2% and 41.2%, respectively, but decreased the energy efficiency by 30.6% and 14.3%, respectively. The highest energy efficiency (12.4%) was obtained at an applied voltage of 20 kV, a total flow rate of 50 ml/min, a CH4/CO2 molar ratio of 1:1 and a discharge length of 10 cm, while the highest total gas conversion of 30.3% was achieved at a higher applied voltage of 26 kV and a lower total flow rate of 25 ml/min. An artificial neural network (ANN) model was developed to predict the plasma reforming process, and to investigate the relative contributions of key operating parameters to the reaction performance of this process. The results of the ANN model indicate that the CH4/CO2 molar ratio and total flow rate affect the gas conversion most significantly, while the CH4/CO2 molar ratio plays a dominant role in determining the product selectivity and energy efficiency.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Non-thermal plasmas, Dielectric barrier discharge, artificial neural, network, Nanosecond pulsed plasma |
| Divisions: | Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 30 May 2022 13:53 |
| Last Modified: | 18 Jan 2023 21:00 |
| DOI: | 10.1016/j.jcou.2022.102073 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3155696 |
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