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  Simulation and optimization of the post plasma-catalytic system for toluene degradation by a hybrid ANN and NSGA-II method

Chang, T., Lu, J., Shen, Z., Huang, Y., Lu, D., Wang, X., et al. (2019). Simulation and optimization of the post plasma-catalytic system for toluene degradation by a hybrid ANN and NSGA-II method. Applied Catalysis B: Environmental, 244, 107-119. doi:10.1016/j.apcatb.2018.11.025.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0003-EC39-4 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-EC3A-3
Genre: Journal Article

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 Creators:
Chang, Tian1, Author
Lu, Jiaqi1, Author
Shen, Zhenxing1, Author
Huang, Yu1, Author
Lu, Di1, Author
Wang, Xin2, Author              
Cao, Junji1, Author
Morent, Rino1, Author
Affiliations:
1external, ou_persistent22              
2Multiphase Chemistry, Max Planck Institute for Chemistry, Max Planck Society, ou_1826290              

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 Abstract: In this study, a post-non-thermal plasma (NTP)-catalytic system was developed for the removal of toluene over a series of MnCoOx/γ-Al2O3 catalysts. The addition of the MnCoOx/γ-Al2O3 catalysts markedly promoted the toluene removal efficiency, COx yield, CO2 yield and energy yield (EY) compared with the plasma alone system. The 5 wt% MnCoOx/γ-Al2O3 catalyst exhibited the best reaction performance, which could be attributed to the reducibility and surface active oxygen species of the catalyst. With artificial neural network (ANN), the effects of experimental parameters on the reaction performance of toluene degradation were modeled and analyzed; for this analysis, four parameters were considered, namely, discharge power, initial concentration of toluene, flow rate, and relative humidity. The results indicated that the predicted results fitted well with the experimental results. The discharge power was the most significant factor for the toluene removal efficiency and COx yield, whereas the EY was the most influenced by the gas flow rate. A multi-objective optimization model was proposed to determine optimal experimental parameters, which was then solved using the non-dominating sorting genetic algorithm II (NSGA-II). The results revealed that the Pareto front obtained from the hybrid ANN and NSGA-II method provided a series of feasible and optimal process parameters for the post-NTP-catalytic system. This hybrid method also served as an effective tool to select process parameters according to application conditions and preferences.

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Language(s): eng - English
 Dates: 2019
 Publication Status: Published in print
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Title: Applied Catalysis B: Environmental
  Abbreviation : Appl. Catal. B Environ.
Source Genre: Journal
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Publ. Info: Amsterdam : Elsevier
Pages: - Volume / Issue: 244 Sequence Number: - Start / End Page: 107 - 119 Identifier: ISSN: 0926-3373
CoNE: https://pure.mpg.de/cone/journals/resource/954928540173