4.8 Article

Optimization of glucose concentration and glucose/yeast ratio in yeast microbial fuel cell using response surface methodology approach

期刊

JOURNAL OF POWER SOURCES
卷 402, 期 -, 页码 402-412

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.jpowsour.2018.09.068

关键词

ANOVA; Methylene blue; OCV; Optimization; Power density; Yeast

资金

  1. National Research Foundation of Korea (NRF) - Ministry of Science and ICT of Republic of Korea [2017H1D3A1A01013887]
  2. National Research Foundation of Korea (NRF)
  3. Ministry of the Ministry of Education (MOE) [2018R1D1A1A09036711]
  4. Korea Institute of Energy Technology Evaluation and Planning (KETEP)
  5. Ministry of Trade, Industry, and Energy (MOTIE) of the Republic of Korea [20184030202230]
  6. National Research Foundation of Korea [2017H1D3A1A01013887] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

向作者/读者索取更多资源

In this work the influence of two practical parameters, i.e. glucose concentration and glucose/yeast ratio, on performance of yeast-based microbial fuel cells (yeast-MFC) is investigated. The novel carbon felt pretreated with polyethylenimine is adopted as anode in open-air single chamber yeast-MFCs. The combination of the two parameters is optimized using response surface methodology with statistical approach. The optional presence of methylene blue as mediator is also included for comparison. Experimental dataset is initially built as reference and 4 mathematical equations are derived to predict the response regarding open circuit voltage (OCV) and maximum power density (MPD). By varying glucose concentration and glucose/yeast ratio, computed response surfaces show different responses are obtained and an optimum point exists within the range investigated. Finally, the optimized combinations for yeast-MFCs with/without mediator are predicted and response is verified in real experiment. The model tends to slightly overestimate the response, but accuracy is within confident range for both OCV and MPD. In fact, MPD obtained for the optimized yeast-MFC without mediator is 340.9 mW m(-2), 3.2% lower than model, while it is 374.4 mW m(-2), 5% lower than model, for the case including mediator. The discrepancy of OCV prediction is below 3%, making the approach reliable.

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