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Enhancing sensitivity of microbial fuel cell sensors for low concentration biodegradable organic matter detection: Regulation of substrate concentration, anode area and external resistance
Gao, Yangyang1,2,3; Wang, Sha1,2,3; Yin, Fengjun1,2,3; Hu, Pin2; Wang, Xingzu1,2,3; Liu, Yuan1,2,3; Liu, Hong1,2,3
2021-03-01
摘要The relatively low sensitivity is an important reason for restricting the microbial fuel cell (MFC) sensors' application in low concentration biodegradable organic matter (BOM) detection. The startup parameters, including substrate concentration, anode area and external resistance, were regulated to enhance the sensitivity of MFC sensors. The results demonstrated that both the substrate concentration and anode area were positively correlated with the sensitivity of MFC sensors, and an external resistance of 210 Omega was found to be optimal in terms of sensitivity of MFC sensors. Optimized MFC sensors had lower detection limit (1 mg/L) and higher sensitivity (Slope value of the linear regression curve was 1.02), which effectively overcome the limitation of low concentration BOM detection. The essential reason is that optimized MFC sensors had higher coulombic efficiency, which was beneficial to improve the sensitivity of MFC sensors. The main impact of the substrate concentration and anode area was to regulate the proportion between electrogens and nonelectrogens, biomass and living cells of the anode biofilm. The external resistance mainly affected the morphology structure and the proportion of living cells of the anode. This study demonstrated an effective way to improve the sensitivity of MFC sensors for low concentration BOM detection. (C) 2020 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V.
关键词Microbial fuel cell sensor High sensitivity Biodegradable organic matter Substrate concentration Anode area External resistance
DOI10.1016/j.jes.2020.08.020
发表期刊JOURNAL OF ENVIRONMENTAL SCIENCES
ISSN1001-0742
卷号101页码:227-235
通讯作者Liu, Yuan(liuyuan@cigit.ac.cn)
收录类别SCI
WOS记录号WOS:000598914600019
语种英语