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Mechanistic aspect of electrochemical signal in a microbial fuel cell-based biosensor.

机译:基于微生物燃料电池的生物传感器中电化学信号的机械方面。

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摘要

Due to contamination of effluent from industrial plants by toxic chemicals, the development of rapid and continuous water toxicity monitoring is an important issue. Complex influent flows into wastewater treatment plants (WWTPs) alter the routine operational condition and reduce the efficiency of the treatment process. The objective of this research is to develop a real-time device for monitoring WWTPs. A microbial fuel cell (MFC)-based biosensor is designed to detect the electrochemical signals in response of disruption by contaminants. A MFC-based biosensor can serve as a water quality emergency alarm for preventing harsh water impact. The activated sludge utilized in the experiment has DO concentration 2 ∼ 6 mg/L; MLSS ranged from 2500 ∼ 3000 mg/L; C: N: P ratio of 100: 5: 1 in nearly 99% COD removal efficiency. In the experiment, a current is generated from substrates in the synthetic wastewater instead of from the microbial metabolism. Of the metals tested Cu(II) contributes the largest current changes relative to metal ion concentration. The redox reaction of substrates is eliminated as a cause. A possible cause with divalent metals is a concentration gradient in which pH provides the most current variation. There is no significant influence of current change corresponding to pH in trivalent metals. Some secondary factors, such as ionic strength and species distribution, are also discussed. Furthermore, theoretical proton concentration variation is calculated and compared with experimental data to understand the difference between an idea model and realistic situation. The experimental data show two orders of magnitude differences from theoretical values. It is assumed that other impacts, such as sludge interaction and membrane transportation, may influence signal variation. In addition, the current variation curve equation fitted mathematically is not only an index to differentiate metal species, but also can be used to calculate concentration of metal ions. However, the accuracy of detection needs to be enhanced.
机译:由于工业厂房的废水被有毒化学物质污染,因此快速而连续的水毒性监测的发展是一个重要的问题。复杂的进水流入废水处理厂(WWTP)会改变常规操作条件并降低处理过程的效率。这项研究的目的是开发一种用于监测污水处理厂的实时设备。基于微生物燃料电池(MFC)的生物传感器设计用于检测电化学信号,以响应污染物的破坏。基于MFC的生物传感器可以用作水质紧急警报,以防止强烈的水冲击。实验中使用的活性污泥的溶解氧浓度为2〜6 mg / L。 MLSS范围为2500〜3000 mg / L; C:N:P比例为100:5:1,可去除近99%的COD。在实验中,电流是从合成废水中的底物而不是微生物代谢中产生的。在测试的金属中,相对于金属离子浓度,Cu(II)贡献最大的电流变化。消除了底物的氧化还原反应。二价金属的可能原因是浓度梯度,其中pH提供了最大的电流变化。三价金属中对应于pH的电流变化没有明显影响。还讨论了一些次要因素,例如离子强度和物质分布。此外,计算理论质子浓度变化并将其与实验数据进行比较,以了解概念模型与实际情况之间的差异。实验数据表明与理论值有两个数量级的差异。假设其他影响(例如污泥相互作用和膜运输)可能会影响信号变化。另外,数学上拟合的电流变化曲线方程不仅是区分金属种类的指标,还可以用于计算金属离子的浓度。但是,需要提高检测精度。

著录项

  • 作者

    Lei, Hao-Yun.;

  • 作者单位

    University of Delaware.;

  • 授予单位 University of Delaware.;
  • 学科 Engineering Environmental.;Chemistry Analytical.;Biology Microbiology.
  • 学位 M.S.
  • 年度 2015
  • 页码 175 p.
  • 总页数 175
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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