A laboratory experiment for science courses: Sedimentary microbial fuel cells

Nowadays there is a concern to improve the quality of education by including an interdisciplinary approach of concepts and their integration in the curriculum of scientific disciplines. The development of microbial fuel cells as a potential alternative for production of renewable energies gives undergraduate students the challenge of integrating interdisciplinary concepts in a hot topic of global interest as alternative energies. We present a laboratory experiment that has been part of a third-year undergraduate course in biology where students gained experience in assembling microbial fuel cells and the understanding of how they work. In this process, the students could integrate biological, biochemical, and electric concepts. In addition, the acquisition of manual skills and experimental design decisions are important for the development of future professionals.

Analytical applications of microbial fuel cells. Part I: Biochemical oxygen demand

Microbial fuel cells (MFCs) are bio-electrochemical devices, where usually the anode (but sometimes the cathode, or both) contains microorganisms able to generate and sustain an electrochemical gradient which is used typically to generate electrical power. In the more studied set-up, the anode contains heterotrophic bacteria in anaerobic conditions, capable to oxidize organic molecules releasing protons and electrons, as well as other by-products. Released protons could reach the cathode (through a membrane or not) whereas electrons travel across an external circuit originating an easily measurable direct current flow. MFCs have been proposed fundamentally as electric power producing devices or more recently as hydrogen producing devices. Here we will review the still incipient development of analytical uses of MFCs or related devices or set-ups, in the light of a non-restrictive MFC definition, as promising tools to asset water quality or other measurable parameters. An introduction to biological based analytical methods, including bioassays and biosensors, as well as MFCs design and operating principles, will also be included. Besides, the use of MFCs as biochemical oxygen demand sensors (perhaps the main analytical application of MFCs) is discussed. In a companion review (Part 2), other new analytical applications are reviewed used for toxicity sensors, metabolic sensors, life detectors, and other proposed applications.

Performance of planar and cylindrical carbon electrodes at sedimentary microbial fuel cells

This paper presents data obtained using an indigenous microbial community contained in anaerobic sediments (mud) collected from the shore of the Río de La Plata River (South America). After the sedimentary microbial fuel cells were assembled the evolution of current and power vs. time was studied. Two types of commercially available graphite materials were used as electrodes, which differ mainly in shape and size. In some experiments, an external carbon source (acetate) increased the power generation rate. The maximum power density observed in the aforementioned condition was 19.57 ± 0.35 and 8.72 ± 1.39 mW/m(2) using rod and graphite disk electrodes, respectively. The better performance of the rod electrodes can be explained, at least in part, by an enhanced rate of mass transport by radial diffusion. DGGE fingerprints were used to study the electrogenic community growing over the electrodes.

Voltamperometric discrimination of urea and melamine adulterated skimmed milk powder

Nitrogen compounds like urea and melamine are known to be commonly used for milk adulteration resulting in undesired intoxication; a well-known example is the Chinese episode occurred in 2008. The development of a rapid, reliable and economic test is of relevance in order to improve adulterated milk identification. Cyclic voltammetry studies using an Au working electrode were performed on adulterated and non-adulterated milk samples from different independent manufacturers. Voltammetric data and their first derivative were subjected to functional principal component analysis (f-PCA) and correctly classified by the KNN classifier. The adulterated and non-adulterated milk samples showed significant differences. Best results of prediction were obtained with first derivative data. Detection limits in milk samples adulterated with 1% of its total nitrogen derived from melamine or urea were as low as 85.0 mg · L(-1) and 121.4 mg · L(-1), respectively. We present this method as a fast and robust screening method for milk adulteration analysis and prevention of food intoxication.