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In this study, a methodology for electrodeposition of nickel nanostructures on carbon felt was developed on the base of pulse plating technique. Different in size, shape, and distribution, Ni-island nanostructures were deposited varying the potential, current, pulse duration, and cycle reiteration. The biocompatibility and nontoxicity of the newly created materials toward Candida melibiosica yeast cells was proven. The prepared Ni-nanomodified carbon felts were investigated as anodes in a two-chamber mediatorless yeast−biofuel cell. Maximum power density values of 720 and 390 mW/m2 were achieved with the electrodes modified under galvanostatic and potentiostatic conditions, respectively, against 36 mW/m2 for the nonmodified ones. The better biofuel cell performance obtained with the Ni-modified electrodes is assigned to an improved electron transfer.

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The commonly used parameters characterizing fuel cells and in particular microbial fuel cells (MFCs) electrical performance are open circuit voltage (OCV), maximum power, and short circuit current. These characteristics are usually obtained from polarization and power curves. In the present study, the expanded uncertainties of operational characteristics for yeast‐based fuel cell were evaluated and the main sources of uncertainty were determined. Two approaches were used: the uncertainty budget building for sources uncertainty estimation and a statistical treatment of identical MFCs results – for operational characteristics uncertainty calculation. It was found that in this particular bioelectrochemical system the major factor contributing to operational characteristics uncertainties was the electrodes' resistance. The operational characteristics uncertainties were decreased from 19 to 13% for OCV, from 42 to 14% for maximal power, and from 46 to 13% for short circuit current with the usage of electrodes with resistance in the interval 6–7 Ω. The described approaches can be used for operational characteristics expanded uncertainties calculation of all types of fuel cells using data from polarization measurements.