Search Results (4)

Gas fermentation is an upcoming technology to convert gaseous substrates into value-added products using autotrophic microorganisms. The hydrogen-oxidizing bacteria Cupriavidus necator efficiently uses CO₂ as its sole carbon source, H₂ as electron donor and O₂ as electron acceptor. Surplus CO₂ is stored in microbial storage material poly-(R)-3-hydroxybutyrate. O₂ supply is the most critical parameter for growth and poly-(R)-3-hydroxybutyrate formation. A narrow O₂ optimum between ~0.2 and ~4 mg/L was previously reported. Here, a standard benchtop bioreactor was redesigned for autotrophic growth of C. necator on explosive mixtures of CO₂, H₂ and O₂. The bioreactor was equipped with mass flow control units and O₂ and CO₂ sensors. A controller for automated gas dosage based on a mathematical model including gas mass transfer, gas consumption and sensor response time was developed. Dissolved O₂ concentrations were adjusted with high precision to 1, 2 and 4% O₂ saturation (0.4, 0.8 and 1.5 mg/L dissolved O₂, respectively). In total, up to 15 g/L cell dry weight were produced. Residual biomass formation was 3.6 ± 0.2 g/L under all three O₂ concentrations. However, poly-(R)-3-hydroxybutyrate content was 71, 77 and 58% of the cell dry weight with 1, 2 and 4% dissolved O₂, respectively. Full article

Electrochemical impedance spectroscopy (EIS) is an important electrochemical technique that is used to detect changes and ongoing processes in a given material. The main challenge of EIS is interpreting the collected measurements, which can be performed in several ways. This article focuses on the electrical equivalent circuit (EEC) approach and uses grammatical evolution to automatically construct an EEC that produces an AC response that corresponds to one obtained by the measured electrochemical process(es). For fitting purposes, synthetic measurements and data from measurements in a realistic environment were used. In order to be able to faithfully fit realistic data from measurements, a new circuit element (ZARC) had to be implemented and integrated into the SPICE simulator, which was used for evaluating EECs. Not only is the presented approach able to automatically (i.e., with almost no user input) produce a more than satisfactory EEC for each of the datasets, but it also can also generate completely new EEC configurations. These new configurations may help researchers to find some new, previously overlooked ongoing electrochemical processes. Full article

Reliable electrical and thermal energy supplies are basic requirements for modern societies and their food supply. Stand-alone stationary power generators based on solid oxide fuel cells (SOFC) represent an attractive solution to the problems of providing the energy required in both rural communities and in rurally-based industries such as those of the agricultural industry. The great advantages of SOFC-based systems are high efficiency and high fuel flexibility. A wide range of commercially available fuels can be used with no or low-effort pre-treatment. In this study, a design process for stand-alone system consisting of a reformer unit and an SOFC-based power generator is presented and tested. An adequate agreement between the measured and simulated values for the gas compositions after a reformer unit is observed with a maximum error of 3 vol% (volume percent). Theoretical degradation free operation conditions determined by employing equilibrium calculations are identified to be steam to carbon ratio (H₂O/C) higher 0.6 for auto-thermal reformation and H₂O/C higher 1 for internal reforming. The produced gas mixtures are used to fuel large planar electrolyte supported cells (ESC). Current densities up to 500 mA/cm² at 0.75 V are reached under internal reforming conditions without degradation of the cells anode during the more than 500 h long-term test run. More detailed electrochemical analysis of SOFCs fed with different fuel mixtures showed that major losses are caused by gas diffusion processes. Full article

Identification of ongoing processes in solid oxide fuel cells (SOFC) enables both optimizing the operating environment and prolonging the lifetime of SOFC. The Levenberg–Marquardt algorithm (LMA) is commonly used in the characterization of unknown electrochemical processes within SOFC by extracting equivalent electrical circuit (EEC) parameter values from electrochemical impedance spectroscopy (EIS) data. LMA is an iteration optimization algorithm regularly applied to solve complex nonlinear least square (CNLS) problems. The LMA convergence can be boosted by the application of an ordinary limit strategy, which avoids the occurrence of off-limit values during the fit. However, to additionally improve LMA descent properties and to discard the problem of a poor initial parameters choice, it is necessary to modify the ordinary limit strategy. In this work, we designed a new automatic update (i.e., adaptive) limit strategy whose purpose is to reduce the impact of a poor initial parameter choice. Consequently, the adaptive limit strategy was embedded in a newly developed EIS fitting engine. To demonstrate that the new adaptive (vs. ordinary) limit strategy is superior, we used it to solve several CNLS problems. The applicability of the adaptive limit strategy was also validated by analyzing experimental EIS data collected by using industrial-scale SOFCs. Full article