Annealing of Gadolinium-Doped Ceria (GDC) Films Produced by the Aerosol Deposition Method

Solid oxide fuel cells need a diffusion barrier layer to protect the zirconia-based electrolyte if a cobalt-containing cathode material like lanthanum strontium cobalt ferrite (LSCF) is used. This protective layer must prevent the direct contact and interdiffusion of both components while still retaining the oxygen ion transport. Gadolinium-doped ceria (GDC) meets these requirements. However, for a favorable cell performance, oxide ion conducting films that are thin yet dense are required. Films with a thickness in the sub-micrometer to micrometer range were produced by the dry room temperature spray-coating technique, aerosol deposition. Since commercially available GDC powders are usually optimized for the sintering of screen printed films or pressed bulk samples, their particle morphology is nanocrystalline with a high surface area that is not suitable for aerosol deposition. Therefore, different thermal and mechanical powder pretreatment procedures were investigated and linked to the morphology and integrity of the sprayed films. Only if a suitable pretreatment was conducted, dense and well-adhering GDC films were deposited. Otherwise, low-strength films were formed. The ionic conductivity of the resulting dense films was characterized by impedance spectroscopy between 300 °C and 1000 °C upon heating and cooling. A mild annealing occurred up to 900 °C during first heating that slightly increased the electric conductivity of GDC films formed by aerosol deposition

Impedance analysis of electrolyte processes in a solid oxide cell

Electrochemical impedance spectroscopy and the distribution of relaxation times are powerful tools to study polarization processes in solid oxide cells (SOC). Commonly the measured polarization resistance is solely attributed to polarization phenomena in the electrodes whereas the electrolyte is assumed to act as purely ohmic series resistance. In this study an electrolyte supported SOC is investigated by impedance spectroscopy from the nominal operating temperature range of 700–900°C down to temperatures as low as 350°C. At such low temperatures the dielectric polarization of the electrolyte is shifted into the accessible frequency range, providing access to additional processes which are deconvoluted and quantified. It is discussed to which extent the additional layers like gadolinia doped ceria diffusion barrier and electrode layers influence the electrolyte processes as grain and grain boundary

Comparison of a solid oxide cell with nickel/gadolinium‐doped ceria fuel electrode during operation with hydrogen/steam and carbon monoxide/carbon dioxide

Solid oxide cells (SOCs) offer the possibility to operate on hydrogen/steam (H$_2$/H$_2$O), carbon monoxide/carbon dioxide (CO/CO$_2$), and mixtures thereof in the fuel cell as well as in the electrolyzer mode. In this study, the electrochemical processes in an electrolyte-supported SOC exhibiting a La$_w$ Sr$_x$ Co$_y$ Fe$_z$ O$_{(3-δ)}$ air electrode and a nickel/gadolinium-doped ceria (Ni/CGO) fuel electrode (FE) were analyzed by electrochemical impedance spectroscopy, and the subsequent impedance data analysis by the distribution of relaxation times for CO/CO$_2$ fuel mixtures. A physicochemical equivalent circuit model was fitted to the measured spectra. With the help of the extracted parameters, a zero-dimensional direct current cell model was parametrized to simulate the current-voltage behavior of the cell. This approach, previously implemented for H$_2$/H$_2$O fuel mixtures, is extended toward CO/CO$_2$ fuels. It will be shown that the same model – with adapted parameters for the FE – can be applied. A comparison of measured and simulated current-voltage curves showed an excellent agreement for both fuels and operating modes (solid oxide fuel cell/solid oxide electrolyzer cell). Simulations reveal that there is nearly no performance difference between H$_2$O and CO$_2$ electrolysis for the electrolyte-supported cell with Ni/CGO FE in comparison to an anode-supported cell with Ni/yttria-stabilized zirconia FE

Software JimenaE allows efficient dynamic simulations of Boolean networks, centrality and system state analysis

The signal modelling framework JimenaE simulates dynamically Boolean networks. In contrast to SQUAD, there is systematic and not just heuristic calculation of all system states. These specific features are not present in CellNetAnalyzer and BoolNet. JimenaE is an expert extension of Jimena, with new optimized code, network conversion into different formats, rapid convergence both for system state calculation as well as for all three network centralities. It allows higher accuracy in determining network states and allows to dissect networks and identification of network control type and amount for each protein with high accuracy. Biological examples demonstrate this: (i) High plasticity of mesenchymal stromal cells for differentiation into chondrocytes, osteoblasts and adipocytes and differentiation-specific network control focusses on wnt-, TGF-beta and PPAR-gamma signaling. JimenaE allows to study individual proteins, removal or adding interactions (or autocrine loops) and accurately quantifies effects as well as number of system states. (ii) Dynamical modelling of cell–cell interactions of plant Arapidopsis thaliana against Pseudomonas syringae DC3000: We analyze for the first time the pathogen perspective and its interaction with the host. We next provide a detailed analysis on how plant hormonal regulation stimulates specific proteins and who and which protein has which type and amount of network control including a detailed heatmap of the A.thaliana response distinguishing between two states of the immune response. (iii) In an immune response network of dendritic cells confronted with Aspergillus fumigatus, JimenaE calculates now accurately the specific values for centralities and protein-specific network control including chemokine and pattern recognition receptors

Practices to support co-design processes: A case-study of co-designing a program for children with parents with a mental health problem in the Austrian region of Tyrol

Forms of collaborative knowledge production, such as community-academic partnerships (CAP), have been increasingly used in health care. However, instructions on how to deliver such processes are lacking. We aim to identify practice ingredients for one element within a CAP, a 6-month co-design process, during which 26 community- and 13 research-partners collaboratively designed an intervention programme for children whose parent have a mental illness. Using 22 published facilitating and hindering factors for CAP as the analytical framework, eight community-partners reflected on the activities which took place during the co-design process. From a qualitative content analysis of the data, we distilled essential practices for each CAP factor. Ten community- and eight research-partners revised the results and co-authored this article. We identified 36 practices across the 22 CAP facilitating or hindering factors. Most practices address more than one factor. Many practices relate to workshop design, facilitation methods, and relationship building. Most practices were identified for facilitating ‘trust among partners’, ‘shared visions, goals and/or missions’, ‘effective/frequent communication’, and ‘well-structured meetings’. Fewer practices were observed for ‘effective conflict resolution’, ‘positive community impact’ and for avoiding ‘excessive funding pressure/control struggles’ and ‘high burden of activities’. Co-designing a programme for mental healthcare is a challenging process that requires skills in process management and communication. We provide practice steps for delivering co-design activities. However, practitioners may have to adapt them to different cultural contexts. Further research is needed to analyse whether co-writing with community-partners results in a better research output and benefits for participants

Software JimenaE allows efficient dynamic simulations of Boolean networks, centrality and system state analysis

The signal modelling framework JimenaE simulates dynamically Boolean networks. In contrast to SQUAD, there is systematic and not just heuristic calculation of all system states. These specific features are not present in CellNetAnalyzer and BoolNet. JimenaE is an expert extension of Jimena, with new optimized code, network conversion into different formats, rapid convergence both for system state calculation as well as for all three network centralities. It allows higher accuracy in determining network states and allows to dissect networks and identification of network control type and amount for each protein with high accuracy. Biological examples demonstrate this: (i) High plasticity of mesenchymal stromal cells for differentiation into chondrocytes, osteoblasts and adipocytes and differentiation-specific network control focusses on wnt-, TGF-beta and PPAR-gamma signaling. JimenaE allows to study individual proteins, removal or adding interactions (or autocrine loops) and accurately quantifies effects as well as number of system states. (ii) Dynamical modelling of cell–cell interactions of plant Arapidopsis thaliana against Pseudomonas syringae DC3000: We analyze for the first time the pathogen perspective and its interaction with the host. We next provide a detailed analysis on how plant hormonal regulation stimulates specific proteins and who and which protein has which type and amount of network control including a detailed heatmap of the A.thaliana response distinguishing between two states of the immune response. (iii) In an immune response network of dendritic cells confronted with Aspergillus fumigatus, JimenaE calculates now accurately the specific values for centralities and protein-specific network control including chemokine and pattern recognition receptors

Investigation of the β-pinene photooxidation by OH in the atmosphere simulation chamber SAPHIR

Beside isoprene, monoterpenes are the non-methane volatile organic compounds (VOC) with the highest global emission rates. Due to their high reactivity towards OH, monoterpenes can dominate the radical chemistry of the atmosphere in forested areas. In the present study the photochemical degradation mechanism of β-pinene was investigated in the Jülich atmosphere simulation chamber SAPHIR. The focus of this study is on the OH budget in the degradation process. Therefore the SAPHIR chamber was equipped with instrumentation to measure radicals (OH, HO2, RO2), the total OH reactivity, important OH precursors (O3, HONO, HCHO), the parent VOC beta-pinene, its main oxidation products, acetone and nopinone, and photolysis frequencies. All experiments were carried out under low NOx conditions (≤ 2 ppb) and at atmospheric beta-pinene concentrations (≤ 5 ppb) with and without addition of ozone. For the investigation of the OH budget, the OH production and destruction rates were calculated from measured quantities. Within the limits of accuracy of the instruments, the OH budget was balanced in all β-pinene oxidation experiments. However, even though the OH budget was closed, simulation results from the Master Chemical Mechanism 3.2 showed that the OH production and destruction rates were underestimated by the model. The measured OH and HO2 concentrations were underestimated by up to a factor of two whereas the total OH reactivity was slightly overestimated because of the poor reproduction of the measured nopinone by the model by up to a factor of three. A new, theory-derived first-generation product distribution by Vereecken and Peeters was able to reproduce the measured nopinone time series and the total OH reactivity. Nevertheless the measured OH and HO2 concentrations remained underestimated by the numerical simulations. These observations together with the fact that the measured OH budget was closed suggest the existence of unaccounted sources of HO2