Hydrogen for electromobility : a promising energy carrier

Electromobility has received important attention in the last few years, but its perception by the public and decision makers is often limited to battery powered vehicles. Alternatives such as hydrogen fuel cells should however be taken into account, as their specific advantages (in particular short refueling times) make electro-mobility as a whole acceptable by a much broader public. Within the SCCER Mobility, PSI and ZHAW work on a novel fuel cell concept aiming at reducing the major limitation to the deployment of fuel cells: their cost

3-D simulation of water and heat transport processes in fuel cells during evaporative cooling and humidification

Evaporative cooling is a promising concept improve the efficiency and reduced costs of polymer electrolyte fuel cells (PEFCs) using modified gas diffusion layers with hydrophilic and hydrophobic lines. This concept has been demonstrated to simultaneously achieve cooling and membrane humidification in experiments. We have developed a 3-D numerical model of such an evaporative cooling cell to address remain questions from the experiments

Deep learning based classification of dynamic processes in time-resolved X-ray tomographic microscopy

Time-resolved X-ray tomographic microscopy is an invaluable technique to investigate dynamic processes in 3D for extended time periods. Because of the limited signal-to-noise ratio caused by the short exposure times and sparse angular sampling frequency, obtaining quantitative information through post-processing remains challenging and requires intensive manual labor. This severely limits the accessible experimental parameter space and so, prevents fully exploiting the capabilities of the dedicated time-resolved X-ray tomographic stations. Though automatic approaches, often exploiting iterative reconstruction methods, are currently being developed, the required computational costs typically remain high. Here, we propose a highly efficient reconstruction and classification pipeline (SIRT-FBP-MS-D-DIFF) that combines an algebraic filter approximation and machine learning to significantly reduce the computational time. The dynamic features are reconstructed by standard filtered back-projection with an algebraic filter to approximate iterative reconstruction quality in a computationally efficient manner. The raw reconstructions are post-processed with a trained convolutional neural network to extract the dynamic features from the low signal-to-noise ratio reconstructions in a fully automatic manner. The capabilities of the proposed pipeline are demonstrated on three different dynamic fuel cell datasets, one exploited for training and two for testing without network retraining. The proposed approach enables automatic processing of several hundreds of datasets in a single day on a single GPU node readily available at most institutions, so extending the possibilities in future dynamic X-ray tomographic investigations

Widespread Occurrence of Pesticides in Organically Managed Agricultural Soils—the Ghost of a Conventional Agricultural Past?

Pesticides are applied in large quantities to agroecosystems worldwide. To date, few studies assessed the occurrence of pesticides in organically managed agricultural soils, and it is unresolved whether these pesticide residues affect soil life. We screened 100 fields under organic and conventional management with an analytical method containing 46 pesticides (16 herbicides, 8 herbicide transformation products, 17 fungicides, seven insecticides). Pesticides were found in all sites, including 40 organic fields. The number of pesticide residues was two times and the concentration nine times higher in conventional compared to organic fields. Pesticide number and concentrations significantly decreased with the duration of organic management. Even after 20 years of organic agriculture, up to 16 different pesticide residues were present. Microbial biomass and specifically the abundance of arbuscular mycorrhizal fungi, a widespread group of beneficial plant symbionts, were significantly negatively linked to the amount of pesticide residues in soil. This indicates that pesticide residues, in addition to abiotic factors such as pH, are a key factor determining microbial soil life in agroecosystems. This comprehensive study demonstrates that pesticides are a hidden reality in agricultural soils, and our results suggest that they have harmful effects on beneficial soil life

Fuel Cell Modeling and Simulations

Fundamental and phenomenological models for cells, stacks, and complete systems of PEFC and SOFC are reviewed and their predictive power is assessed by comparing model simulations against experiments. Computationally efficient models suited for engineering design include the (1+1) dimensionality approach, which decouples the membrane in-plane and through-plane processes, and the volume-averaged-method (VAM) that considers only the lumped effect of pre-selected system components. The former model was shown to capture the measured lateral current density inhomogeneities in a PEFC and the latter was used for the optimization of commercial SOFC systems. State Space Modeling (SSM) was used to identify the main reaction pathways in SOFC and, in conjunction with the implementation of geometrically well- defined electrodes, has opened a new direction for the understanding of electrochemical reactions. Furthermore, SSM has advanced the understanding of the COpoisoning- induced anode impedance in PEFC. Detailed numerical models such as the Lattice Boltzmann (LB) method for transport in porous media and the full 3-D Computational Fluid Dynamics (CFD) Navier-Stokes simulations are addressed. These models contain all components of the relevant physics and they can improve the understanding of the related phenomena, a necessary condition for the development of both appropriate simplified models as well as reliable technologies. Within the LB framework, a technique for the characterization and computer- reconstruction of the porous electrode structure was developed using advanced pattern recognition algorithms. In CFD modeling, 3-D simulations were used to investigate SOFC with internal methane steam reforming and have exemplified the significance of porous and novel fractal channel distributors for the fuel and oxidant delivery, as well as for the cooling of PEFC. As importantly, the novel concept has been put forth of functionally designed, fractal-shaped fuel cells, showing promise of significant performance improvements over the conventional rectangular shaped units. Thermo-economic modeling for the optimization of PEFC is finally addressed

Operando Properties of Gas Diffusion Layers: Saturation and Liquid Permeability

Polymer electrolyte fuel cells (PEFC) require a sophisticated water management to operate efficiently, especially at high current densities which are needed to reach system cost targets. The description of the complicated two-phase water transport remains a challenge in PEFC models and requires experimental validation on various length scales. In this work, operando X-ray tomographic microscopy (XTM) with scan times of 10 s was used to depict the liquid water at defined conditions at a technically relevant cell temperature of 80°C. Cells with Toray TGP-H-060 gas diffusion layer (GDL) with microporous layer (MPL) and different rib width were operated with different feed gas humidifications (under- and oversaturated) and current densities between 0.75 to 3.0 A/cm2. Based on the quantification of the local and average saturation, the distribution of water cluster size is analyzed. Different categories of the water cluster connectivity are defined and quantified. The analysis is complemented with numerical simulations of the permeability in the liquid phase of the GDL that is correlated to saturation for the different GDL domains. The numerical simulations of the pressure drop of liquid water flow from the catalyst layer toward the gas channels in channel-rib repetition units allows for conclusions on cluster growth mechanisms