Effect of operating conditions on current density distribution and high frequency resistance in a segmented PEM fuel cell

Understanding losses in polymer electrolyte membrane fuel cells, in the form of ohmic and mass transport, is of great importance to their commercialization. In this study, we use a spatially resolved cell consisting of 49 segments to measure the local current density distribution and high frequency resistance (HFR). A parametric study is used to investigate the effects of cell voltage, inlet relative humidity and flow rate and configuration using a three-channel serpentine flow field. We found that as the cell voltage decreased, the current density increased, while the HFR decreased. However, at a low cell voltage of 200 mV, we found the HFR to be higher than that at 500 mV. This increase is attributed to the increased electro-osmotic drag. This trend is independent of the flow configuration. Further, we found that the effect of the inlet relative humidity on the HFR highly depends on the flow configurations. Finally, a sharp decrease in the current density at some specific bend segments was observed, which correlates with lower OCV values and higher HFR values at this position.     

Impact of Brownian motion on the particle settling in molten metals

Understanding the settling behavior of nanoparticles in molten metals/alloys is important as it will aid in achieving uniform dispersions of reinforcement particles in metal matrix nanocomposites. Uniform dispersions are necessary to activate the Orowan strengthening mechanism, which can increase yield strength without significant diminishment of ductility. In this work, an analytical model of particle size effects on settling is described that takes into account both deterministic Stokes’ law and stochastic Brownian motion. The model shows a clear transitional behavior where settling velocity follows Stokes’ law for large particles and then drops to zero for small particles implying that Brownian motion predominates. It indicated that, in the Brownian motion regime, where the discrete nature of the liquid must be considered, the random motion imparted by unbalanced collisions can overwhelm the motions normally imposed by forces such as gravity, viscous drag, and thermal/concentration gradients.     

Performance optimization of polymer electrolyte membrane fuel cells using the Nelder-Mead algorithm

The direct-search simplex method for function optimization has been adapted to performance optimization of polymer electrolyte membrane fuel cells (PEMFCs). The established method is strongly application oriented and uses only experimentally determined data for optimization. It is not restricted to discrete parameters optimums and does not require the use of third-party software or computational resources. Hence, it is easy to implement in fuel cell testing stations. The optimization consists of finding, for a given fuel cell load, an optimum set of values of the 7 fuel cell operating parameters: the fuel cell temperature, the reactants' stoichiometric ratios, the reactants' inlet relative humidity, and the reactants' outlet pressures, resulting in the highest fuel cell performance. The performance is measured using a scalar function of the operating parameters and the load and can be defined according to needs.Two PEMFC performance functions: the fuel cell voltage and the system-related fuel cell efficiency were optimized using the procedure for practically sized PEMFC stacks of two designs. With respect to the nominal operating conditions defined as optimal for each stack design by its manufacturer, the gains from the optimization procedure were up to over 12% and up to over 7% for the stack voltage and efficiency, respectively. The validation of the procedure involved 5 stack specimens and four laboratories and consistent results were obtained.     

A Multiplexed Four Channel On-Line Iodine Monitor

Abstract

A robust autonomous system is described for the spectrophotometric determination of aqueous elemental iodine in multiple flowing process streams. The quantitative methodology uses characteristic absorbance at 460 nm, corrected for baseline drift using absorbance at 600 nm. Linear dynamic ranges of 0.2 - 25 mg/L, 0.4 - 45 mg/L, and 2 - 250 mg/L have been attained using path lengths of 1 cm, 5 cm, and 10 cm respectively. The multiplexed iodine monitor has proven capable of continuous operation for periods of up to eighteen months.     

Interleukin‐4‐Clicked Surfaces Drive M2 Macrophage Polarization

Driving macrophage (M?) polarization into the M2 phenotype provides potential against inflammatory diseases. Interleukin‐4 (IL‐4) promotes polarization into the M2‐M? phenotype, but its systemic use is constrained by dose‐limiting toxicity. Consequently, we developed IL‐4‐decorated surfaces aiming at sustained and localized activity. IL‐4 muteins were generated by genetic code expansion; Lys42 was replaced by unnatural amino acids (uAAs). Both muteins showed cell‐stimulation ability and binding affinity to IL4Rα similar to those of wt‐IL‐4. Copper‐catalyzed (CuAAC) and copper‐free strain‐promoted (SPAAC) 1,3‐dipolar azide–alkyne cycloadditions were used to site‐selectively anchor IL‐4 to agarose surfaces. These surfaces had sustained IL‐4 activity, as demonstrated by TF‐1 cell proliferation and M2, but not M1, polarization of M‐CSF‐generated human M?. The approach provides a blueprint for the engineering of cytokine‐activated surfaces profiled for sustained and spatially controlled activity.     

Universitärer Forschungscluster „Sustainable Technologies in Metal Production and Processing” (STMP)

Foundation of a university research cluster — Co-operation along the value creation chain from raw materials to components — Evidence of joint performance offers — Utilization of synergies — Integration of Christian Doppler Laboratories — Flexible arrangement of co-operations and networks     

Multilevel surrogate modeling of an amine scrubbing process for CO2capture

Surrogate models provide a powerful method for simplifying calculations within complex simulations. While surrogate models are broadly applied within chemical engineering, little research exists investigating the level of surrogacy's impact on a simplified process model. In this work, artificial neural networks (ANN) and Kriging models are used as surrogate models at the process, process unit, and thermodynamic levels for a CO₂ amine scrubbing process. The surrogated models are evaluated against an Aspen Plus simulation for accuracy, convergence behavior, computational cost, and ability to extrapolate. The thermodynamic and process unit models can better handle discontinuous, non-smooth behavior, and convergence issues in the surrogated truth model, but poor conditioning in the final system of equations results in a lower accuracy and convergence rate than the process level surrogate. Beyond model accuracy, availability of diverse data, intended re-usability, and the desired outputs must be considered when selecting a level of abstraction.     

Crystallization of poly(ethylene terephthalate)/polycarbonate blends. I. Unreinforced systems

The crystallization and transition temperatures of poly(ethylene terephthalate) (PET) in blends with polycarbonate (PC) is considered using thermal analysis. Additives typically used in commercial polyester blends, transesterification inhibitor and antioxidant, are found to enhance the crystallization rate of PET. Differential scanning calorimetry (DSC) reveals two glass transition temperatures in PET/PC blends, consistent with an immiscible blend. Optical microscopy observations are also consistent with an immiscible blend. Small shifts observed in the T_g of each component may be due to interactions between the phases. The degree of crystallinity of PET in PET/PC blends is significantly depressed for high PC contents. Also, in blends with PC content greater than 60 wt %, two distinct crystallization exotherms are observed in dynamic crystallization from the melt. The isothermal crystallization kinetics of PET, PET modified with blend additives, and PET in PET/PC blends have been evaluated using DSC and the data analyzed using the Avrami model. The crystallization of PET in these systems is found to deviate from the Avrami prediction in the later stages of crystallization. Isothermal crystallization data are found to superimpose when plotted as a function of time divided by crystallization half-time. A weighted series Avrami model is found to describe the crystallization of PET and PET/PC blends during all stages of crystallization. © 1996 John Wiley & Sons, Inc.     

Technology Assessment on Renewable Raw Materials: Potentials and Risks of the Use of Starches

Starch as a renewable raw material for chemical/industrial uses has a long tradition. In terms of quantity, starch ranks third behind wood and vegetable oils. In the medium term, this position will be maintained, if not improved. The volume of renewable raw materials used for fuel is even greater and expected to increase in the medium term. By means of a technology assessment on chemical/industrial and energy uses of renewable raw materials, it shall be demonstrated where the specific potentials and risks of starch use can be found. Among others, the following aspects are considered: energy and CO₂ balance sheets, biodegradability and competiveness. Under the headings of „saving of raw materials (degree of self-sufficiency)”︁, „area required (reduction of surpluses)”︁, „employment effects”︁, „contribution to CO₂ reduction”︁ and „need for subsidies”︁, medium-term (up to 2005) potential use of starch in Germany is studied relative to use of renewable raw materials in total.