WATER PERMEABILITY OF MEA FUEL CELL FABRICATION USING X-Y ROBOTIC SPRAYER

The fabrication of MEA is conducted using an in-house robotic sprayer machine capable of adjusting its X-Y motions. The MEA produced was analyzed for porosity; distributions pore and water flux using BET and SEM based on the water permeability methodology. The results of the MEA shown that the pore geometry of MEA has a tortuocity parameter which is greater than the MEA's thickness while the permeability coefficient parameter of water is 9.10'5 gcm'1men-1psia'1 or the tortuocity of 2. These results were then compared to the ones available from the commercial MEA

Spatio-temporal mapping of variation potentials in leaves of Helianthus annuus L. seedlings in situ using multi-electrode array.

Damaging thermal stimuli trigger long-lasting variation potentials (VPs) in higher plants. Owing to limitations in conventional plant electrophysiological recording techniques, recorded signals are composed of signals originating from all of the cells that are connected to an electrode. This limitation does not enable detailed spatio-temporal distributions of transmission and electrical activities in plants to be visualised. Multi-electrode array (MEA) enables the recording and imaging of dynamic spatio-temporal electrical activities in higher plants. Here, we used an 8 × 8 MEA with a polar distance of 450 μm to measure electrical activities from numerous cells simultaneously. The mapping of the data that were recorded from the MEA revealed the transfer mode of the thermally induced VPs in the leaves of Helianthus annuus L. seedlings in situ. These results suggest that MEA can enable recordings with high spatio-temporal resolution that facilitate the determination of the bioelectrical response mode of higher plants under stress

SURFACE AREA MICROSTRUCTURE GAS DIFFUSION LAYER AND ITS EFFECTS ON MEA FUEL CELL

The Membrane Electrode Assembly (MEA) microstructure is the path in which the input gases, namely, hydrogen and compressed air, will follow through in the process of obtaining energy from the polymer electrode membrane fuel cell (PEMFC) system. The efficiency of the conversion is dependent on the microstructure model of the materials used in making this gas diffusion layer (GDE or gas diffusion electrode (GDE). For every change in microstructure dimension, hence the electrical output obtained will be affected. Therefore, controlling the MEA microstructure in its fabrication is an imperative step in producing a good MEA. The controlling parameters used are the surface area of micro pore inside the Gas Diffusion Layer (GDL). The methods of BET are utilized in the study of surfaces, respectively; while the single stack fuel cell simulation is used in obtaining the current-voltage relationship. Results of the analyses showed that the current MEA Fuel Cell increasing as well as increasing surface area GDL. Whereas, surface area GDL is one of the parameter control to get GDL appropriate. Keywords: surface area, cell potential fuel cell I

A new approach to the spatio-temporal pattern identification in neuronal multi-electrode registrations

A lot of methods were created in last decade for the spatio-temporal analysis of multi-electrode array (MEA) neuronal data sets. All these methods were implemented starting from a channel to channel analysis, with a great computational effort and onerous spatial pattern recognition task. 
Our idea is to approach the MEA data collection from a different point of view, i.e. considering all channels simultaneously. We transform the 2D plus time MEA signal in a mono-dimensional plus time signal and elaborate it as a normal 1D signal, using the Space-Amplitude Transform method. 
This geometrical transformation is completely invertible and allows to employ very fast processing algorithms. 
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Variable selection based on entropic criterion and its application to the debris-flow triggering

We propose a new data analyzing scheme, the method of minimum entropy analysis (MEA), in this paper. New MEA provides a quantitative criterion to select relevant variables for modeling the physical system interested. Such method can be easily extended to various geophysical/geological data analysis, where many relevant or irrelevant available measurements may obscure the understanding of the highly complicated physical system like the triggering of debris-flows. After demonstrating and testing the MEA method, we apply this method to a dataset of debris-flow occurrences in Taiwan and successfully find out three relevant variables, i.e. the hydrological form factor, numbers and areas of landslides, to the triggering of observed debris-flow events due to the 1996 Typhoon Herb.Comment: 9 pages and 4 table

A Mixed Eulerian-Lagrangian Model for the Analysis of Dynamic Fracture

National Science Foundation Grant MEA 84-0065

Low Gravity Flight Complement Data

The structural and mechanical design and performance requirements for a space transportation system carrier which will accommodate essentially self-supporting low-g MEA and MAUS facilities are described. Also included are the mission requirements for the materials processing facility and MEA/MAUS experiment flight implementation reguirements