Publications

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The transient transport of electrolytes in thermally-activated batteries is studied using electron probe micro-analysis (EPMA), demonstrating the robust capability of EPMA as a useful tool for studying and quantifying mass transport within porous materials, particularly in difficult environments where classical flow measurements are challenging. By tracking the mobility of bromine and potassium ions from the electrolyte stored within the separator into the lithium silicon anode and iron disulfide cathode, we are able to quantify the transport mechanisms and physical properties of the electrodes including permeability and tortuosity. Due to the micron to submicron scale porous structure of the initially dry anode, a fast capillary pressure driven flow is observed into the anode from which we are able to set a lower bound on the permeability of 10-1 mDarcy. The transport into the cathode is diffusion-limited because the cathode originally contained some electrolyte before activation. Using a transient one-dimensional diffusion model, we estimate the tortuosity of the cathode electrode to be 2.8 ± 0.8.

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We are developing computational models to elucidate the expansion and dynamic filling process of a polyurethane (PMDI) foam used to encapsulate electronic components or to produce lightweight structural parts. The polyurethane of interest is a chemically blown foam, where carbon dioxide is produced via the reaction of water, a blowing agent, and isocyanate. Here, we take a careful look at the evolution of the bubble sizes during blowing. This information will help the development of subgrid models to predict bubble formation, growth, coalescence and collapse, drainage, and, hence, eventually the development of engineering models to predict foam expansion into a mold. Close-up views of bubbles at a transparent wall of a narrow, temperature-controlled channel are recorded during the foaming reaction and analyzed with image processing. Because these bubbles are pressed against the wall, the bubble sizes in the last frames after the expansion has stopped are compared to scanning electron microscope (SEM) images of the interior of some of the cured samples to determine if the presence of the wall significantly changes the bubble sizes. In addition, diffusing wave spectroscopy (DWS) is used to determine the average bubble sizes across the width of a similar channel as the bubbles change with time. DWS also gives information about microstructural changes as bubbles rearrange upon bubble collapse or coalescence. In this paper we conclude qualitatively that the bubble size distribution is heavily dependent on the formulation of foam being tested, temperature, the height in the foam bar, the proximity to a wall, and the degree of over-packing.

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Temperature monitoring is essential in automation, mechatronics, robotics and other dynamic systems. Wireless methods which can sense multiple temperatures at the same time without the use of cables or slip-rings can enable many new applications. A novel method utilizing small permanent magnets is presented for wirelessly measuring the temperature of multiple points moving in repeatable motions. The technique utilizes linear least squares inversion to separate the magnetic field contributions of each magnet as it changes temperature. The experimental setup and calibration methods are discussed. Initial experiments show that temperatures from 5 to 50 °C can be accurately tracked for three neodymium iron boron magnets in a stationary configuration and while traversing in arbitrary, repeatable trajectories. This work presents a new sensing capability that can be extended to tracking multiple temperatures inside opaque vessels, on rotating bearings, within batteries, or at the tip of complex endeffectors.

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We are studying PMDI polyurethane with a fast catalyst, such that filling and polymerization occur simultaneously. The foam is over-packed to tw ice or more of its free rise density to reach the density of interest. Our approach is to co mbine model development closely with experiments to discover new physics, to parameterize models and to validate the models once they have been developed. The model must be able to repres ent the expansion, filling, curing, and final foam properties. PMDI is chemically blown foam, wh ere carbon dioxide is pr oduced via the reaction of water and isocyanate. The isocyanate also re acts with polyol in a competing reaction, which produces the polymer. A new kinetic model is developed and implemented, which follows a simplified mathematical formalism that decouple s these two reactions. The model predicts the polymerization reaction via condensation chemis try, where vitrification and glass transition temperature evolution must be included to correctly predict this quantity. The foam gas generation kinetics are determined by tracking the molar concentration of both water and carbon dioxide. Understanding the therma l history and loads on the foam due to exothermicity and oven heating is very important to the results, since the kinetics and ma terial properties are all very sensitive to temperature. The conservation eq uations, including the e quations of motion, an energy balance, and thr ee rate equations are solved via a stabilized finite element method. We assume generalized-Newtonian rheology that is dependent on the cure, gas fraction, and temperature. The conservation equations are comb ined with a level set method to determine the location of the free surface over time. Results from the model are compared to experimental flow visualization data and post-te st CT data for the density. Seve ral geometries are investigated including a mock encapsulation part, two configur ations of a mock stru ctural part, and a bar geometry to specifically test the density model. We have found that the model predicts both average density and filling profiles well. However, it under predicts density gradients, especially in the gravity direction. Thoughts on m odel improvements are also discussed.

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