Existing sensors for gaseous species often degrade their performance because of the loss of the measurement accuracy in the presence of interferences. Thus, new sensing approaches are required with improved...
Real time determination of gases in the fuel stream of solid oxide fuel cells (SOFCs) is critical for their operation control and low operating costs. Because conventional gas sensors have gas cross-sensitivity problem, other instruments based on traditional detection principles should be utilized for multi-gas analysis. However, the complexity and cost of these instruments prohibit their uses in field-deployed SOFC units. We are developing a new generation of gas sensors, known as multivariable sensors, that have several independent responses for multi-gas detection with a single sensor. Our sensors are fabricated as nanostructures inspired by the iridescence of Morpho butterflies. Our sensor design rules coupled with machine learning tools (e.g. support vector machine, principal components analysis, hierarchical cluster analysis) provide the ability to independently quantify several gases with one sensor. The unobtrusive form factors of these sensors provide further benefits of their future implementations in SOFC systems.
Carbon nanotube (CNT) field emission (FE) has numerous potential applications including field emission displays, field electron microscopes, x-ray sources, and multiple electron beam lithography. We have developed fabrication and CNT growth processes to produce FE devices that yield stable performance at high current density. We have demonstrated stable performance for average current densities up to 0.8 A cm-2 during total charge extraction of 100 C, equivalent to 2.5 x 10 6 mAs cm-2 •
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