We have studied the stability of the luminescence from porous Si in the presence of a variety of ambient gases (e.g., N2, H2, forming gas, and O2). Although the optical properties are fairly stable under most conditions, illumination in the presence of O2 causes a substantial decrease in luminescence efficiency. Infrared measurements show that the surfaces of degraded samples are oxidized. The luminescence lifetime of the degraded material is found to be substantially reduced, and the density of Si dangling bonds increases by more than two orders of magnitude, which suggests that oxidation of the surface introduces nonradiative recombination channels. These observations indicate that the electronic properties at the surface of the porous Si play a key role in obtaining efficient luminescence from this material.

Silicon is at the heart of the microelectronics revolution. Its dominance over other semiconductors is intimately tied to its superior materials and processing properties and to the tremendous base of technology that has developed around it. Another semiconductor is not likely to displace silicon as the material of choice in electronic applications. Silicon, however, is an extremely inefficient light emitter, and for this reason has not enjoyed the same level of dominance in optical applications.

GaN (Eg = ~3.4 eV) was photoelectrochemically characterized and the energetic position of its bandedges determined with respect to SHE. Electrochemical impedance spectroscopy was employed to analyze the interface, determine the space charge layer capacitance, and, subsequently obtain the flatband potential of GaN in different aqueous electrolytes. The flatband potential of GaN varied at an approximately Nernstian rate in aqueous buffer electrolytes of different pHs indicating acid-base equilibria at the interface.

Near-surface soil moisture is a critical component of land surface energy and water balance studies encompassing a wide range of disciplines. However, the processes of infiltration, runoff, and evapotranspiration in the vadose zone of the soil are not easy to quantify or predict because of the difficulty in accurately representing soil texture and hydraulic properties in land surface models. This study approaches the problem of parameterizing soils from a unique perspective based on components originally developed for operational estimation of soil moisture for mobility assessments. Estimates of near-surface soil moisture derived fiom passive (L-band) microwave remote sensing were acquired on six dates during the Monsoon '90 experiment in southeastern Arizona, and used to calibrate hydraulic properties in an offline land surface model and infer information on the soil conditions of the region. Specifically, a robust parameter estimation tool (PEST) was used to calibrate the Noah land surface model and run at very high spatial resolution across the Walnut Gulch Experimental Watershed. Errors in simulated versus observed soil moisture were minimized by adjusting the soil texture, which in turn controls the hydraulic properties through the use of pedotransfer functions. By estimating a continuous range of widely applicable soil properties such as sand, silt, and clay percentages rather than applying rigid soil texture classes, lookup tables, or large parameter sets as in previous studies, the physical accuracy and consistency of the resulting soils could then be assessed.In addition, the sensitivity of this calibration method to the number and timing of microwave retrievals is determined in relation to the temporal patterns in precipitation and soil drying. The resultant soil properties were applied to an extended time period demonstrating the improvement in simulated soil moisture over that using default or county-level soil parameters. The methodology is also applied to an independent case at Walnut Gulch using a new soil moisture product fiom active (C-band) radar imagery with much lower spatial and temporal resolution. Overall, results demonstrate the potential to gain physically meaningful soils information using simple parameter estimation with few but appropriately timed remote sensing retrievals. This study exarnines the ability of microwave remote sensing estimates of soil moisture to be used to calibrate a land surface model and, in the process, infer soil textural and hydraulic properties across spatially heterogeneous landscapes. Results also demonstrate the limitations and potential improvements in simulating soil moisture evolution using a combination of remote sensing, modeling, and parameter estimation techniques. Watershed. E r r m in simulated versus observed soil moistwe were m&mized by adjustbg the soil texae, which k ttt.m eontrols the hytlraa1-iit:propefiies though k use of pedob-msfer h e k s . By estimating a continms range of widely applicable soil prope~es swh sts sad, silt, and cl...