The GaAs solar cells with V-grooved emitters

Geometrically structured surfaces have become increasingly important to solar cell efficiency improvements and radiation tolerance. Gallium arsenide solar cells with a V-grooved front surface which demonstrate improved optical coupling and higher short-circuit current compared to planar cells were fabricated. GaAs homojunction cells were fabricated by organometallic chemical vapor deposition (OMCVD) on an n+ substrate. The V-grooves were formed on the surface with an anisotropic etch, and an n-type buffer and p-type emitter were grown by OMCVD, followed by ohmic contacts. Reflectivity measurements show significantly lower reflectance for the microgrooved cell compared to the planar structure. The short circuit current of the V-grooved solar cell is consistently higher than that of the planar controls

A V-grooved GaAs solar cell

V-grooved GaAs solar cells promise the benefits of improved optical coupling, higher short-circuit current, and increased tolerance to particle radiation compared to planar cells. A GaAs homojunction cell was fabricated by etching a V-groove pattern into an n epilayer (2.1 x 10 to the 17th power per cu cm) grown by metalorganic chemical vapor deposition (MOCVD) on an n+ substrate (2.8 x 10 to the 18th power per cu cm) and then depositing and MOCVD p epilayer (4.2 x 10 to the 18th power per cu cm). Reflectivity measurements on cells with and without an antireflective coating confirm the expected decrease in reluctance of the microgrooved cell compared to the planar structure. The short circuit current of the V-grooved solar cell was 13 percent higher than that of the planar control

Peeled film GaAs solar cells for space power

Gallium arsenide (GaAs) peeled film solar cells were fabricated, by Organo-Metallic Vapor Phase Epitaxy (OMVPE), incorporating an aluminum arsenide (AlAs) parting layer between the device structure and the GaAs substrate. This layer was selectively removed by etching in dilute hydrofloric (HF) acid to release the epitaxial film. Test devices exhibit high series resistance due to insufficient back contact area. A new design is presented which uses a coverglass superstrate for structural support and incorporates a coplanar back contact design. Devices based on this design should have a specific power approaching 700 W/Kg

Quantitative uniqueness for elliptic equations with singular lower order terms

We use a Carleman type inequality of Koch and Tataru to obtain quantitative estimates of unique continuation for solutions of second order elliptic equations with singular lower order terms. First we prove a three sphere inequality and then describe two methods of propagation of smallness from sets of positive measure.Comment: 23 pages, v2 small changes are done and some mistakes are correcte

The stability for the Cauchy problem for elliptic equations

We discuss the ill-posed Cauchy problem for elliptic equations, which is pervasive in inverse boundary value problems modeled by elliptic equations. We provide essentially optimal stability results, in wide generality and under substantially minimal assumptions. As a general scheme in our arguments, we show that all such stability results can be derived by the use of a single building brick, the three-spheres inequality.Comment: 57 pages, review articl

Large-Mass Ultra-Low Noise Germanium Detectors: Performance and Applications in Neutrino and Astroparticle Physics

A new type of radiation detector, a p-type modified electrode germanium diode, is presented. The prototype displays, for the first time, a combination of features (mass, energy threshold and background expectation) required for a measurement of coherent neutrino-nucleus scattering in a nuclear reactor experiment. The device hybridizes the mass and energy resolution of a conventional HPGe coaxial gamma spectrometer with the low electronic noise and threshold of a small x-ray semiconductor detector, also displaying an intrinsic ability to distinguish multiple from single-site particle interactions. The present performance of the prototype and possible further improvements are discussed, as well as other applications for this new type of device in neutrino and astroparticle physics (double-beta decay, neutrino magnetic moment and WIMP searches).Comment: submitted to Phys. Rev.

Nearest Neighbor Networks: clustering expression data based on gene neighborhoods

<p>Abstract</p> <p>Background</p> <p>The availability of microarrays measuring thousands of genes simultaneously across hundreds of biological conditions represents an opportunity to understand both individual biological pathways and the integrated workings of the cell. However, translating this amount of data into biological insight remains a daunting task. An important initial step in the analysis of microarray data is clustering of genes with similar behavior. A number of classical techniques are commonly used to perform this task, particularly hierarchical and K-means clustering, and many novel approaches have been suggested recently. While these approaches are useful, they are not without drawbacks; these methods can find clusters in purely random data, and even clusters enriched for biological functions can be skewed towards a small number of processes (e.g. ribosomes).</p> <p>Results</p> <p>We developed Nearest Neighbor Networks (NNN), a graph-based algorithm to generate clusters of genes with similar expression profiles. This method produces clusters based on overlapping cliques within an interaction network generated from mutual nearest neighborhoods. This focus on nearest neighbors rather than on absolute distance measures allows us to capture clusters with high connectivity even when they are spatially separated, and requiring mutual nearest neighbors allows genes with no sufficiently similar partners to remain unclustered. We compared the clusters generated by NNN with those generated by eight other clustering methods. NNN was particularly successful at generating functionally coherent clusters with high precision, and these clusters generally represented a much broader selection of biological processes than those recovered by other methods.</p> <p>Conclusion</p> <p>The Nearest Neighbor Networks algorithm is a valuable clustering method that effectively groups genes that are likely to be functionally related. It is particularly attractive due to its simplicity, its success in the analysis of large datasets, and its ability to span a wide range of biological functions with high precision.</p

Delayed self-recognition in children with autism spectrum disorder.

This study aimed to investigate temporally extended self-awareness (awareness of one’s place in and continued existence through time) in autism spectrum disorder (ASD), using the delayed self-recognition (DSR) paradigm (Povinelli et al., Child Development 67:1540–1554, 1996). Relative to age and verbal ability matched comparison children, children with ASD showed unattenuated performance on the DSR task, despite showing significant impairments in theory-of-mind task performance, and a reduced propensity to use personal pronouns to refer to themselves. The results may indicate intact temporally extended self-awareness in ASD. However, it may be that the DSR task is not an unambiguous measure of temporally extended self-awareness and it can be passed through strategies which do not require the possession of a temporally extended self-concept

Quantitative estimates of unique continuation for parabolic equations, determination of unknown time-varying boundaries and optimal stability estimates

In this paper we will review the main results concerning the issue of stability for the determination unknown boundary portion of a thermic conducting body from Cauchy data for parabolic equations. We give detailed and selfcontained proofs. We prove that such problems are severely ill-posed in the sense that under a priori regularity assumptions on the unknown boundaries, up to any finite order of differentiability, the continuous dependence of unknown boundary from the measured data is, at best, of logarithmic type