Heteroepitaxial InP solar cells on Si and GaAs substrates

The characteristics of InP cells processed from thin layers of InP heteroepitaxially grown on GaAs, on silicon with an intervening GaAs layer, and on GaAs with intervening Ga(x)In(1-x)As layers are described, and the factors affecting cell efficiency are discussed. Under 10 MeV proton irradiations, the radiation resistances of the heteroepitaxial cells were superior to that of homoepitaxial InP cells. The superior radiation resistance is attributed to the high dislocation densities present in the heteroepitaxial cells

New directions in InP solar cell research

Recent research efforts representing new directions in InP solar cell research are reviewed. These include heteroepitaxial growth on silicon and gallium arsenide substrates, V-grooved cells, large area high efficiency cells, and surface passivation. Improvements in heteroepitaxial cell efficiency are described together with processing of 19.1 percent, 4 sq cm cells. Recommendations are made for improvements in processing leading to increased efficiencies

The effect of the low Earth orbit environment on space solar cells

The results of a space flight experiment designed to provide reference cell standards for photovoltaic measurements as well as to investigate the solar spectrum and the effect of long-term exposure of solar cells to the space environment are presented. This experiment, the Advanced Photovoltaic Experiment (APEX), was launched into low Earth orbit as part of the Long Duration Exposure Facility in 1984 and retrieved 69 months later. APEX contained over 150 solar cells of a wide variety of materials, designs and coverglasses. Data on cell performance was recorded for the first year-on-orbit

Ruminative thought style and depressed mood.

Recent research has suggested that the measure most commonly used to assess rumination, the Response Style Questionnaire (RSQ; L. D. Butler & S. Nolen-Hoeksema, 1994), may be heavily biased by depressive symptoms, thereby restricting the scope of research exploring this construct. This article offers a broader conceptualization of rumination, which includes positive, negative, and neutral thoughts as well as past and future-oriented thoughts. The first two studies describe the development and evaluation of the Ruminative Thought Style Questionnaire (RTS), a psychometrically sound measure of the general tendency to ruminate. Further, the scale is comprised of a single factor and shows high internal consistency, suggesting that rumination does encompasses the factors mentioned. The final study involved a longitudinal diary investigation of rumination and mood over time. Results suggest that the RTS assesses a related, but separate, construct than does the RSQ. RTS scores predicted future depressed mood beyond the variance accounted for by initial depressed mood whereas RSQ scores did not. The implications of these results and directions for future research are discussed

Effect of dislocations on properties of heteroepitaxial InP solar cells

The apparently unrelated phenomena of temperature dependency, carrier removal and photoluminescence are shown to be affected by the high dislocation densities present in heteroepitaxial InP solar cells. Using homoepitaxial InP cells as a baseline, it is found that the relatively high dislocation densities present in heteroepitaxial InP/GaAs cells lead to increased volumes of dVoc/dt and carrier removal rate and substantial decreases in photoluminescence spectral intensities. With respect to dVoc/dt, the observed effect is attributed to the tendency of dislocations to reduce Voc. Although the basic cause for the observed increase in carrier removal rate is unclear, it is speculated that the decreased photoluminescence intensity is attributable to defect levels introduced by dislocations in the heteroepitaxial cells

Radiation damage and annealing in large area n+/p/p+ GaAs shallow homojunction solar cells

Annealing of radiation damage was observed for the first time in VPE-grown, 2- by 2-cm, n+/p/p+ GaAs shallow homojunction solar cells. Electrical performance of several cells was determined as a function of 1-MeV electron fluence in the range of 10 to the 13th power to 10 to the 15th power e-/sq cm and as a function of thermal annealing time at various temperatures. Degradation of normalized power output after a fluence of 10 to the 15th power 1-MeV electrons/sq cm ranged from a low of 24 to 31 percent of initial maximum power. Normalized short circuit current degradation was limited to the range from 10 to 19 percent of preirradiated values. Thermal annealing was carried out in a flowing nitrogen gas ambient, with annealing temperatures spanning the range from 125 to 200 C. Substantial recovery of short circuit current was observed at temperatures as low as 175 C. In one case improvement by as much as 10 percent of the postirradiated value was observed. The key features of these cells are their extremely thin emitter layers (approxmately 0.05 micrometers), the absence of any Al sub xGd sub 1-x As passivating window layer, and their fabrication by vapor phase epitaxy

Normative data on cognitive measures of depression.

The assessment of cognition and cognitive change is important for case conceptualization, monitoring the efficacy of specific interventions, and evaluating treatment outcome in cognitive-behavioral therapy. Unfortunately, a paucity of normative data exists on cognitive measures used for psychotherapy outcome research in depression, and little information is available to guide a practitioner\u27s understanding of the magnitude and clinical significance of a patient\u27s cognitive change. This article presents normative data on 6 self-report instruments that assess negative and positive automatic thoughts, hopelessness, cognitive biases and errors, and dysfunctional attitudes. Normative data were derived from studies published from the date of inception of a given cognitive index to the year 2000. Recommendations for the use of these normative data are provided

Active Sampling-based Binary Verification of Dynamical Systems

Nonlinear, adaptive, or otherwise complex control techniques are increasingly relied upon to ensure the safety of systems operating in uncertain environments. However, the nonlinearity of the resulting closed-loop system complicates verification that the system does in fact satisfy those requirements at all possible operating conditions. While analytical proof-based techniques and finite abstractions can be used to provably verify the closed-loop system's response at different operating conditions, they often produce conservative approximations due to restrictive assumptions and are difficult to construct in many applications. In contrast, popular statistical verification techniques relax the restrictions and instead rely upon simulations to construct statistical or probabilistic guarantees. This work presents a data-driven statistical verification procedure that instead constructs statistical learning models from simulated training data to separate the set of possible perturbations into "safe" and "unsafe" subsets. Binary evaluations of closed-loop system requirement satisfaction at various realizations of the uncertainties are obtained through temporal logic robustness metrics, which are then used to construct predictive models of requirement satisfaction over the full set of possible uncertainties. As the accuracy of these predictive statistical models is inherently coupled to the quality of the training data, an active learning algorithm selects additional sample points in order to maximize the expected change in the data-driven model and thus, indirectly, minimize the prediction error. Various case studies demonstrate the closed-loop verification procedure and highlight improvements in prediction error over both existing analytical and statistical verification techniques.Comment: 23 page

Cryptic persistence and loss of local endemism in Lake Constance charr subject to anthropogenic disturbance

In the welcome circumstance that species believed extinct are rediscovered, it is often the case that biological knowledge acquired before the presumed extinction is limited. Efforts to address these knowledge gaps, in particular to assess the taxonomic integrity and conservation status of such species, can be hampered by a lack of genetic data and scarcity of samples in museum collections. Here, we present a proof-of-concept case study based on a multidisciplinary data evaluation approach to tackle such problems. The approach was developed after the rediscovery, 40 years after its presumed extinction, of the enigmatic Lake Constance deep-water charr Salvelinus profundus. Targeted surveys led to the capture of further species and additional sympatric normal charr, Salvelinus cf. umbla. Since the lake had been subject to massive stocking in the past, an evaluation of the genetic integrity of both extant forms was called for in order to assess possible introgression. A two-step genomic approach was developed based on restriction site associated DNA (RAD). Diagnostic population genomic (single nucleotide polymorphism [SNP]) data were harvested from contemporary samples and used for RNA bait design to perform target capture in DNA libraries of archival scale material, enabling a comparison between extant and historic samples. Furthermore, life history traits and morphological data for both extant forms were gathered and compared with historical data from the past 60–120 years. While extant deep-water charr matched historical deep-water specimens in body shape, gill raker count, and growth rates, significant differences were discovered between historical and extant normal charr. These resulted were supported by genomic analyses of contemporary samples, revealing the two extant forms to be highly divergent. The results of population assignment tests suggest that the endemic deep-water charr persisted in Lake Constance during the eutrophic phase, but not one of the historical genomic samples could be assigned to the extant normal charr taxon. Stocking with non-endemic charr seems to be the most likely reason for these changes. This proof-of-concept study presents a multidisciplinary data evaluation approach that simultaneously tests population genomic integrity and addresses some of the conservation issues arising from rediscovery of a species characterized by limited data availability.publishedVersio

What do cyclists need to see to avoid single-bicycle crashes?

The number of single-bicycle crash victims is substantial in countries with high levels of cycling. To study the role of visual characteristics of the infrastructure, such as pavement markings, in single-bicycle crashes, a study in two steps was conducted. In Study 1, a questionnaire study was conducted among bicycle crash victims (n = 734). Logistic regression was used to study the relationship between the crashes and age, light condition, alcohol use, gaze direction and familiarity with the crash scene. In Study 2, the image degrading and edge detection method (IDED-method) was used to investigate the visual characteristics of 21 of the crash scenes. The results of the studies indicate that crashes, in which the cyclist collided with a bollard or road narrowing or rode off the road, were related to the visual characteristics of bicycle facilities. Edge markings, especially in curves of bicycle tracks, and improved conspicuity of bollards are recommended. Statement of Relevance: Elevated single-bicycle crash numbers are common in countries with high levels of cycling. No research has been conducted on what cyclists need to see to avoid this type of crash. The IDED-method to investigate crash scenes is new and proves to be a powerful tool to quantify 'visual accessibility'. © 2011 Taylor & Francis