779 research outputs found

    Coplanar back contacts for thin silicon solar cells

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    The type of coplanar back contact solar cell described was constructed with interdigitated n(+) and p(+) type regions on the back of the cell, such that both contacts are made on the back with no metallization grid on the front. This cell construction has several potential advantages over conventional cells for space use namely, convenience of interconnects, lower operating temperatures and higher efficiency due to the elimination of grid shadowing. However, the processing is more complex, and the cell is inherently more radiation sensitive. The latter problem can be reduced substantially by making the cells very thin (approximately 50 micrometers). Two types of interdigitated back contact cells are possible, the types being dependent on the character of the front surface. The front surface field cell has a front surface region that is of the same conductivity type as the bulk but is more heavily doped. This creates an electric field at the surface which repels the minority carriers. The tandem junction cell has a front surface region of a conductivity type that is opposite to that of the bulk. The junction thus created floats to open circuit voltage on illumination and injects carriers into the bulk which then can be collected at the rear junction. For space use, the front surface field cell is potentially more radiation resistant than the tandem junction cell because the flow of minority carriers (electrons) into the bulk will be less sensitive to the production of recombination centers, particularly in the space charge region at the front surface

    Thin cells for space

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    Research and pilot line production efforts directed towards the fabrication of high efficiency ultrathin silicon solar cells (50 micrometers) are reported. Conventional ultrathin cells with air-mass-zero (AM0) efficiencies exceeding 14% and coplanar back contact cells with AM0 efficiencies up to 11.7% were developed. The primary mechanisms limiting efficiency were determined in both types of cells, and they are discussed within the context of further improving efficiency. Results of pilot line production of conventional ultrathin cells are also presented. Average AM0 efficiencies of 12% were readily achieved for 2000 cell production runs

    Potential shift in tree species composition after interaction of fire and drought in the Central Alps

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    The future trajectory of forest ecosystems under climate change is heavily debated. Previous studies on the impacts of climate change on forest ecosystems have focused mainly on direct effects of altered climatic conditions, whereas interactions with disturbance events have been largely neglected. The aim of this study is to explore interactions of drought with fire disturbance and to assess their effects on tree species shifts in the European Central Alps. Tree recruitment after a stand replacing wildfire in the Rhone valley, Switzerland, was measured along an altitudinal temperature moisture gradient. Recruitment was more successful in pioneer species (Betula pendula, Populus tremula and Salix appendiculata) than in pre-fire stand forming (PFSF) species (Larix decidua, Picea abies and Pinus sylvestris). Seedling and sapling density was not related to fire intensity, but it correlated with the distance to the forest edge in PFSF species. The window of opportunity for seedling establishment was short (1-2years), and moisture deficit was the main limiting factor for tree recruitment at lower altitudes. We suggest that prolonged drought periods, as projected under continued global warming, will further aggravate tree recruitment success after fire disturbance at low altitudes of the Central Alps and may eventually lead to a shift from PFSF species to either more drought-tolerant species or to forest-free vegetatio

    Detection, Analysis and Clinical Validation of Chromosomal Aberrations by Multiplex Ligation-Dependent Probe Amplification in Chronic Leukemia

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    Current diagnostic screening strategies based on karyotyping or fluorescent in situ hybridization (FISH) for detection of chromosomal abnormalities in chronic lymphocytic leukemia (CLL) are laborious, time-consuming, costly, and have limitations in resolution. Multiplex ligation-dependent probe amplification (MLPA) can simultaneously detect copy number changes of multiple loci in one simple PCR reaction, making it an attractive alternative to FISH. To enhance the clinical robustness and further harness MLPA technology for routine laboratory operations, we have developed and validated a protocol for comprehensive, automatic data analysis and interpretation. A training set of 50 normal samples was used to establish reference ranges for each individual probe, for the calling of statistically significant copy number changes. The maximum normal ranges of 2 and 3 standard deviations (SD) are distributed between 0.82 and 1.18 (Mean Ā± 2SD, 95% CI, Pā€Š=ā€Š0.05), and between 0.73 and 1.27 (Mean Ā± 3SD, 99% CI, Pā€Š=ā€Š0.01), respectively. We found an excellent correlation between MLPA and FISH with 93.6% concordance (P<0.0001) from a testing cohort of 100 clinically suspected CLL cases. MLPA analyses done on 94/100 patients showed sensitivity and specificity of 94.2% and 92.9%, respectively. MLPA detected additional copy number gains on 18q21.1 and chromosome 19, and novel micro-deletions at 19q13.43 and 19p13.2 loci in six samples. Three FISH-failed samples were tested positive by MLPA, while three 13q- cases with a low percentage of leukemia cells (7%, 12% and 19%) were not detected by MLPA. The improved CLL MLPA represents a high-throughput, accurate, cost-effective and user-friendly platform that can be used as a first-line screening test in a clinical laboratory

    The Chemical Translation Serviceā€”a web-based tool to improve standardization of metabolomic reports

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    Summary: Metabolomic publications and databases use different database identifiers or even trivial names which disable queries across databases or between studies. The best way to annotate metabolites is by chemical structures, encoded by the International Chemical Identifier code (InChI) or InChIKey. We have implemented a web-based Chemical Translation Service that performs batch conversions of the most common compound identifiers, including CAS, CHEBI, compound formulas, Human Metabolome Database HMDB, InChI, InChIKey, IUPAC name, KEGG, LipidMaps, PubChem CID+SID, SMILES and chemical synonym names. Batch conversion downloads of 1410 CIDs are performed in 2.5 min. Structures are automatically displayed

    A LEED structural analysis of the Co(100) surface

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    The structure of the clean Co(1010) surface has been analysed by LEED. Application of a recently developed computational scheme reveals the prevalence of the termination A in which the two topmost layers exhibit a narrow spacing of 0.62 ƅ, corresponding to a 12.8(Ā±0.5)% contraction with respect to the bulk value, while the spacing between the second and third layer is slightly expanded by 0.8(Ā±0.2)%

    Fully Automated Optimization of Robotā€Based MOF Thin Film Growth via Machine Learning Approaches

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    Metalā€“organic frameworks (MOFs), have emerged as ideal class of materials for the identification of structureā€“property relationships and for the targeted design of multifunctional materials for diverse applications. While the powder form is most common, for the integration of MOFs into devices, typically thin films of surface anchored MOFs (SURMOFs), are required. Although the quality of SURMOFs emerging from layer-by-layer approaches is impressive, previous works revealed that the optimum growth conditions are very different between different types of MOFs and different substrates. Furthermore, the choice of appropriate synthesis conditions (e.g., solvents, modulators, concentrations, immersion times) is crucial for the growth process and needs to be adjusted for different substrates. Machine learning (ML) approaches show great promise for multi-parameter optimization problems such as the above discussed growth conditions for SURMOF on a particular substrate. Here, this work presents an ML-based approach allowing to quickly identify optimized growth conditions for HKUST-I SURMOFs with high crystallinity and uniform orientation. This process can subsequently be used to optimize growth on other types of substrates. In addition, an analysis of the results allows to gain further insights into the factors governing the growth of MOF thin films
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