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End date: 2012 × Start date: 2010 × Version: publishedVersion × Publisher: Bristol : IOP Publishing ×

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Now showing 1 - 4 of 4
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    Atomically controlled CVD processing of group IV semiconductors for ultra-large-scale integrations
    (Bristol : IOP Publishing, 2012) Murota, Junichi; Sakuraba, Masao; Tillack, Bernd
    One of the main requirements for ultra-large-scale integrations (ULSIs) is atomic-order control of process technology. Our concept of atomically controlled processing is based on atomic-order surface reaction control by CVD. By ultraclean low-pressure CVD using SiH4 and GeH4 gases, high-quality low-temperature epitaxial growth of Si1−xGex (100) (x=0–1) with atomically flat surfaces and interfaces on Si(100) is achieved. Self-limiting formation of 1–3 atomic layers of group IV or related atoms in the thermal adsorption and reaction of hydride gases on Si1-xGex (100) are generalized based on the Langmuir-type model. By the Si epitaxial growth on top of the material already-formed on Si(100), N, B and C atoms are confined within about a 1 nm thick layer. In Si cap layer growth on the P atomic layer formed on Si1−xGex (100), segregation of P atoms is suppressed by using Si2H6 instead of SiH4 at a low temperature of 450 °C. Heavy C atomic-layer doping suppresses strain relaxation as well as intermixing between Si and Ge at the Si1−xGex/Si heterointerface. It is confirmed that higher carrier concentration and higher carrier mobility are achieved by atomic-layer doping. These results open the way to atomically controlled technology for ULSIs.
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    Extreme fire events are related to previous-year surface moisture conditions in permafrost-underlain larch forests of Siberia
    (Bristol : IOP Publishing, 2012) Forkel, Matthias; Thonicke, Kirsten; Beer, Christian; Cramer, Wolfgang; Bartalev, Sergey; Schmullius, Christiane
    Wildfires are a natural and important element in the functioning of boreal forests. However, in some years, fires with extreme spread and severity occur. Such severe fires can degrade the forest, affect human values, emit huge amounts of carbon and aerosols and alter the land surface albedo. Usually, wind, slope and dry air conditions have been recognized as factors determining fire spread. Here we identify surface moisture as an additional important driving factor for the evolution of extreme fire events in the Baikal region. An area of 127 000 km2 burned in this region in 2003, a large part of it in regions underlain by permafrost. Analyses of satellite data for 2002–2009 indicate that previous-summer surface moisture is a better predictor for burned area than precipitation anomalies or fire weather indices for larch forests with continuous permafrost. Our analysis advances the understanding of complex interactions between the atmosphere, vegetation and soil, and how coupled mechanisms can lead to extreme events. These findings emphasize the importance of a mechanistic coupling of soil thermodynamics, hydrology, vegetation functioning, and fire activity in Earth system models for projecting climate change impacts over the next century.
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    Comparing climate projections to observations up to 2011
    (Bristol : IOP Publishing, 2012) Rahmstorf, Stefan; Foster, Grant; Cazenave, Anny
    We analyse global temperature and sea-level data for the past few decades and compare them to projections published in the third and fourth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). The results show that global temperature continues to increase in good agreement with the best estimates of the IPCC, especially if we account for the effects of short-term variability due to the El Niño/Southern Oscillation, volcanic activity and solar variability. The rate of sea-level rise of the past few decades, on the other hand, is greater than projected by the IPCC models. This suggests that IPCC sea-level projections for the future may also be biased low.
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    A statistically predictive model for future monsoon failure in India
    (Bristol : IOP Publishing, 2012) Schewe, Jacob; Levermann, Anders
    Indian monsoon rainfall is vital for a large share of the world's population. Both reliably projecting India's future precipitation and unraveling abrupt cessations of monsoon rainfall found in paleorecords require improved understanding of its stability properties. While details of monsoon circulations and the associated rainfall are complex, full-season failure is dominated by large-scale positive feedbacks within the region. Here we find that in a comprehensive climate model, monsoon failure is possible but very rare under pre-industrial conditions, while under future warming it becomes much more frequent. We identify the fundamental intraseasonal feedbacks that are responsible for monsoon failure in the climate model, relate these to observational data, and build a statistically predictive model for such failure. This model provides a simple dynamical explanation for future changes in the frequency distribution of seasonal mean all-Indian rainfall. Forced only by global mean temperature and the strength of the Pacific Walker circulation in spring, it reproduces the trend as well as the multidecadal variability in the mean and skewness of the distribution, as found in the climate model. The approach offers an alternative perspective on large-scale monsoon variability as the result of internal instabilities modulated by pre-seasonal ambient climate conditions.