671 research outputs found

    Theory of Optical Orientation in n-Type Semiconductors

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    Time resolved measurements of magnetization in n-GaAs have revealed a rich array of spin decoherence processes, and have shown that fairly long lifetimes (\sim 100 ns) can be achieved under certain circumstances. In time-resolved Faraday rotation and time-resolved Kerr rotation the evolution of the magnetization can be followed as a function of temperature, applied field, doping level and excitation level. We present a theory for the spin relaxation in n-GaAs based on a set of rate equations for two interacting thermalized subsystems of spins: localized states on donor sites and itinerant states in the conduction band. The conduction band spins relax by scattering from defects or phonons through the D'yakonov-Perel' mechanism, while the localized spins relax by interacting with phonons (when in an applied field) or through the Dzyaloshinskii-Moriya interaction. In this model, numerous features of the data, including puzzling temperature and doping dependences of the relaxation time, find an explanation.Comment: 4 pages, 2 figures; revised version has a more complete discussion of the Elliott-Yafet and spin-phonon decay mechanism

    Interpretation of organic components from positive matrix factorization of aerosol mass spectrometric data

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    International audienceThe organic aerosol (OA) dataset from an Aerodyne Aerosol Mass Spectrometer (Q-AMS) collected at the Pittsburgh Air Quality Study in September 2002 was analyzed for components with Positive Matrix Factorization (PMF). Three components ? hydrocarbon-like organic aerosol OA (HOA), a highly-oxygenated OA (OOA-I) that correlates well with sulfate, and a less-oxygenated, semi-volatile OA (OOA-II) that correlates well with nitrate and chloride ? are identified and interpreted as primary combustion emissions, aged SOA, and semivolatile, less aged SOA, respectively. The complexity of interpreting the PMF solutions of unit mass resolution (UMR) AMS data is illustrated by a detailed analysis of the solutions as a function of number of components and rotational state. A public database of AMS spectra has been created to aid this type of analysis. A sensitivity analysis with realistic synthetic data is also used to characterize the behavior of PMF for choosing the best number of factors, rotations of non-unique solutions, and the retrievability of more (or less) correlated factors. The ambient and synthetic data indicate that the variation of the PMF quality of fit parameter (Q, a normalized chi-squared metric) vs. number of factors in the solution is useful to identify the minimum number of factors, but more detailed analysis and interpretation is needed to choose the best number of factors. The maximum value of the rotational matrix is not useful for determining the best number of factors. In synthetic datasets, factors are "split" into two or more components when solving for more factors than were used in the input. Elements of the "splitting" behavior are observed in solutions of real datasets with several factors. Significant structure remains in the residual of the real dataset after physically-meaningful factors have been assigned and an unrealistic number of factors would be required to explain the remaining variance. This residual structure appears to be due to variability in the spectra of the components (especially OOA-II in this case), which is likely to be a key limit of the retrievability of components from AMS datasets using PMF and similar methods that need to assume constant component mass spectra. Methods for characterizing and dealing with this variability are needed. Values of the rotational parameter (FPEAK) near zero appear to be most appropriate for these datasets. Interpretation of PMF factors must be done carefully. Synthetic data indicate that PMF internal diagnostics and similarity to available source component spectra together are not sufficient for identifying factors. It is critical to use correlations between factor time series and external measurement time series to support factor interpretations. Components with R>0.9) with other components are suspect and should be interpreted with care. Results from this study may be useful for interpreting the PMF analysis of data from other aerosol mass spectrometers

    The influence of chemical composition and mixing state of Los Angeles urban aerosol on CCN number and cloud properties

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    International audienceThe relationship between cloud condensation nuclei (CCN) number and the physical and chemical properties of the atmospheric aerosol distribution is explored for a polluted urban data set from the Study of Organic Aerosols at Riverside I (SOAR-1) campaign conducted at Riverside, California, USA during summer 2005. The mixing state and, to a lesser degree, the average chemical composition are shown to be important parameters in determining the activation properties of those particles around the critical activation diameters for atmospherically-realistic supersaturation values. Closure between predictions and measurements of CCN number at several supersaturations is attempted by modeling a number of aerosol chemical composition and mixing state schemes of increasing complexity. It is shown that a realistic treatment of the state of mixing of the urban aerosol distribution is critical in order to eliminate model bias. Fresh emissions such as elemental carbon and small organic particles must be treated as non-activating and explicitly accounted for in the model scheme. The relative number concentration of these particles compared to inorganics and oxygenated organic compounds of limited hygroscopicity plays an important role in determining the CCN number. Furthermore, expanding the different composition/mixing state schemes to predictions of cloud droplet number concentration in a cloud parcel model highlights the dependence of cloud optical properties on the state of mixing and hygroscopic properties of the different aerosol modes, but shows that the relative differences between the different schemes are reduced compared to those from the CCN model

    Major components of atmospheric organic aerosol in southern California as determined by hourly measurements of source marker compounds

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    We report the first hourly in-situ measurements of speciated organic aerosol (OA) composition in an urban environment. Field measurements were made in southern California at the University of California–Riverside during the 2005 Study of Organic Aerosol at Riverside (SOAR), which included two separate measurement periods: a summer study (15 July–15 August) and a fall study (31 October–28 November). Hourly measurements of over 300 semivolatile and nonvolatile organic compounds were made using the thermal desorption aerosol gas chromatograph (TAG). Positive matrix factorization (PMF) was performed on a subset of these compounds to identify major components contributing to submicron (i.e., PM<sub>1</sub>) OA at the site, as measured by an aerosol mass spectrometer (AMS). PMF analysis was performed on an 11-day focus period in each season, representing average seasonal conditions during the summer and a period of urban influence during the fall. As a result of this analysis, we identify multiple types of primary and secondary OA (POA and SOA). Secondary sources contribute substantially to fine OA mass at Riverside, which commonly receives regional air masses that pass through metropolitan Los Angeles during the summer. Four individual summertime SOA components are defined, and when combined, they are estimated to contribute an average 88% of the total fine OA mass during summer afternoons according to PMF results. These sources appear to be mostly from the oxidation of anthropogenic precursor gases, with one SOA component having contributions from oxygenated biogenics. During the fall, three out of four aerosol components that contain SOA are inseparable from covarying primary emissions, and therefore we cannot estimate the fraction of total OA that is secondary in nature during the fall study. Identified primary OA components are attributed to vehicle emissions, food cooking, primary biogenics, and biomass burning aerosol. While a distinction between local and regional vehicle emissions is made, a combination of these two factors accounted for approximately 11% of observed submicron OA during both sampling periods. Food cooking operations contributed ~10% of submicron OA mass during the summer, but was not separable from SOA during the fall due to high covariance of sources. Biomass burning aerosol contributed a larger fraction of fine OA mass during the fall (~11%) than compared to summer (~7%). Primary biogenic aerosol was also identified during the summer, contributing ~1% of the OA, but not during the fall. While the contribution of both local and regional primary vehicle OA accounts for only ~11% of total OA during both seasons, gas-phase vehicle emissions likely create a substantial fraction of the observed SOA as a result of atmospheric processing

    Electromechanically active pair dynamics in a Gd-doped ceria single crystal

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    Oxygen-defective ceria, e.g. Gd-doped ceria, shows giant electromechanical properties related to a complex local rearrangement of its lattice. Although they are not entirely identified, the electroactive mechanisms arise from cation and oxygen vacancy (V-O) pairs (i.e. Ce-V-O), and the local structural elastic distortion in their surroundings. Here, we study the geometry and behaviour of Ce-V-O pairs in a grain boundary-free bulk Ce0.9Gd0.1O1.95 single crystal under an AC electric field of ca. 11 kV cm(-1). The analysis was carried out through X-ray absorption spectroscopy (XAS) techniques at the Ce L-III edge. Using Density Functional Theory (DFT) calculations, we investigated the effects of the strain on density of states and orbitals at the valence band edge. Our research indicates that electrostriction increases at low temperatures. The electromechanical strain has a structural nature and can rise by one order of magnitude, i.e., from 5 x 10(-4) at room temperature to 5 x 10(-3) at -193 degrees C, due to an increase in the population of the electrically active pairs. At a constant V-O concentration, the material can thus configure heterogeneous pairs and elastic nanodomains that are either mechanically responsive or not

    Evaluation of the volatility basis-set approach for the simulation of organic aerosol formation in the Mexico City metropolitan area

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    New primary and secondary organic aerosol modules have been added to PMCAMx, a three dimensional chemical transport model (CTM), for use with the SAPRC99 chemistry mechanism based on recent smog chamber studies. The new modeling framework is based on the volatility basis-set approach: both primary and secondary organic components are assumed to be semivolatile and photochemically reactive and are distributed in logarithmically spaced volatility bins. This new framework with the use of the new volatility basis parameters for low-NOx [low - NO subscript x] and high-NOx [high - NO subscript x] conditions tends to predict 4–6 times higher anthropogenic SOA concentrations than those predicted with older generation of models. The resulting PMCAMx-2008 was applied in Mexico City Metropolitan Area (MCMA) for approximately a week during April of 2003. The emission inventory, which uses as starting point the MCMA 2004 official inventory, is modified and the primary organic aerosol (POA) emissions are distributed by volatility based on dilution experiments. The predicted organic aerosol (OA) concentrations peak in the center of Mexico City reaching values above 40 μg [mu g] m−3 [m superscript -3]. The model predictions are compared with Aerosol Mass Spectrometry (AMS) observations and their Positive Matrix Factorization (PMF) analysis. The model reproduces both Hydrocarbon-like Organic Aerosol (HOA) and Oxygenated Organic Aerosol (OOA) concentrations and diurnal profiles. The small OA underprediction during the rush hour periods and overprediction in the afternoon suggest potential improvements to the description of fresh primary organic emissions and the formation of the oxygenated organic aerosols respectively, although they may also be due to errors in the simulation of dispersion and vertical mixing. However, the AMS OOA data are not specific enough to prove that the model reproduces the organic aerosol observations for the right reasons. Other combinations of contributions of primary, aged primary, and secondary organic aerosol production rates may lead to similar results. The model results suggest strongly that during the simulated period transport of OA from outside the city was a significant contributor to the observed OA levels. Future simulations should use a larger domain in order to test whether the regional OA can be predicted with current SOA parameterizations. Sensitivity tests indicate that the predicted OA concentration is especially sensitive to the volatility distribution of the emissions in the lower volatility bins.Seventh Framework Programme (European Commission)European UnionMEGAPOLI (Project) (Grant agreement no. 212520)Molina Center for Energy and the EnvironmentUnited States. National Oceanic and Atmospheric Administration. Office of Global Programs (Grant NA08OAR4310565)National Science Foundation (U.S.) (Grant ATM-0528634)National Science Foundation (U.S.) (Grant ATM-0528227)United States. Dept. of Energy. Office of Biological and Environmental Research. Atmospheric Science Program (DEFG0208ER64627

    Upper limits for a narrow resonance in the reaction p + p -> K^+ + (Lambda p)

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    The reaction pp -> K^+ + (Lambda p) has been measured at T_p = 1.953 GeV and \Theta = 0 deg with a high missing mass resolution in order to study the Lambda p final state interaction. Narrow S = -1 resonances predicted by bag model calculations are not visible in the missing mass spectrum. Small structures observed in a previous experiment are not confirmed. Upper limits for the production cross section of a narrow resonance are deduced for missing masses between 2058 and 2105 MeV/c^2.Comment: 8 pages, 5 figure
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