Hydrogenation of Magnesium Nickel Boride for Reversible Hydrogen Storage

We report that a ternary magnesium nickel boride (MgNi_(2.5)B_2) mixed with LiH and MgH_2 can be hydrogenated reversibly forming LiBH_4 and Mg_2NiH_4 at temperatures below 300 °C. The ternary boride was prepared by sintering a mechanically milled mixture of MgB_2 and Ni precursors at 975 °C under inert atmosphere. Hydrogenation of the ternary, milled with LiH and MgH_2, was performed under 100 to 160 bar H_2 at temperatures up to 350 °C. Analysis using X-ray diffraction, Fourier transform infrared, and ^(11)B magic angle spinning NMR confirmed that the ternary boride was hydrogenated forming borohydride anions. The reaction was reversible with hydrogenation kinetics that improved over three cycles. This work suggests that there may be other ternary or higher order boride phases useful for reversible hydrogen storage

Validation of northern latitude Tropospheric Emission Spectrometer stare ozone profiles with ARC-IONS sondes during ARCTAS: sensitivity, bias and error analysis

We compare Tropospheric Emission Spectrometer (TES) versions 3 and 4, V003 and V004, respectively, nadir-stare ozone profiles with ozonesonde profiles from the Arctic Intensive Ozonesonde Network Study (ARCIONS, http://croc.gsfc.nasa.gov/arcions/ during the Arctic Research on the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) field mission. The ozonesonde data are from launches timed to match Aura's overpass, where 11 coincidences spanned 44° N to 71° N from April to July 2008. Using the TES "stare" observation mode, 32 observations are taken over each coincidental ozonesonde launch. By effectively sampling the same air mass 32 times, comparisons are made between the empirically-calculated random errors to the expected random errors from measurement noise, temperature and interfering species, such as water. This study represents the first validation of high latitude (>70°) TES ozone. We find that the calculated errors are consistent with the actual errors with a similar vertical distribution that varies between 5% and 20% for V003 and V004 TES data. In general, TES ozone profiles are positively biased (by less than 15%) from the surface to the upper-troposphere (~1000 to 100 hPa) and negatively biased (by less than 20%) from the upper-troposphere to the lower-stratosphere (100 to 30 hPa) when compared to the ozonesonde data. Lastly, for V003 and V004 TES data between 44° N and 71° N there is variability in the mean biases (from −14 to +15%), mean theoretical errors (from 6 to 13%), and mean random errors (from 9 to 19%)

Mathematical modelling of tumour response in primary breast cancer.

Although breast cancer is perceived to be relatively chemosensitive, cytotoxic drug therapy only leads to cure in the adjuvant setting. In advanced disease, primary resistance and inadequate cell kill may be important in determining the lack of a durable response to cytotoxics, but for an individual patient's tumour there is no consistent way of determining the importance of these two factors. An adaptation of Skipper's log cell kill model of tumour response to chemotherapy was applied to serial tumour measurements of 46 locally advanced primary breast carcinomas undergoing neoadjuvant chemotherapy. Assuming a log-normal distribution of errors in the clinically measured volumes, the model produced, for each tumour separately, in vivo estimates of proportional cell kill, initial resistance and tumour doubling times during therapy. After 4 weeks' treatment, these data could then be used to predict subsequent tumour volumes with good accuracy. In addition, for the 13 tumours that became operable after the neoadjuvant chemotherapy, there was a significant association between the final volume as predicted by the model and the final pathological volume (P < 0.05). This approach could be usefully employed to determine those tumours that are primarily resistant to the treatment regimen, permitting changes of therapy to more effective drugs at a time when the tumour is clinically responding but destined to progress

Impact of the assimilation of ozone from the Tropospheric Emission Spectrometer on surface ozone across North America

We examine the impact of assimilating ozone observations from the Tropospheric Emission Spectrometer (TES) on North American surface ozone abundances in the GEOS-Chem model in August 2006. The assimilation reduces the negative bias in the modeled free tropospheric ozone, which enhances the ozone flux into the boundary layer. Surface ozone abundances increased by as much as 9 ppb in western North America and by less than 2 ppb in the southeast, resulting in a total background source of ozone of 20-40 ppb. The enhanced ozone in the model reduced the model bias with respect to surface ozone observations in the western USA, but exacerbated it in the east. This increase in the bias in the boundary layer in the east, despite the agreement between the assimilation and ozonesonde measurements in the free troposphere, suggests errors in the ozone sources or sinks or in boundary layer mixing in the model. © 2009

Technical Note: Impact of nonlinearity on changing the a priori of trace gas profiles estimates from the Tropospheric Emission Spectrometer (TES)

International audienceNon-linear optimal estimates of atmospheric profiles from the Tropospheric Emission Spectrometer (TES) may contain a priori information that varies geographically, which is a confounding factor in the analysis and physical interpretation of an ensemble of profiles. A common strategy is to transform these profile estimates to a common prior using a linear operation thereby facilitating the interpretation of profile variability. However, this operation is dependent on the assumption of not worse than moderate non-linearity near the solution of the non-linear estimate. We examines the robustness of this assumption when exchanging the prior by comparing atmospheric retrievals from the Tropospheric Emission Spectrometer processed with a uniform prior with those processed with a variable prior and converted to a uniform prior following the non-linear retrieval. We find that linearly converting the prior following a non-linear retrieval is shown to have a minor effect on the results as compared to a non-linear retrieval using a uniform prior when compared to the expected total error, with less than 10% of the change in the prior ending up as unbiased fluctuations in the profile estimate results