Use of reversible hydrides for hydrogen storage

The addition of metals or alloys whose hydrides have a high dissociation pressure allows a considerable increase in the hydrogenation rate of magnesium. The influence of temperature and hydrogen pressure on the reaction rate were studied. Results concerning the hydriding of magnesium rich alloys such as Mg2Ca, La2Mg17 and CeMg12 are presented. The hydriding mechanism of La2Mg17 and CeMg12 alloys is given

Modélisation du comportement mécanique de la neige à partir d'images microtomographiques

Characterizing the complex microstructure of snow and its mechanics is a major challenge for avalanche forecasting and hazard mapping. While the effect of environmental conditions on the snow metamorphism, which leads to numerous snow types, is fairly known, the relation between snow microstructure and mechanical properties is poorly understood because of the very fragile nature of snow. In order to decipher this relation for dry snow, this thesis presents a modeling approach of snow mechanics based on the three-dimensional microstructure of snow captured by X-ray microtomography and the properties of ice. First, in order to automatically process the microtomographic data, we take advantage of the minimization of the snow surface energy through metamorphism to efficiently binary segment grayscale images. Second, assuming an elastic brittle behavior of the ice matrix, the tensile strength of snow is modeled via a finite element approach. The model reveals an apparent pseudo-plastic behavior caused by damage, and the highly heterogenous stress distribution in the ice matrix. Third, we develop a discrete element model, accounting for grain-rearrangements and the creation/failure of inter-granular contacts. The grains, geometric input of the model, are detected in the microstructure with mechanically-relevant criteria and described as rigid clumps of spheres. The model evidences that the compression behavior of snow is mainly controlled by density but that the first stage of deformation is also sensible to the snow type. Last, the inter-granular bonds, recognized to be critical for the mechanical properties, are characterized through a new microstructural indicator, which effectively highly correlates with the simulated mechanical and physical properties.Caractériser les propriétés mécaniques de la neige est un défi majeur pour la prévision et la prédétermination du risque d’avalanche. Du fait du grand nombre de types de neige et de la difficulté à effectuer des mesures sur ce matériau très fragile, la compréhension de la relation entre la microstructure de la neige et ses propriétés mécaniques est encore incomplète. Cette thèse aborde ce problème par le biais d’une approche de modélisation mécanique basée sur la microstructure tridimensionnelle de neige obtenue par microtomographie aux rayons X. Tout d’abord, afin d’automatiser et améliorer la segmentation des images microtomographiques, un nouvel algorithme tirant profit de la minimisation de l’énergie de surface de la neige a été développé et évalué. L’image air-glace est ensuite utilisée comme entrée géométrique d’un modèle éléments finis où la glace est supposée élastique fragile. Ce modèle permet de reproduire le comportement fragile en traction et révèle le comportement pseudoplastique apparent causé par l’endommagement microscopique, ainsi que la forte hétérogénéité des contraintes dans la matrice de glace. Pour reproduire les grandes déformations impliquant le ré-arrangement de grains, un modèle par éléments discrets a ensuite été développé. Les grains sont identifiés dans la microstructure en utilisant des critères géométriques dont la pertinence mécanique a été démontrée, et décrits dans le modèle par des blocs rigides de sphères. Le comportement simulé en compression est dominé par le rôle de la densité mais révèle également des différences liées au type de neige. Enfin, pour distinguer le degré de cohésion entre les types de neige, un indicateur microstructurel a été développé et s’est avéré être fortement corrélé aux propriétés mécaniques et physiques du matériau

First-principles study of iron oxyfluorides and lithiation of FeOF

First-principles studies of iron oxyfluorides in the FeF[subscript 2] rutile framework (FeO[subscript x]F[subscript 2−x], 0≤x≤1) are performed using density functional theory (DFT) in the general gradient approximation (GGA) with a Hubbard U correction. Studies of O/F orderings reveal FeOF to be particularly stable compared to other FeO[subscript x]F[subscript 2−x] (x≠1) structures, where FeF[subscript 2]-FeOF mixing is not energetically favored. The band gap of FeF[subscript 2] is found to decrease as oxygen is substituted into its structure. The GGA + U electronic structure evolves from that of a Mott-Hubbard insulator (x=0) to a charge transfer semiconductor (x=1). Lithiation studies reveal that lithiation sites offering mixed O/F environments are the most stable. An insertion voltage plateau up to Li[subscript 0.5]FeOF on lithiation is found, in agreement with recent Li-ion battery experiments. The energetics of further lithiation with respect to conversion scenarios are discussed.United States. Dept. of Energy. Office of Basic Energy Sciences (Northeastern Center for Chemical Energy Storage Award DE-SC0001294

Effects of Bark Beetle Attacks on Forest Snowpack and Avalanche Formation – Implications for Protection Forest Management

Healthy, dense forests growing in avalanche terrain reduce the likelihood of slab avalanche release by inhibiting the formation of continuous snow layers and weaknesses in the snowpack. Driven by climate change, trends towards more frequent and severe bark beetle disturbances have already resulted in the death of millions of hectares of forest in North America and central Europe, affecting snowpack in mountain forests and potentially reducing their protective capacity against avalanches. We examined the spatial variability in snow stratigraphy, i.e., the characteristic layering of the snowpack, by repeatedly measuring vertical profiles of snow penetration resistance with a digital snow micro penetrometer (SMP) along 10- and 20-m transects in a spruce beetle-infested Engelmann spruce forest in Utah, USA. Three study plots were selected characterizing different stages within a spruce beetle outbreak cycle: non-infested/green, infested \u3e 3 years ago/gray stage, and salvage-logged. A fourth plot was installed in a non-forested meadow as the control. Based on our SMP measurements and a layer matching algorithm, we quantified the spatial variability in snow stratigraphy, and tested which forest, snow and/or meteorological conditions influenced differences between our plots using linear mixed effects models. Our results showed that spatial variability in snow stratigraphy was best explained by the percentage of canopy covering a transect (R2 = 0.71, p \u3c 0.001), and that only 14% of the variance was explained by the stage within the outbreak cycle. That is, differences between green and gray stage stands did not depend much on the reduction in needle mass, but spatial variability in snow stratigraphy increased significantly with increasing forest canopy cover. At both study plots, a more heterogeneous snow stratigraphy developed, which translates to disrupted and discontinuous snow layers and, therefore, reduced avalanche formation. We attribute this to the effect that small fine branches and twigs still present in the canopy of gray stage trees have on snow interception and unloading, and especially on canopy drip. In contrast, salvage logging that reduced the canopy cover to ∼25%, led to a spatially less variable and similar snow stratigraphy as observed in the meadow. At these two study plots, a homogeneous snow stratigraphy consisting of distinct vertical and continuous slope-parallel soft and hard snow layers including weak layers had formed, a condition which is generally more prone to avalanche release. Our findings therefore emphasize advantages of leaving dead trees in place, especially in protection forests where bark beetle populations have reached epidemic levels

Mismatch negativity generation in subjects at risk for psychosis: source analysis is more sensitive than surface electrodes in risk prediction

Background: Deficits of mismatch negativity (MMN) in patients with schizophrenia have been demonstrated many times and there is growing evidence that alterations of MMN already exist in individuals at risk for psychosis. The present study examines differences in MMN between subjects fulfilling ultra-high risk (UHR) or only basic symptoms criteria and it addresses the question, if MMN source analysis can improve prediction of transition to psychosis. Methods: The MMN to duration, frequency, and intensity deviants was recorded in 50 healthy controls and 161 individuals at risk for psychosis classified into three subgroups: only basic symptoms (n = 74), only ultra-high risk (n = 13) and persons who fulfill both risk criteria (n = 74). Based on a three-source model of MMN generation, we conducted an MMN source analysis and compared the amplitudes of surface electrodes and sources among the three groups. Results: Significant differences in MMN generation among the four groups were revealed at surface electrodes Cz and C4 (p < 0.05) and at the frontal source (p < 0.001) for duration deviant stimuli. The 15 subjects from the risk groups who subsequently developed a manifest psychosis had a significantly lower MMN amplitude at frontal source (p = 0.019) without showing significant differences at surface electrodes. Low activity at frontal MMN source increased the risk of transition to manifest disease by the factor 3.12 in UHR subjects. Conclusion: MMN activity differed significantly between subjects presenting only basic symptoms and subjects which additionally meet UHR criteria. The largest differences between groups as well as between individuals with and without transition were observed at the frontal source. The present results suggest that source analysis is more sensitive than surface electrodes in psychosis risk prediction by MMN

Can Saharan dust deposition impact snowpack stability in the French Alps?

Saharan dust deposits can turn snow covered mountains into a spectacular orange landscape. When avalanches release, a formerly buried dust layer can become apparent, possibly marking the base of the crown. This appearance may suggest a relation between avalanche release and the prior deposited dust, which found mention among recreationists and avalanche professionals alike. While dust deposition affects the absorption of solar energy altering snowpack temperatures and melt rates, to date, there is no clear scientific evidence that dust deposition can significantly modify avalanche activity. Here we investigate, using an ensemble snow cover model, the impact of dust deposition on snow properties and mechanical stability by comparing simulations with and without dust deposition for synthetic and observed dust deposition events. The study focuses on two typical avalanche situations: artificial triggering on persistent weak layers and natural release of wet-snow avalanches. We study several situations with and without dust deposition and demonstrate how sensitive the impact of dust deposition is to the deposited dust mass, the slope aspect, the elevation and the meteorological conditions following the dust deposition. The additional energy absorbed by the dust layer speeds up warming and may advance surface wetting to ease the formation of a melt-freeze crust. If the crust is buried, the phenomenon of a strong temperature gradient close to the crust may promote the formation of persistent weak layers inside the snowpack after weak layer burial. On the other hand, the melt-freeze crust may also lead to an increase of snowpack stability by redistributing the stress applied to buried weak layers. Regarding wet-snow instabilities, we show that dust deposition can advance the onset of wet-snow avalanche activity by up to one month in spring, as hypothesized in previous studies. Thus, the impact of Saharan dust deposition on snow mechanical stability can be either neutral, positive or negative, depending on the local snow and meteorological conditions. Even though not all physical processes are implemented, state-of the art snow cover models are able to mimic the speed-up of crust formation and snow instability models can point out relevant situations for avalanche forecasting.</p

Impact of water vapor diffusion and latent heat on the effective thermal conductivity of snow

Heat transport in snowpacks is understood to occur through the two processes of heat conduction and latent heat transport carried by water vapor, which are generally treated as decoupled from one another. This paper investigates the coupling between both these processes in snow, with an emphasis on the impacts of the kinetics of the sublimation and deposition of water vapor onto ice. In the case when kinetics is fast, latent heat exchanges at ice surfaces modify their temperature and therefore the thermal gradient within ice crystals and the heat conduction through the entire microstructure. Furthermore, in this case, the effective thermal conductivity of snow can be expressed by a purely conductive term complemented by a term directly proportional to the effective diffusion coefficient of water vapor in snow, which illustrates the inextricable coupling between heat conduction and water vapor transport. Numerical simulations on measured three-dimensional snow microstructures reveal that the effective thermal conductivity of snow can be significantly larger, by up to about 50 % for low-density snow, than if water vapor transport is neglected. A comparison of our numerical simulations with literature data suggests that the fast kinetics hypothesis could be a reasonable assumption for modeling heat and mass transport in snow. Lastly, we demonstrate that under the fast kinetics hypothesis the effective diffusion coefficient of water vapor is related to the effective thermal conductivity by a simple linear relationship. Under such a condition, the effective diffusion coefficient of water vapor is expected to lie in the narrow 100 % to about 80 % range of the value of the diffusion coefficient of water vapor in air for most seasonal snows. This may greatly facilitate the parameterization of water vapor diffusion of snow in models.</p