Pressure Evolution of a Field Induced Fermi Surface Reconstruction and of the Neel Critical Field in CeIn3

We report high-pressure skin depth measurements on the heavy fermion material CeIn3 in magnetic fields up to 64 T using a self-resonant tank circuit based on a tunnel diode oscillator. At ambient pressure, an anomaly in the skin depth is seen at 45 T. The field where this anomaly occurs decreases with applied pressure until approximately 1.0 GPa, where it begins to increase before merging with the antiferromagnetic phase boundary. Possible origins for this transport anomaly are explored in terms of a Fermi surface reconstruction. The critical magnetic field at which the Neel ordered phase is suppressed is also mapped as a function of pressure and extrapolates to the previous ambient pressure measurements at high magnetic fields and high pressure measurements at zero magnetic field.Comment: 15 pages, 5 figure

Fermi Surface of Alpha-Uranium at Ambient Pressure

We have performed de Haas-van Alphen measurements of the Fermi surface of alpha-uranium single crystals at ambient pressure within the alpha-3 charge density wave (CDW) state from 0.020 K - 10 K and magnetic fields to 35 T using torque magnetometry. The angular dependence of the resulting frequencies is described. Effective masses were measured and the Dingle temperature was determined to be 0.74 K +/- 0.04 K. The observation of quantum oscillations within the alpha-3 CDW state gives new insight into the effect of the charge density waves on the Fermi surface. In addition we observed no signature of superconductivity in either transport or magnetization down to 0.020 K indicating the possibility of a pressure-induced quantum critical point that separates the superconducting dome from the normal CDW phase.Comment: 11 pages, 4 figures, 3 table

Enhancing shopping experiences in smart retailing

The retailing market has undergone a paradigm-shift in the last decades, departing from its traditional form of shopping in brick-and-mortar stores towards online shopping and the establishment of shopping malls. As a result, “small” independent retailers operating in urban environments have suffered a substantial reduction of their turnover. This situation could be presumably reversed if retailers were to establish business “alliances” targeting economies of scale and engage themselves in providing innovative digital services. The SMARTBUY ecosystem realizes the concept of a “distributed shopping mall”, which allows retailers to join forces and unite in a large commercial coalition that generates added value for both retailers and customers. Along this line, the SMARTBUY ecosystem offers several novel features: (i) inventory management of centralized products and services, (ii) geo-located marketing of products and services, (iii) location-based search for products offered by neighboring retailers, and (iv) personalized recommendations for purchasing products derived by an innovative recommendation system. SMARTBUY materializes a blended retailing paradigm which combines the benefits of online shopping with the attractiveness of traditional shopping in brick-and-mortar stores. This article provides an overview of the main architectural components and functional aspects of the SMARTBUY ecosystem. Then, it reports the main findings derived from a 12 months-long pilot execution of SMARTBUY across four European cities and discusses the key technology acceptance factors when deploying alike business alliances

Influence of liquid structure on diffusive isotope separation in molten silicates and aqueous solutions

Molecular diffusion in natural volcanic liquids discriminates between isotopes of major ions (e.g., Fe, Mg, Ca, and Li). Although isotope separation by diffusion is expected on theoretical grounds, the dependence on mass is highly variable for different elements and in different media. Silicate liquid diffusion experiments using simple liquid compositions were carried out to further probe the compositional dependence of diffusive isotopic discrimination and its relationship to liquid structure. Two diffusion couples consisting of the mineral constituents anorthite (CaAl{sub 2}Si{sub 2}O{sub 8}; denoted AN), albite (NaAlSi{sub 3}O{sub 8}; denoted AB), and diopside (CaMgSi{sub 2}O{sub 6}; denoted DI) were held at 1450°C for 2 h and then quenched to ambient pressure and temperature. Major-element as well as Ca and Mg isotope profiles were measured on the recovered quenched glasses. In both experiments, Ca diffuses rapidly with respect to Si. In the AB–AN experiment, D{sub Ca}/D{sub Si} ~ 20 and the efficiency of isotope separation for Ca is much greater than in natural liquid experiments where D{sub Ca}/D{sub Si} ~ 1. In the AB–DI experiment, D{sub Ca}/D{sub Si} ~ 6 and the efficiency of isotope separation is between that of the natural liquid experiments and the AB–AN experiment. In the AB–DI experiment, D{sub Mg}/D{sub Si} ~ 1 and the efficiency of isotope separation for Mg is smaller than it is for Ca yet similar to that observed for Mg in natural liquids. The results from the experiments reported here, in combination with results from natural volcanic liquids, show clearly that the efficiency of diffusive separation of Ca isotopes is systematically related to the solvent-normalized diffusivity—the ratio of the diffusivity of the cation (D{sub Ca}) to the diffusivity of silicon (D{sub Si}). The results on Ca isotopes are consistent with available data on Fe, Li, and Mg isotopes in silicate liquids, when considered in terms of the parameter D{sub cation}/D{sub Si}. Cations diffusing in aqueous solutions display a similar relationship between isotopic separation efficiency and D{sub cation} =D{sub H 2 O} , although the efficiencies are smaller than in silicate liquids. Our empirical relationship provides a tool for predicting the magnitude of diffusive isotopic effects in many geologic environments and a basis for a more comprehensive theory of isotope separation in liquid solutions. We present a conceptual model for the relationship between diffusivity and liquid structure that is consistent with available data

An overview of solvent extraction processes developed in Europe for advanced nuclear fuel recycling, Part 2 — homogeneous recycling

The hydrometallurgical separation concepts for the recycling of irradiated nuclear fuels developed in Europe are presented and discussed. Whilst Part 1 of the review focused on concepts for heterogeneous recycling of minor actinides, this article focuses on group recycling of transuranic actinides, which would support homogeneous recycling scenarios. Most of these concepts were developed within European collaborative projects and involve solvent extraction processes separating all the actinides (U-Cm) in two cycles. The first cycle uses a monoamide extractant to recover uranium leaving all the transuranic actinides in the aqueous raffinate with the fission products. The second cycle aims for a group recovery of the transuranium elements and several strategies have been proposed for this stage. In this review article, the various solvent extraction processes are summarised and the key features of the process schemes are compared

Tree-mycorrhizal associations detected remotely from canopy spectral properties

A central challenge in global ecology is the identification of key functional processes in ecosystems that scale, but do not require, data for individual species across landscapes. Given that nearly all tree species form symbiotic relationships with one of two types of mycorrhizal fungi – arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) fungi – and that AM- and ECM-dominated forests often have distinct nutrient economies, the detection and mapping of mycorrhizae over large areas could provide valuable insights about fundamental ecosystem processes such as nutrient cycling, species interactions, and overall forest productivity. We explored remotely sensed tree canopy spectral properties to detect underlying mycorrhizal association across a gradient of AM- and ECM-dominated forest plots. Statistical mining of reflectance and reflectance derivatives across moderate/high-resolution Landsat data revealed distinctly unique phenological signals that differentiated AM and ECM associations. This approach was trained and validated against measurements of tree species and mycorrhizal association across ~130 000 trees throughout the temperate United States. We were able to predict 77% of the variation in mycorrhizal association distribution within the forest plots (P \u3c 0.001). The implications for this work move us toward mapping mycorrhizal association globally and advancing our understanding of biogeochemical cycling and other ecosystem processes