ALBERT

Description: Author(s): A. Hojem, D. Wesenberg, and B. L. Zink In a wide range of experiments where electrical currents are used to inject angular momentum, or spin currents, from a metallic ferromagnet into a nonmagnetic metal, the interface plays a critical role. Whether in the giant magnetoresistance effect or in nonlocal spin valves, a loss of spin polarization of an electrical current crossing the interface is seen to reduce the spin current and lead to smaller overall response in sensors. The authors here compare electrical spin injection to the more recently discovered thermal spin injection in a nonlocal spin valve. They show that, despite a strong reduction of electrical spin injection that they tie to the loss of interfacial spin polarization, thermal spin injection remains a large effect. This highlights that thermal spin injection (also called the spin-dependent Seebeck effect) can proceed by new physical mechanisms not possible in the electrically driven case, potentially involving incoherent spin pumping and collective behavior of magnetization in the oxidized interface layer. Better understanding of these interface effects could lead to new ways to increase sensitivity of next-generation magnetic sensors and efficiency of sources of spin current in metallic systems. [Phys. Rev. B 94, 024426] Published Thu Jul 21, 2016

Description: Author(s): B. L. Zink, M. Manno, L. O'Brien, J. Lotze, M. Weiler, D. Bassett, S. J. Mason, S. T. B. Goennenwein, M. Johnson, and C. Leighton We present measurements of spin pumping detected by the inverse spin Hall effect voltage and ferromagnetic resonance spectroscopy in a series of metallic ferromagnet/normal metal thin film stacks. We compare heterostructures grown in situ to those where either a magnetic or nonmagnetic oxide is intr… [Phys. Rev. B 93, 184401] Published Mon May 02, 2016

Description: Heterogeneity of landscape features like terrain, soil, and vegetation properties affects the partitioning of water and energy. However, it remains unclear to what extent an explicit representation of this heterogeneity at the sub-grid scale of distributed hydrological models can improve the hydrological consistency and the robustness of such models. In this study, hydrological process complexity arising from sub-grid topography heterogeneity was incorporated into the distributed mesoscale Hydrologic Model (mHM). Seven study catchments across Europe were used to test whether (1) the incorporation of additional sub-grid variability on the basis of landscape-derived response units improves model internal dynamics, (2) the application of semi-quantitative, expert-knowledge-based model constraints reduces model uncertainty, and whether (3) the combined use of sub-grid response units and model constraints improves the spatial transferability of the model. Unconstrained and constrained versions of both the original mHM and mHMtopo, which allows for topography-based sub-grid heterogeneity, were calibrated for each catchment individually following a multi-objective calibration strategy. In addition, four of the study catchments were simultaneously calibrated and their feasible parameter sets were transferred to the remaining three receiver catchments. In a post-calibration evaluation procedure the probabilities of model and transferability improvement, when accounting for sub-grid variability and/or applying expert-knowledge-based model constraints, were assessed on the basis of a set of hydrological signatures. In terms of the Euclidian distance to the optimal model, used as an overall measure of model performance with respect to the individual signatures, the model improvement achieved by introducing sub-grid heterogeneity to mHM in mHMtopo was on average 13 %. The addition of semi-quantitative constraints to mHM and mHMtopo resulted in improvements of 13 and 19 %, respectively, compared to the base case of the unconstrained mHM. Most significant improvements in signature representations were, in particular, achieved for low flow statistics. The application of prior semi-quantitative constraints further improved the partitioning between runoff and evaporative fluxes. In addition, it was shown that suitable semi-quantitative prior constraints in combination with the transfer-function-based regularization approach of mHM can be beneficial for spatial model transferability as the Euclidian distances for the signatures improved on average by 2 %. The effect of semi-quantitative prior constraints combined with topography-guided sub-grid heterogeneity on transferability showed a more variable picture of improvements and deteriorations, but most improvements were observed for low flow statistics.