Spin injection and spin accumulation in all-metal mesoscopic spin valves

We study the electrical injection and detection of spin accumulation in lateral ferromagnetic metal-nonmagnetic metal-ferromagnetic metal (F/N/F) spin valve devices with transparent interfaces. Different ferromagnetic metals, permalloy (Py), cobalt (Co) and nickel (Ni), are used as electrical spin injectors and detectors. For the nonmagnetic metal both aluminium (Al) and copper (Cu) are used. Our multi-terminal geometry allows us to experimentally separate the spin valve effect from other magneto resistance signals such as the anomalous magneto resistance (AMR) and Hall effects. We find that the AMR contribution of the ferromagnetic contacts can dominate the amplitude of the spin valve effect, making it impossible to observe the spin valve effect in a 'conventional' measurement geometry. In a 'non local' spin valve measurement we are able to completely isolate the spin valve signal and observe clear spin accumulation signals at T=4.2 K as well as at room temperature (RT). For aluminum we obtain spin relaxation lengths (lambda_{sf}) of 1.2 mu m and 600 nm at T=4.2 K and RT respectively, whereas for copper we obtain 1.0 mu m and 350 nm. The spin relaxation times tau_{sf} in Al and Cu are compared with theory and results obtained from giant magneto resistance (GMR), conduction electron spin resonance (CESR), anti-weak localization and superconducting tunneling experiments. The spin valve signals generated by the Py electrodes (alpha_F lambda_F=0.5 [1.2] nm at RT [T=4.2 K]) are larger than the Co electrodes (alpha_F lambda_F=0.3 [0.7] nm at RT [T=4.2 K]), whereas for Ni (alpha_F lambda_F<0.3 nm at RT and T=4.2 K) no spin signal is observed. These values are compared to the results obtained from GMR experiments.Comment: 16 pages, 12 figures, submitted to PR

A global phylogenomic analysis of the shiitake genus Lentinula

Lentinula is a broadly distributed group of fungi that contains the cultivated shiitake mushroom, L. edodes. We sequenced 24 genomes representing eight described species and several unnamed lineages of Lentinula from 15 countries on four continents. Lentinula comprises four major clades that arose in the Oligocene, three in the Americas and one in Asia–Australasia. To expand sampling of shiitake mushrooms, we assembled 60 genomes of L. edodes from China that were previously published as raw Illumina reads and added them to our dataset. Lentinula edodes sensu lato (s. lat.) contains three lineages that may warrant recognition as species, one including a single isolate from Nepal that is the sister group to the rest of L. edodes s. lat., a second with 20 cultivars and 12 wild isolates from China, Japan, Korea, and the Russian Far East, and a third with 28 wild isolates from China, Thailand, and Vietnam. Two additional lineages in China have arisen by hybridization among the second and third groups. Genes encoding cysteine sulfoxide lyase (lecsl) and γ-glutamyl transpeptidase (leggt), which are implicated in biosynthesis of the organosulfur flavor compound lenthionine, have diversified in Lentinula. Paralogs of both genes that are unique to Lentinula (lecsl 3 and leggt 5b) are coordinately up-regulated in fruiting bodies of L. edodes. The pangenome of L. edodes s. lat. contains 20,308 groups of orthologous genes, but only 6,438 orthogroups (32%) are shared among all strains, whereas 3,444 orthogroups (17%) are found only in wild populations, which should be targeted for conservation

Surface Magneto-Optic Kerr Effect

A simple apparatus based on magneto-optic Kerr effect is described which is suitable for studying surface magnetism of thin three- and four-component multilayers. Specific examples are given on how the system can be used and how it performs in various types of studies. Its applications include registration of magnetic hysteresis loops, determination of the Curie and Neél transition temperatures, and detection of surface magnetism and magnetic anisotropies. INTRODUCTION Magnetization in ferromagnetic and paramagnetic media causes an optical anisotropy that changes the state of linearly polarized light incident on the surface of such media. In particular, the polarization direction of incident light is rotated upon reflection by a small angle q k (the Kerr angle) and the light becomes elliptically polarized. Such a change of the beam&apos;s characteristics upon reflection from magnetic media is called the surface magneto-optic Kerr effect (SMOKE). The attribute &quot;surface&quot; comes from the fact ..

Modeling Epoxidation of Drug-like Molecules with a Deep Machine Learning Network

[Image: see text] Drug toxicity is frequently caused by electrophilic reactive metabolites that covalently bind to proteins. Epoxides comprise a large class of three-membered cyclic ethers. These molecules are electrophilic and typically highly reactive due to ring tension and polarized carbon–oxygen bonds. Epoxides are metabolites often formed by cytochromes P450 acting on aromatic or double bonds. The specific location on a molecule that undergoes epoxidation is its site of epoxidation (SOE). Identifying a molecule’s SOE can aid in interpreting adverse events related to reactive metabolites and direct modification to prevent epoxidation for safer drugs. This study utilized a database of 702 epoxidation reactions to build a model that accurately predicted sites of epoxidation. The foundation for this model was an algorithm originally designed to model sites of cytochromes P450 metabolism (called XenoSite) that was recently applied to model the intrinsic reactivity of diverse molecules with glutathione. This modeling algorithm systematically and quantitatively summarizes the knowledge from hundreds of epoxidation reactions with a deep convolution network. This network makes predictions at both an atom and molecule level. The final epoxidation model constructed with this approach identified SOEs with 94.9% area under the curve (AUC) performance and separated epoxidized and non-epoxidized molecules with 79.3% AUC. Moreover, within epoxidized molecules, the model separated aromatic or double bond SOEs from all other aromatic or double bonds with AUCs of 92.5% and 95.1%, respectively. Finally, the model separated SOEs from sites of sp(2) hydroxylation with 83.2% AUC. Our model is the first of its kind and may be useful for the development of safer drugs. The epoxidation model is available at http://swami.wustl.edu/xenosite