Orientational pinning and transverse voltage: Simulations and experiments in square Josephson junction arrays

We study the dependence of the transport properties of square Josephson Junctions arrays with the direction of the applied dc current, both experimentally and numerically. We present computational simulations of current-voltage curves at finite temperatures for a single vortex in the array ($Ha^2/\Phi_0=f=1/L^2$), and experimental measurements in $100\times1000$ arrays under a low magnetic field corresponding to $f\approx0.02$. We find that the transverse voltage vanishes only in the directions of maximum symmetry of the square lattice: the [10] and [01] direction (parallel bias) and the [11] direction (diagonal bias). For orientations different than the symmetry directions, we find a finite transverse voltage which depends strongly on the angle $\phi$ of the current. We find that vortex motion is pinned in the [10] direction ($\phi=0$), meaning that the voltage response is insensitive to small changes in the orientation of the current near $\phi=0$. We call this phenomenon orientational pinning. This leads to a finite transverse critical current for a bias at $\phi=0$ and to a transverse voltage for a bias at $\phi\not=0$. On the other hand, for diagonal bias in the [11] direction the behavior is highly unstable against small variations of $\phi$, leading to a rapid change from zero transverse voltage to a large transverse voltage within a few degrees. This last behavior is in good agreement with our measurements in arrays with a quasi-diagonal current drive.Comment: 9 pages, 9 figure

Diffusion studies in the β (B2), β′ (bcc), and γ (fcc) Fe-Ni-Al alloys at 1000 °C

Diffusion studies were carried out in the Fe-Ni-Al system at 1000°C with solid-solid diffusion couples assembled with β (B2), β′ (bcc), and γ (fcc) single-phase alloys for the development of diffusion structures, diffusion paths, and for the determination of interdiffusion and intrinsic diffusion coefficients. The diffusion structures were examined by optical and scanning electron microscopy, and the concentration profiles were determined by electron microprobe analysis. Diffusion couples included several series of β vs γ and β′ vs γ diffusion couples characterized by a common terminal alloy bonded to several terminal alloys with varying compositions. The development of planar and nonplanar interfaces, as well as two-phase layers, as observed in various couples, were related to the diffusion paths. The interdiffusion fluxes of individual components were calculated directly from the experimental concentration profiles, and the diffusional interactions among components were examined in the light of zero-flux planes (ZFPs) and flux reversals, which were identified in several couples. Ternary interdiffusion coefficients (D̃i.jFe (i, j = Al, Ni)), with Fe considered as the dependent concentration variable, were evaluated at composition points of the intersection of diffusion paths of single-phase couples and of multiphase couples that developed planar interfaces. The interdiffusion coefficients were the largest in magnitude for the β′ alloys, especially near the β/β′ miscibility gap, and decreased for the β and γ alloys. In the β and γ phases, the main interdiffusion coefficient for Al was larger than those for Ni and Fe. Also, Fe interdiffused faster than Ni in the Fe-rich β and β′ phases. The cross-interdiffusion coefficients (D̃AlNiFe and D̃NiAlFe) were negative in all three phases. In general, the D̃AlNiFe coefficients were larger in magnitude than the D̃NiAlFe coefficients; however, the magnitude of D̃NiAlFe was greater than that of D̃AlNiFe near the β/(β + γ) phase boundary on the ternary isotherm. In the β phase, the magnitude of D̃ijFe (i, j = Al, Ni) coefficients increased over 1 to 2 orders of magnitude with a decrease in the Al concentration and increase in the Fe/Ni concentration ratio. Interdiffusion coefficients, extrapolated from the ternary coefficients for binary alloys, were consistent with those in literature. Intrinsic diffusion coefficients were also determined at selected compositions. In addition, tracer diffusion coefficients were estimated for the binary Fe-Al and Ni-Al alloys at selected compositions, from an extrapolation of ternary interdiffusion coefficients

Prediction of Breast Cancer Risk Based on Profiling With Common Genetic Variants

Background: Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking. Methods: We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates. Results: There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer. Conclusions: The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.Peer reviewe