Switching Distributions for Perpendicular Spin-Torque Devices within the Macrospin Approximation

We model "soft" error rates for writing (WSER) and for reading (RSER) for perpendicular spin-torque memory devices by solving the Fokker-Planck equation for the probability distribution of the angle that the free layer magnetization makes with the normal to the plane of the film. We obtain: (1) an exact, closed form, analytical expression for the zero-temperature switching time as a function of initial angle; (2) an approximate analytical expression for the exponential decay of the WSER as a function of the time the current is applied; (3) comparison of the approximate analytical expression for the WSER to numerical solutions of the Fokker-Planck equation; (4) an approximate analytical expression for the linear increase in RSER with current applied for reading; (5) comparison of the approximate analytical formula for the RSER to the numerical solution of the Fokker-Planck equation; and (6) confirmation of the accuracy of the Fokker-Planck solutions by comparison with results of direct simulation using the single-macrospin Landau-Lifshitz-Gilbert (LLG) equations with a random fluctuating field in the short-time regime for which the latter is practical

Direct-Current Induced Dynamics in Co90Fe10/Ni80Fe20 Point Contacts

We have directly measured coherent high-frequency magnetization dynamics in ferromagnet films induced by a spin-polarized DC current. The precession frequency can be tuned over a range of several gigahertz, by varying the applied current. The frequencies of excitation also vary with applied field, resulting in a microwave oscillator that can be tuned from below 5 GHz to above 40 GHz. This novel method of inducing high-frequency dynamics yields oscillations having quality factors from 200 to 800. We compare our results with those from single-domain simulations of current-induced dynamics

Flux flow of Abrikosov-Josephson vortices along grain boundaries in high-temperature superconductors

We show that low-angle grain boundaries (GB) in high-temperature superconductors exhibit intermediate Abrikosov vortices with Josephson cores, whose length $l$ along GB is smaller that the London penetration depth, but larger than the coherence length. We found an exact solution for a periodic vortex structure moving along GB in a magnetic field $H$ and calculated the flux flow resistivity $R_F(H)$, and the nonlinear voltage-current characteristics. The predicted $R_F(H)$ dependence describes well our experimental data on $7^{\circ}$ unirradiated and irradiated $YBa_2Cu_3O_7$ bicrystals, from which the core size $l(T)$, and the intrinsic depairing density $J_b(T)$ on nanoscales of few GB dislocations were measured for the first time. The observed temperature dependence of $J_b(T)=J_{b0}(1-T/T_c)^2$ indicates a significant order parameter suppression in current channels between GB dislocation cores.Comment: 5 pages 5 figures. Phys. Rev. Lett. (accepted

Adjusting magnetic nanostructures for high-performance magnetic sensors

The magnetic properties of the soft ferromagnetic layer in magnetic tunnel junctions are one of key factors to determine the performance of magnetoresistance sensors. We use a three-step orthogonal annealing procedure to modify the nanostructures of the free layer in the magnetic tunnel junction to control features such as magnetization reversal, coercivity, exchange field, and tunnel magnetoresistance ratio. We present a sensor with an improved sensitivity as high as 3944%/mT. This magnetic sensor only dissipates 200 lW of power while operating under an applied voltage of 1V

Positional clustering improves computational binding site detection and identifies novel cis-regulatory sites in mammalian GABA(A) receptor subunit genes

Understanding transcription factor (TF) mediated control of gene expression remains a major challenge at the interface of computational and experimental biology. Computational techniques predicting TF-binding site specificity are frequently unreliable. On the other hand, comprehensive experimental validation is difficult and time consuming. We introduce a simple strategy that dramatically improves robustness and accuracy of computational binding site prediction. First, we evaluate the rate of recurrence of computational TFBS predictions by commonly used sampling procedures. We find that the vast majority of results are biologically meaningless. However clustering results based on nucleotide position improves predictive power. Additionally, we find that positional clustering increases robustness to long or imperfectly selected input sequences. Positional clustering can also be used as a mechanism to integrate results from multiple sampling approaches for improvements in accuracy over each one alone. Finally, we predict and validate regulatory sequences partially responsible for transcriptional control of the mammalian type A γ-aminobutyric acid receptor (GABA(A)R) subunit genes. Positional clustering is useful for improving computational binding site predictions, with potential application to improving our understanding of mammalian gene expression. In particular, predicted regulatory mechanisms in the mammalian GABA(A)R subunit gene family may open new avenues of research towards understanding this pharmacologically important neurotransmitter receptor system