Atomic and Electronic Structure of CoFeB/MgO Interface from First Principles

First-principles calculations of the atomic and electronic structure of crystalline CoFeB/MgO/CoFeB magnetic tunnel junctions (MTJs) are performed to understand the effect of B on spin-dependent transport in these junctions. The authors find that it is energetically favorable for B atoms to reside at the crystalline CoFeB/MgO interface rather than remain in the bulk of the crystalline CoFeB electrode. The presence of B at the interfaces is detrimental to tunneling magnetoresistance (TMR) because it significantly suppresses the majority-channel conductance through states of symmetry. Preventing B segregation to the interfaces during annealing should result in an enhanced TMR in CoFeB/MgO/CoFeB MTJs

Effect of oxygen vacancies on spin-dependent tunneling in Fe/MgO/Fe

First-principles calculations based on density functional theory are used to elucidate the effect of O vacancies, forming F centers, on spin-dependent tunneling in Fe/MgO/Fe(001) magnetic tunnel junctions. O vacancies produce occupied localized s states and unoccupied resonant p states, which is consistent with available experimental data. The authors find that O vacancies affect the conductance by nonresonant scattering of tunneling electrons causing a substantial reduction of tunneling magnetoresistance (TMR). Improving the quality of the MgO barrier to reduce O vacancy concentration would improve TMR in these and similar junctions

Signal Durations and local Richter magnitudes in northeast india: An empirical approach

Twenty four analog seismic stations are operated by the Regional Research Laboratory (Jorhat), National Geophysical Research Institute (Hyderabad) and by the India Meteorological Department (IMD) in the Northeastern region (NER) of India. 8000 seismograms of 1992 shallow (5-30km) earthquakes recorded by these stations during the period from January 1985 to December 1999, have been used to establish relationships between signal durations and the local Richter magnitudes (ML). In order to obtain the empirical relations for the determination of duration magnitudes (MD), signal duration estimates have been fitted using regression analysis to models of the form Model-I: MD = C0 + C1 Log10 (S.D) + C2 Δ + C3 h Model-II: MD = C0 + C1 Log10 (S.D) + C2 Δ + C3 h + C4 [Log10 (S.D)]2, where S.D is the signal duration in seconds, Δ epicentral distance in degree and h focal depth in km. The models yielded duration magnitudes at each of the 24 stations having standard deviations as low as 0.07. For these stations, station factors are obtained by finding the average of the deviations of network magnitude (i.e. mean estimate of station magnitudes for each earthquake, denoted by MD A) from station magnitudes (MD) for the earthquake events in NER. Over - and under - estimations of station magnitudes with respect to ML are also determined for each station. It has been observed that the estimates of MD (A) scatter up to about 0.8units with respect to ML for both the models. Application of these factors reduced scatter down to ± 0.25 units for both the models. © Geol. Soc. India

Self-regulation learning as active inference: dynamic causal modeling of an fMRI neurofeedback task

Introduction: Learning to self-regulate brain activity by neurofeedback has been shown to lead to changes in the brain and behavior, with beneficial clinical and non-clinical outcomes. Neurofeedback uses a brain-computer interface to guide participants to change some feature of their brain activity. However, the neural mechanism of self-regulation learning remains unclear, with only 50% of the participants succeeding in achieving it. To bridge this knowledge gap, our study delves into the neural mechanisms of self-regulation learning via neurofeedback and investigates the brain processes associated with successful brain self-regulation. Methods: We study the neural underpinnings of self-regulation learning by employing dynamical causal modeling (DCM) in conjunction with real-time functional MRI data. The study involved a cohort of 18 participants undergoing neurofeedback training targeting the supplementary motor area. A critical focus was the comparison between top-down hierarchical connectivity models proposed by Active Inference and alternative bottom-up connectivity models like reinforcement learning. Results: Our analysis revealed a crucial distinction in brain connectivity patterns between successful and non-successful learners. Particularly, successful learners evinced a significantly stronger top-down effective connectivity towards the target area implicated in self-regulation. This heightened top-down network engagement closely resembles the patterns observed in goal-oriented and cognitive control studies, shedding light on the intricate cognitive processes intertwined with self-regulation learning. Discussion: The findings from our investigation underscore the significance of cognitive mechanisms in the process of self-regulation learning through neurofeedback. The observed stronger top-down effective connectivity in successful learners indicates the involvement of hierarchical cognitive control, which aligns with the tenets of Active Inference. This study contributes to a deeper understanding of the neural dynamics behind successful self-regulation learning and provides insights into the potential cognitive architecture underpinning this process

Ferroelectric Instability under Screened Coulomb Interactions

We explore the effect of charge carrier doping on ferroelectricity using density functional calculations and phenomenological modeling. By considering a prototypical ferroelectric material, BaTiO3, we demonstrate that ferroelectric displacements are sustained up to the critical concentration of 0.11 electron per unit cell volume. This result is consistent with experimental observations and reveals that the ferroelectric phase and conductivity can coexist. Our investigations show that the ferroelectric instability requires only a short-range portion of the Coulomb force with an interaction range of the order of the lattice constant. These results provide a new insight into the origin of ferroelectricity in displacive ferroelectrics and open opportunities for using doped ferroelectrics in novel electronic devices.Comment: 4 pages, 5 figures with 5 pages of supplementary materia

Spin-dependent tunneling from clean and oxidized Co surfaces

Transmission through a sufficiently thick vacuum barrier is factorized in the product of two ‘‘surface transmission functions’’ and a vacuum decay factor. Based on this factorization, we study the spin polarization of the tunneling current from clean and oxidized (1 1 1) FCC Co surfaces through vacuum into Al. The conductance is calculated using the principal-layer Green’s function approach within the tight-binding LMTO scheme. We find that for typical vacuum barrier thicknesses the tunneling current from the clean surface is dominated by minority-spin electrons. A monolayer of oxygen on top of the surface completely changes the shape of kll-resolved transmission and makes the tunneling current almost 100% majority-spin polarized

Optical and magneto-optical properties of MnPt\u3csub\u3e3\u3c/sub\u3e films (abstract)

Optically thick films of MnPt3 were prepared by magnetron sputtering onto quartz substrates. Postdeposition annealing at 850 °C resulted in highly textured (111) films with the L12 (Cu3Au) structure. MnPt3 films are ferromagnetic with a Curie temperature of 380 °C, and they show large magneto-optical effects in the visible.1,2 These films also show a high degree of long-range order. The diagonal components of the dielectric tensor were determined using variable angle spectroscopic ellipsometry measurements over the spectral range 1.2–2.4 eV. Magneto-optic Kerr rotation and ellipticity measurements were made at near normal incidence over the spectral range 1.4–3.6 eV to determine the off-diagonal components of the MnPt3 dielectric tensor. First-principles electronic structure calculations were carried out for the ordered MnPt3 structure, and from these the components of the dielectric tensor were calculated. We find excellent agreement between the measured and calculated diagonal components, but only fair agreement for the off-diagonal components