Fast Fourier Transform periodic interpolation method for superposition sums in a periodic unit cell
Not Available
Ai, Fangzhou↗
Engineering topics
Lomakin, Vitaliy
Publications and source records attributed to Lomakin, Vitaliy.
Giant phonon-skyrmion coupling in ferromagnet/heavy metal heterostructures
Not provided.
Materials Science↗
Voltage-controlled magnetic anisotropy enabled by resistive switching
The discovery of new mechanisms of controlling magnetic properties by electric fields or currents furthers the fundamental understanding of magnetism and has important implications for practical use. Here, we present an approach of utilizing resistive switching to control magnetic anisotropy. We study a ferromagnetic oxide that exhibits an electrically triggered metal-to-insulator phase transition producing a volatile resistive switching. The switching occurs in a characteristic spatial pattern, the formation of an insulating barrier perpendicular to the current flow, which results in an unusual ferromagnetic/paramagnetic/ferromagnetic configuration. Further, the formation of this voltage-driven paramagnetic insulating barrier is accompanied by the emergence of a strong uniaxial magnetic anisotropy that overpowers the intrinsic material anisotropy. Our results demonstrate that resistive switching is an effective tool for manipulating magnetic properties. Because resistive switching can be induced in a broad range of materials, our findings could enable a new class of voltage-controlled magnetism systems.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Linearized frequency domain Landau-Lifshitz-Gilbert equation formulation
We present a general finite element linearized Landau-Lifshitz-Gilbert equation (LLGE) solver for magnetic systems under weak time-harmonic excitation field. The linearized LLGE is obtained by assuming a small deviation around the equilibrium state of the magnetic system. Inserting such expansion into LLGE and keeping only first order terms gives the linearized LLGE, which gives a frequency domain solution for the complex magnetization amplitudes under an external time-harmonic applied field of a given frequency. We solve the linear system with an iterative solver using generalized minimal residual method. We construct a preconditioner matrix to effectively solve the linear system. The validity, effectiveness, speed, and scalability of the linear solver are demonstrated via numerical examples.
36 MATERIALS SCIENCE↗
Switching current reduction in magnetoresistive random access memories
We present an approach for minimizing the critical current for the magnetization switching in magnetic tunnel junctions by optimizing the spatial distribution of the current density. We show that such a minimization is possible because critical current is determined by the condition of making one of the magnetization eigenstates grow in time. The excitation of the eigenstates is enhanced when the spatial distributions of the eigenstates and current density overlap. Critical current can be viewed as a functional of the current density spatial distribution and it can be minimized by optimizing this distribution. Such an optimization results in a major reduction of the critical current and increase of the switching efficiency, viz. the ratio between the energy barrier and critical current. The minimized critical current increases approximately linearly with the magnetic tunnel junction size, which is much slower than critical current for the case of a uniform current density. The optimized efficiency can be approximately a constant with respect to the magnetic tunnel junction size, which is much higher than the efficiency for the uniform current density. Additional optimization can be achieved by spatially modulating the material parameters, e.g., the saturation magnetization. The presented approach and obtained scaling of the critical current and efficiency offers opportunities for the magnetic tunnel junction optimization.
36 MATERIALS SCIENCE↗
Quantum materials for energy-efficient neuromorphic computing: Opportunities and challenges
Neuromorphic computing approaches become increasingly important as we address future needs for efficiently processing massive amounts of data. The unique attributes of quantum materials can help address these needs by enabling new energy-efficient device concepts that implement neuromorphic ideas at the hardware level. In particular, strong correlations give rise to highly non-linear responses, such as conductive phase transitions that can be harnessed for short- and long-term plasticity. Similarly, magnetization dynamics are strongly non-linear and can be utilized for data classification. This Perspective discusses select examples of these approaches and provides an outlook on the current opportunities and challenges for assembling quantum-material-based devices for neuromorphic functionalities into larger emergent complex network systems.
36 MATERIALS SCIENCE↗