Search

Neuromorphic computing (NC) has been gaining attention as a potential candidate for artificial intelligence. The building blocks for NC are neurons and synapses. Research studies have indicated that domain wall (DW) devices are one of the most energy-efficient contenders for realizing NC. Moreover, synaptic functions can be achieved by obtaining multi-resistance states in DW devices. However, in DW devices with no artificial pinning, it is difficult to control the DW position, and hence achieving multilevel resistance is difficult. Here, we have proposed the concept of nanoscale interfacial Dzyaloshinskii–Moriya interaction (iDMI) for controllably stopping the DWs at specific positions, and hence, realizing multi-resistance states. We show that the nanoscale iDMI forms an energy barrier (well), which can controllably pin the DWs at the pinning sites. Moreover, a tunable depinning current density was achieved by changing the width and iDMI constant of the confinement region. We have also studied pinning in a device with five successive pinning sites. This feature is a proof-of-concept for realizing multi-resistance states in the proposed concept. Based on these observations, a magnetic tunnel junction—where the free layer is made up of the proposed concept—can be fabricated to achieve synapses for NC applications. [ABSTRACT FROM AUTHOR]

Pursuing enhanced spin–orbit torque (SOT) has become a significant focus for achieving energy-efficient spintronics devices. Researchers have explored different materials, layer engineering, and various post-deposition modification methods to realize higher SOT. Here, we have utilized the bombardment of mixed ions (Ar+ and He+ in various ratios) with 0.6 kV bias voltage to enhance the SOT efficiency in a Pt/Co/W stack. The bombardment modifies the physical properties (magnetic, electric, and structural) due to cascade collision, knocking off atoms (from the surface), and ion implantation. The increased percentage of He+ suppresses the drastic behavior of cascade collisions, and hence, the properties are tunable by changing the gas ratio. We exploited this behavior to design a material stack with enhanced SOT efficiency. We fabricated Hall bars to quantify SOT and observed a 4.5× increase in the effective damping-like efficiency. The efficiency and switching current density in the stack could be tuned by the variation of Ar:He ion ratio and the exposure duration. This study offers an easy route to tune the energy efficiency of spin devices, contributing to the advancement of next-generation spintronics. [ABSTRACT FROM AUTHOR]

Summary: The error analysis for the selection of representative point sets (RPSs) in multidimensional random‐variate space assigned with arbitrary nonuniform distribution with compact support for uncertainty quantification is developed by extending the Koksma‐Hlawka inequalities, which bound the worst error with some kind of discrepancy of the RPS and the variation of the integrand. The novel concepts of the EF‐discrepancy and the GF‐discrepancy are introduced, and the connection and equivalence between them are inquired into. Based on such theoretical basis, the error estimate of selecting RPSs in the standardized space instead of that in the original physical space is studied, showing that the standardization of the input random variables does not increase, but usually reduce, the error bound by GF‐discrepancy. The extended Koksma‐Hlawka inequality also establishes the theoretical basis for the error estimate of the probability density evolution method. Besides, the closed‐form expressions for the EF‐discrepancy are given in the Appendix. A numerical example involving a complex nonlinear engineering structure modeled by the finite element method is studied, showing the accuracy of the proposed approach. [ABSTRACT FROM AUTHOR]