Adaptive cognition implemented with a context-aware and flexible neuron for next-generation artificial intelligence.

Neuromorphic computing mimics the organizational principles of the brain in its quest to replicate the brain's intellectual abilities. An impressive ability of the brain is its adaptive intelligence, which allows the brain to regulate its functions "on the fly" to cope with myriad and ever-changing situations. In particular, the brain displays three adaptive and advanced intelligence abilities of context-awareness, cross frequency coupling, and feature binding. To mimic these adaptive cognitive abilities, we design and simulate a novel, hardware-based adaptive oscillatory neuron using a lattice of magnetic skyrmions. Charge current fed to the neuron reconfigures the skyrmion lattice, thereby modulating the neuron's state, its dynamics and its transfer function "on the fly." This adaptive neuron is used to demonstrate the three cognitive abilities, of which context-awareness and cross-frequency coupling have not been previously realized in hardware neurons. Additionally, the neuron is used to construct an adaptive artificial neural network (ANN) and perform context-aware diagnosis of breast cancer. Simulations show that the adaptive ANN diagnoses cancer with higher accuracy while learning faster and using a more compact and energy-efficient network than a nonadaptive ANN. The work further describes how hardware-based adaptive neurons can mitigate several critical challenges facing contemporary ANNs. Modern ANNs require large amounts of training data, energy, and chip area, and are highly task-specific; conversely, hardware-based ANNs built with adaptive neurons show faster learning, compact architectures, energy-efficiency, fault-tolerance, and can lead to the realization of broader artificial intelligence.

Effects of Anisotropic Strain on Spin-Orbit Torque Produced by the Dirac Nodal Line Semimetal IrO2.

We report spin-torque ferromagnetic resonance studies of the efficiency of the damping-like (ξDL) spin-orbit torque exerted on an adjacent ferromagnet film by current flowing in epitaxial (001) and (110) IrO2 thin films. IrO2 possesses Dirac nodal lines (DNLs) in the band structure that are gapped by spin-orbit coupling, which could enable a very high spin Hall conductivity, σSH. We find that the (001) films do exhibit exceptionally high ξDL ranging from 0.45 at 293 K to 0.65 at 30 K, which sets the lower bounds of σSH to be 1.9 × 105 and 3.75 × 105 Ω-1 m-1, respectively, 10 times higher and of opposite sign than the theoretical prediction. Furthermore, ξDL and σSH are substantially reduced in anisotropically strained (110) films. We suggest that this high sensitivity to anisotropic strain is because of changes in contributions to σSH near the DNLs.

Rational design principles for giant spin Hall effect in 5d-transition metal oxides.

Spin Hall effect (SHE), a mechanism by which materials convert a charge current into a spin current, invokes interesting physics and promises to empower transformative, energy-efficient memory technology. However, fundamental questions remain about the essential factors that determine SHE. Here, we solve this open problem, presenting a comprehensive theory of five rational design principles for achieving giant intrinsic SHE in transition metal oxides. Arising from our key insight regarding the inherently geometric nature of SHE, we demonstrate that two of these design principles are weak crystal fields and the presence of structural distortions. Moreover, we discover that antiperovskites are a highly promising class of materials for achieving giant SHE, reaching SHE values an order of magnitude larger than that reported for any oxide. Additionally, we derive three other design principles for enhancing SHE. Our findings bring deeper insight into the physics driving SHE and could help enhance and externally control SHE values.

Density functional theory based study of graphene and dielectric oxide interfaces.

We study the effects of insulating oxides in their crystalline forms on the energy band structure of monolayer and bilayer graphene using a first principles density functional theory based electronic structure method and a local density approximation. We consider the dielectric oxides SiO(2) (α-quartz) and Al(2)O(3) (alumina or α-sapphire), each with two surface terminations. Our study suggests that atomic relaxations and resulting equilibrium separations play a critical role in perturbing the linear band structure of graphene in contrast to the less critical role played by dangling bonds that result from cleaving the crystal in a particular direction. For Si-terminated quartz a Dirac cone is retained while it is restored on adding a second graphene layer for O-terminated quartz. Alumina needs more than two graphene layers to preserve the Dirac cone. Our results are, at best, semi-quantitative for the common amorphous forms of the oxides considered.