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There is accelerating interest in developing memory devices using antiferromagnetic (AFM) materials, motivated by the possibility for electrically controlling AFM order via spin-orbit torques, and its read-out via magnetoresistive effects. Recent studies have shown, however, that high current densities create non-magnetic contributions to resistive switching signals in AFM/heavy metal (AFM/HM) bilayers, complicating their interpretation. Here we introduce an experimental protocol to unambiguously distinguish current-induced magnetic and nonmagnetic switching signals in AFM/HM structures, and demonstrate it in IrMn3/Pt devices. A six-terminal double-cross device is constructed, with an IrMn3 pillar placed on one cross. The differential voltage is measured between the two crosses with and without IrMn3 after each switching attempt. For a wide range of current densities, reversible switching is observed only when write currents pass through the cross with the IrMn3 pillar, eliminating any possibility of non-magnetic switching artifacts. Micromagnetic simulations support our findings, indicating a complex domain-mediated switching process.

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A scaling law is demonstrated in the conductivity of gated two-dimensional (2D) materials with tunable concentrations of ionized impurity scatterers. Experimental data is shown to collapse onto a single 2D conductivity scaling (2DCS) curve when the mobility is scaled by r, the relative impurity-induced scattering, and the gate voltage is shifted by Vs, a consequence of impurity-induced doping. This 2DCS analysis is demonstrated first in an encapsulated 2D black phosphorus multilayer at T = 100K with charge trap densities programmed by a gate bias upon cooldown, and next in a Bi2Se3 2D monolayer at room temperature exposed to varying concentrations of gas adsorbates. The observed scaling can be explained using a conductivity model with screened ionized impurity scatterers. The slope of the r vs. Vs plot defines a disorder-charge specific scattering rate Γq = dr/dVs equivalent to a scattering strength per unit impurity charge density: Γq > 0 indicates a preponderance of positively charged impurities with Γq < 0 for negatively charged. This 2DCS analysis is expected to be applicable in arbitrary 2D materials systems with tunable impurity density, which will advance 2D materials characterization and improve performance of 2D sensors and transistors.

We present a super-resolution model for an advection-diffusion process with limited information. While most of the super-resolution models assume high-resolution (HR) ground-truth data in the training, in many cases such HR dataset is not readily accessible. Here, we show that a Recurrent Convolutional Network trained with physics-based regularizations is able to reconstruct the HR information without having the HR ground-truth data. Moreover, considering the ill-posed nature of a super-resolution problem, we employ the Recurrent Wasserstein Autoencoder to model the uncertainty.• Address the common problem of the lack of ground-truth HR data.• Model the uncertainty with a probabilistic model.