Nanoscale Correlations between Metal-Insulator Transition and Resistive Switching Effect in Metallic Perovskite Oxides

Tuning the superconducting performance of YBa2Cu3O7-δ films through field-induced oxygen doping

The exploration of metal-insulator transitions to produce field-induced reversible resistive switching effects has been a longstanding pursuit in materials science. Although the resistive switching effect in strongly correlated oxides is often associated with the creation or annihilation of oxygen vacancies, the underlying mechanisms behind this phenomenon are complex and, in many cases, still not clear. This study focuses on the analysis of the superconducting performance of cuprate YBa2Cu3O7-δ (YBCO) devices switched to different resistive states through gate voltage pulses. The goal is to evaluate the effect of field-induced oxygen diffusion on the magnetic field and angular dependence of the critical current density and identify the role of induced defects in the switching performance. Transition electron microscopy measurements indicate that field-induced transition to high resistance states occurs through the generation of YBa2Cu4O7 (Y124) intergrowths with a large amount of oxygen vacancies, in agreement with the obtained critical current density dependences. These results have significant implications for better understanding the mechanisms of field-induced oxygen doping in cuprate superconductors and their role on the superconducting performance.

Quantum Monte Carlo Method in the Steady State

We present a numerically exact steady-state inchworm Monte Carlo method for nonequilibrium quantum impurity models. Rather than propagating an initial state to long times, the method is directly formulated in the steady state. This eliminates any need to traverse the transient dynamics and grants access to a much larger range of parameter regimes at vastly reduced computational costs. We benchmark the method on equilibrium Green's functions of quantum dots in the noninteracting limit and in the unitary limit of the Kondo regime. We then consider correlated materials described with dynamical mean field theory and driven away from equilibrium by a bias voltage. We show that the response of a correlated material to a bias voltage differs qualitatively from the splitting of the Kondo resonance observed in bias-driven quantum dots.

Superconducting disordered neural networks for neuromorphic processing with fluxons

In superconductors, magnetic fields are quantized into discrete fluxons (flux quanta Φ₀), made of microscopic circulating supercurrents. We introduce a multiterminal synapse network comprising a disordered array of superconducting loops with Josephson junctions. The loops can trap fluxons defining memory, while the junctions allow their movement between loops. Dynamics of fluxons through such a disordered system through a complex reconfigurable energy landscape represents brain-like spiking information flow. In this work, we experimentally demonstrate a three-loop network using YBa₂Cu₃O_{7 - δ}-based superconducting loops and Josephson junctions, which exhibit stable memory configurations of trapped flux in loops that determine the rate of flow of fluxons through synaptic connections. The memory states are, in turn, affected by the applied input signals but can also be externally configured electrically through control current/feedback terminals. These results establish a previously unexplored, biologically similar architectural approach to neuromorphic computing that is scalable while dissipating energy of atto Joules/spike.

Transverse barrier formation by electrical triggering of a metal-to-insulator transition

Application of an electric stimulus to a material with a metal-insulator transition can trigger a large resistance change. Resistive switching from an insulating into a metallic phase, which typically occurs by the formation of a conducting filament parallel to the current flow, is a highly active research topic. Using the magneto-optical Kerr imaging, we found that the opposite type of resistive switching, from a metal into an insulator, occurs in a reciprocal characteristic spatial pattern: the formation of an insulating barrier perpendicular to the driving current. This barrier formation leads to an unusual N-type negative differential resistance in the current-voltage characteristics. We further demonstrate that electrically inducing a transverse barrier enables a unique approach to voltage-controlled magnetism. By triggering the metal-to-insulator resistive switching in a magnetic material, local on/off control of ferromagnetism is achieved using a global voltage bias applied to the whole device.

Low-temperature emergent neuromorphic networks with correlated oxide devices

Neuromorphic computing-which aims to mimic the collective and emergent behavior of the brain's neurons, synapses, axons, and dendrites-offers an intriguing, potentially disruptive solution to society's ever-growing computational needs. Although much progress has been made in designing circuit elements that mimic the behavior of neurons and synapses, challenges remain in designing networks of elements that feature a collective response behavior. We present simulations of networks of circuits and devices based on superconducting and Mott-insulating oxides that display a multiplicity of emergent states that depend on the spatial configuration of the network. Our proposed network designs are based on experimentally known ways of tuning the properties of these oxides using light ions. We show how neuronal and synaptic behavior can be achieved with arrays of superconducting Josephson junction loops, all within the same device. We also show how a multiplicity of synaptic states could be achieved by designing arrays of devices based on hydrogenated rare earth nickelates. Together, our results demonstrate a research platform that utilizes the collective macroscopic properties of quantum materials to mimic the emergent behavior found in biological systems.

Electrical Conduction Characteristic of a 2D MXene Device with Cu/Cr2C/TiN Structure Based on Density Functional Theory

The electronic structure and the corresponding electrical conductive behavior of the Cu/Cr₂C/TiN stack were assessed according to a newly developed first-principle model based on density functional theory. Using an additional Cr₂C layer provides the metal-like characteristic of the Cu/Cr₂C/TiN stack with much larger electrical conduction coefficients (i.e., mobility, diffusivity, and electrical conductivity) than the conventional Ag/Ti₃C₂/Pt stack due to the lower activation energy. This device is therefore capable of offering faster switching speeds, lower programming voltage, and better stability and durability than the memristor device with conventional Ti₃C₂ MXene.