X-ray Nanoimaging of a Heterogeneous Structural Phase Transition in VO.

Controlling the Mott transition through strain engineering is crucial for advancing the development of memristive and neuromorphic computing devices. Yet, Mott insulators are heterogeneous due to intrinsic phase boundaries and extrinsic defects, posing significant challenges to fully understanding the impact of microscopic distortions on the local Mott transition. Here, using a synchrotron-based scanning X-ray nanoprobe, we studied the real-space structural heterogeneity during the structural phase transition in a VO thin film.

Generation of Tunable Stochastic Sequences Using the Insulator-Metal Transition.

Probabilistic computing is a paradigm in which data are not represented by stable bits, but rather by the probability of a metastable bit to be in a particular state. The development of this technology has been hindered by the availability of hardware capable of generating stochastic and tunable sequences of "1s" and "0s". The options are currently limited to complex CMOS circuitry and, recently, magnetic tunnel junctions.

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.

Spatiotemporal characterization of the field-induced insulator-to-metal transition.

Many correlated systems feature an insulator-to-metal transition that can be triggered by an electric field. Although it is known that metallization takes place through filament formation, the details of how this process initiates and evolves remain elusive. We use in-operando optical reflectivity to capture the growth dynamics of the metallic phase with space and time resolution.

Energy-efficient Mott activation neuron for full-hardware implementation of neural networks.

To circumvent the von Neumann bottleneck, substantial progress has been made towards in-memory computing with synaptic devices. However, compact nanodevices implementing non-linear activation functions are required for efficient full-hardware implementation of deep neural networks. Here, we present an energy-efficient and compact Mott activation neuron based on vanadium dioxide and its successful integration with a conductive bridge random access memory (CBRAM) crossbar array in hardware.

Controlling Metal-Insulator Transitions in Vanadium Oxide Thin Films by Modifying Oxygen Stoichiometry.

Vanadium oxides are strongly correlated materials which display metal-insulator transitions (MITs) as well as various structural and magnetic properties that depend heavily on oxygen stoichiometry. Therefore, it is crucial to precisely control oxygen stoichiometry in these materials, especially in thin films. This work demonstrates a high-vacuum gas evolution technique which allows for the modification of oxygen concentrations in VO thin films by carefully tuning the thermodynamic conditions.

Non-thermal resistive switching in Mott insulator nanowires.

Resistive switching can be achieved in a Mott insulator by applying current/voltage, which triggers an insulator-metal transition (IMT). This phenomenon is key for understanding IMT physics and developing novel memory elements and brain-inspired technology. Despite this, the roles of electric field and Joule heating in the switching process remain controversial.

A caloritronics-based Mott neuristor.

Machine learning imitates the basic features of biological neural networks at a software level. A strong effort is currently being made to mimic neurons and synapses with hardware components, an approach known as neuromorphic computing. While recent advances in resistive switching have provided a path to emulate synapses at the 10 nm scale, a scalable neuron analogue is yet to be found.

Giant nonvolatile resistive switching in a Mott oxide and ferroelectric hybrid.

Controlling the electronic properties of oxides that feature a metal-insulator transition (MIT) is a key requirement for developing a new class of electronics often referred to as "Mottronics." A simple, controllable method to switch the MIT properties in real time is needed for practical applications. Here we report a giant, nonvolatile resistive switching (ΔR/R > 1,000%) and strong modulation of the MIT temperature (ΔT > 30 K) in a voltage-actuated VO/PMN-PT [Pb(Mg,Nb)O-PbTiO] heterostructure.

Robust Coupling between Structural and Electronic Transitions in a Mott Material.

The interdependences of different phase transitions in Mott materials are fundamental to the understanding of the mechanisms behind them. One of the most important relations is between the ubiquitous structural and electronic transitions. Using IR spectroscopy, optical reflectivity, and x-ray diffraction, we show that the metal-insulator transition is coupled to the structural phase transition in V_{2}O_{3} films.

Dynamic Control of the Vortex Pinning Potential in a Superconductor Using Current Injection through Nanoscale Patterns.

Control over the vortex potential at the nanoscale in a superconductor is a subject of great interest for both fundamental and technological reasons. Many methods for achieving artificial pinning centers have been demonstrated, for example, with magnetic nanostructures or engineered imperfections, yielding many intriguing effects. However, these pinning mechanisms do not offer dynamic control over the strength of the patterned vortex potential because they involve static nanostructures created in or near the superconductor.

p-wave triggered superconductivity in single-layer graphene on an electron-doped oxide superconductor.

Electron pairing in the vast majority of superconductors follows the Bardeen-Cooper-Schrieffer theory of superconductivity, which describes the condensation of electrons into pairs with antiparallel spins in a singlet state with an s-wave symmetry. Unconventional superconductivity was predicted in single-layer graphene (SLG), with the electrons pairing with a p-wave or chiral d-wave symmetry, depending on the position of the Fermi energy with respect to the Dirac point. By placing SLG on an electron-doped (non-chiral) d-wave superconductor and performing local scanning tunnelling microscopy and spectroscopy, here we show evidence for a p-wave triggered superconducting density of states in SLG.

Increased superconducting transition temperature of a niobium thin film proximity coupled to gold nanoparticles using linking organic molecules.

The superconducting critical temperature, T(C), of thin Nb films is significantly modified when gold nanoparticles (NPs) are chemically linked to the Nb film, with a consistent enhancement when using 3 nm long disilane linker molecules. The T(C) increases by up to 10% for certain linker length and NP size. No change is observed when the nanoparticles are physisorbed with nonlinking molecules.

Proximity-induced pseudogap: evidence for preformed pairs.

The temperature evolution of the proximity effect in Au/La(2-x)Sr(x)CuO(4) and La(1.55)Sr(0.45)CuO(4)/La(2-x)Sr(x)CuO(4) bilayers was investigated using scanning tunneling microscopy.