Nanoscale metal inclusions in or on solid-state dielectrics are an integral part of modern electrocatalysis, optoelectronics, capacitors, metamaterials and memory devices. The properties of these composite systems strongly depend on the size, dispersion of the inclusions and their chemical stability, and are usually considered constant. Here we demonstrate that nanoscale inclusions (for example, clusters) in dielectrics dynamically change their shape, size and position upon applied electric field. Through systematic in situ transmission electron microscopy studies, we show that fundamental electrochemical processes can lead to universally observed nucleation and growth of metal clusters, even for inert metals like platinum. The clusters exhibit diverse dynamic behaviours governed by kinetic factors including ion mobility and redox rates, leading to different filament growth modes and structures in memristive devices. These findings reveal the microscopic origin behind resistive switching, and also provide general guidance for the design of novel devices involving electronics and ionics.

Epitaxy-the growth of a crystalline material on a substrate-is crucial for the semiconductor industry, but is often limited by the need for lattice matching between the two material systems. This strict requirement is relaxed for van der Waals epitaxy, in which epitaxy on layered or two-dimensional (2D) materials is mediated by weak van der Waals interactions, and which also allows facile layer release from 2D surfaces. It has been thought that 2D materials are the only seed layers for van der Waals epitaxy. However, the substrates below 2D materials may still interact with the layers grown during epitaxy (epilayers), as in the case of the so-called wetting transparency documented for graphene. Here we show that the weak van der Waals potential of graphene cannot completely screen the stronger potential field of many substrates, which enables epitaxial growth to occur despite its presence. We use density functional theory calculations to establish that adatoms will experience remote epitaxial registry with a substrate through a substrate-epilayer gap of up to nine ångströms; this gap can accommodate a monolayer of graphene. We confirm the predictions with homoepitaxial growth of GaAs(001) on GaAs(001) substrates through monolayer graphene, and show that the approach is also applicable to InP and GaP. The grown single-crystalline films are rapidly released from the graphene-coated substrate and perform as well as conventionally prepared films when incorporated in light-emitting devices. This technique enables any type of semiconductor film to be copied from underlying substrates through 2D materials, and then the resultant epilayer to be rapidly released and transferred to a substrate of interest. This process is particularly attractive in the context of non-silicon electronics and photonics, where the ability to re-use the graphene-coated substrates allows savings on the high cost of non-silicon substrates.

Memristors have been extensively studied for data storage and low-power computation applications. In this study, we show that memristors offer more than simple resistance change. Specifically, the dynamic evolutions of internal state variables allow an oxide-based memristor to exhibit Ca(2+)-like dynamics that natively encode timing information and regulate synaptic weights. Such a device can be modeled as a second-order memristor and allow the implementation of critical synaptic functions realistically using simple spike forms based solely on spike activity.

Although several types of architecture combining memory cells and transistors have been used to demonstrate artificial synaptic arrays, they usually present limited scalability and high power consumption. Transistor-free analog switching devices may overcome these limitations, yet the typical switching process they rely on-formation of filaments in an amorphous medium-is not easily controlled and hence hampers the spatial and temporal reproducibility of the performance. Here, we demonstrate analog resistive switching devices that possess desired characteristics for neuromorphic computing networks with minimal performance variations using a single-crystalline SiGe layer epitaxially grown on Si as a switching medium. Such epitaxial random access memories utilize threading dislocations in SiGe to confine metal filaments in a defined, one-dimensional channel. This confinement results in drastically enhanced switching uniformity and long retention/high endurance with a high analog on/off ratio. Simulations using the MNIST handwritten recognition data set prove that epitaxial random access memories can operate with an online learning accuracy of 95.1%.

Low-dimensional electronic systems have traditionally been obtained by electrostatically confining electrons, either in heterostructures or in intrinsically nanoscale materials such as single molecules, nanowires, and graphene. Recently, a new paradigm has emerged with the advent of symmetry-protected surface states on the boundary of topological insulators, enabling the creation of electronic systems with novel properties. For example, time reversal symmetry (TRS) endows the massless charge carriers on the surface of a three-dimensional topological insulator with helicity, locking the orientation of their spin relative to their momentum 1,2 . Weakly breaking this symmetry generates a gap on the surface, 3 resulting in charge carriers with finite effective mass and exotic spin textures 4 . Analogous manipulations of the one-dimensional boundary states of a two-dimensional topological insulator are also possible, but have yet to be observed in the leading candidate materials 5,6 . Here, we demonstrate experimentally that charge neutral monolayer graphene displays a new type of quantum spin Hall (QSH) effect 7,8 , previously thought to exist only in time reversal invariant topological insulators 5,9-11 , when it is subjected to a very large magnetic field angled with respect to the graphene plane. Unlike in the TRS case 5,9,10 , the QSH presented here is protected by a spin-rotation symmetry that emerges as electron spins in a half-filled Landau level are polarized by the large in-plane magnetic field. The properties of the resulting helical edge states can be modulated by balancing the applied field against an intrinsic antiferromagnetic instability [12][13][14] , which tends to spontaneously break the spin-rotation symmetry. In the resulting canted antiferromagnetic (CAF) state, we observe transport signatures of gapped edge states, which constitute a new kind of one-dimensional electronic system with tunable band gap and associated spin-texture 15 .In the integer quantum Hall effect, the topology of the bulk Landau level (LL) energy bands 16 requires the existence of gapless edge states at any interface with the vacuum. The metrological precision of the Hall quantization can be traced to the inability of these edge states to backscatter due to the physical separation of modes with opposite momentum by the insulating sample bulk 17 . In contrast, counterpropagating boundary states in a symmetry-protected topological (SPT) insulator coexist spatially but are prevented from backscattering by a symmetry of the experimental system 1,2 . The local symmetry that protects transport in SPT surface states is unlikely to be as robust as the inherently nonlocal physical separation that protects the quantum Hall effect. However, it enables the creation of new electronic systems in which momentum and some quantum number such as spin are coupled, potentially leading to devices with new functionality. Most experimentally realized SPT phases are based on TRS, with counterpropagating states protected from intermixing by the Kram...

Memristors have been proposed for a number of applications from nonvolatile memory to neuromorphic systems. Unlike conventional devices based solely on electron transport, memristors operate on the principle of resistive switching (RS) based on redistribution of ions. To date, a number of experimental and modeling studies have been reported to probe the RS mechanism; however, a complete physical picture that can quantitatively describe the dynamic RS behavior is still missing. Here, we present a quantitative and accurate dynamic switching model that not only fully accounts for the rich RS behaviors in memristors in a unified framework but also provides critical insight for continued device design, optimization, and applications. The proposed model reveals the roles of electric field, temperature, oxygen vacancy concentration gradient, and different material and device parameters on RS and allows accurate predictions of diverse set/reset, analog switching, and complementary RS behaviors using only material-dependent device parameters.

Nanoscale resistive switching devices (memristive devices or memristors) have been studied for a number of applications ranging from non-volatile memory, logic to neuromorphic systems. However a major challenge is to address the potentially large variations in space and time in these nanoscale devices. Here we show that in metal-filament based memristive devices the switching can be fully stochastic. While individual switching events are random, the distribution and probability of switching can be well predicted and controlled. Rather than trying to force high switching probabilities using excess voltage or time, the inherent stochastic nature of resistive switching allows these binary devices to be used as building blocks for novel error-tolerant computing schemes such as stochastic computing and provides the needed "analog" feature for neuromorphic applications. To verify such potential, we demonstrated memristor-based stochastic bitstreams in both time and space domains, and show that an array of binary memristors can act as a multi-level "analog" device for neuromorphic applications.

Resistive switching devices are widely believed as a promising candidate for future memory and logic applications. Here we show that by using multilayer oxide heterostructures the switching characteristics can be systematically controlled, ranging from unipolar switching to complementary switching and bipolar switching with linear and nonlinear on-states and high endurance. Each layer can be tailed for a specific function during resistance switching, thus greatly improving the degree of control and flexibility for optimized device performance.