In-Operando Spatiotemporal Imaging of Coupled Film-Substrate Elastodynamics During an Insulator-to-Metal Transition.

The drive toward non-von Neumann device architectures has led to an intense focus on insulator-to-metal (IMT) and the converse metal-to-insulator (MIT) transitions. Studies of electric field-driven IMT in the prototypical VO2 thin-film channel devices are largely focused on the electrical and elastic responses of the films, but the response of the corresponding TiO2 substrate is often overlooked, since it is nominally expected to be electrically passive and elastically rigid. Here, in-operando spatiotemporal imaging of the coupled elastodynamics using X-ray diffraction microscopy of a VO2 film channel device on TiO2 substrate reveals two new surprises. First, the film channel bulges during the IMT, the opposite of the expected shrinking in the film undergoing IMT. Second, a microns thick proximal layer in the substrate also coherently bulges accompanying the IMT in the film, which is completely unexpected. Phase-field simulations of coupled IMT, oxygen vacancy electronic dynamics, and electronic carrier diffusion incorporating thermal and strain effects suggest that the observed elastodynamics can be explained by the known naturally occurring oxygen vacancies that rapidly ionize (and deionize) in concert with the IMT (MIT). Fast electrical-triggering of the IMT via ionizing defects and an active "IMT-like" substrate layer are critical aspects to consider in device applications.

Programmable coupled oscillators for synchronized locomotion.

The striking similarity between biological locomotion gaits and the evolution of phase patterns in coupled oscillatory network can be traced to the role of central pattern generator located in the spinal cord. Bio-inspired robotics aim at harnessing this control approach for generation of rhythmic patterns for synchronized limb movement. Here, we utilize the phenomenon of synchronization and emergent spatiotemporal pattern from the interaction among coupled oscillators to generate a range of locomotion gait patterns. We experimentally demonstrate a central pattern generator network using capacitively coupled Vanadium Dioxide nano-oscillators. The coupled oscillators exhibit stable limit-cycle oscillations and tunable natural frequencies for real-time programmability of phase-pattern. The ultra-compact 1 Transistor-1 Resistor implementation of oscillator and bidirectional capacitive coupling allow small footprint area and low operating power. Compared to biomimetic CMOS based neuron and synapse models, our design simplifies on-chip implementation and real-time tunability by reducing the number of control parameters.

Stochastic IMT (Insulator-Metal-Transition) Neurons: An Interplay of Thermal and Threshold Noise at Bifurcation.

Artificial neural networks can harness stochasticity in multiple ways to enable a vast class of computationally powerful models. Boltzmann machines and other stochastic neural networks have been shown to outperform their deterministic counterparts by allowing dynamical systems to escape local energy minima. Electronic implementation of such stochastic networks is currently limited to addition of algorithmic noise to digital machines which is inherently inefficient; albeit recent efforts to harness physical noise in devices for stochasticity have shown promise. To succeed in fabricating electronic neuromorphic networks we need experimental evidence of devices with measurable and controllable stochasticity which is complemented with the development of reliable statistical models of such observed stochasticity. Current research literature has sparse evidence of the former and a complete lack of the latter. This motivates the current article where we demonstrate a stochastic neuron using an insulator-metal-transition (IMT) device, based on electrically induced phase-transition, in series with a tunable resistance. We show that an IMT neuron has dynamics similar to a piecewise linear FitzHugh-Nagumo (FHN) neuron and incorporates all characteristics of a spiking neuron in the device phenomena. We experimentally demonstrate spontaneous stochastic spiking along with electrically controllable firing probabilities using Vanadium Dioxide (VO2) based IMT neurons which show a sigmoid-like transfer function. The stochastic spiking is explained by two noise sources - thermal noise and threshold fluctuations, which act as precursors of bifurcation. As such, the IMT neuron is modeled as an Ornstein-Uhlenbeck (OU) process with a fluctuating boundary resulting in transfer curves that closely match experiments. The moments of interspike intervals are calculated analytically by extending the first-passage-time (FPT) models for Ornstein-Uhlenbeck (OU) process to include a fluctuating boundary. We find that the coefficient of variation of interspike intervals depend on the relative proportion of thermal and threshold noise, where threshold noise is the dominant source in the current experimental demonstrations. As one of the first comprehensive studies of a stochastic neuron hardware and its statistical properties, this article would enable efficient implementation of a large class of neuro-mimetic networks and algorithms.

Author Correction: Vertex coloring of graphs via phase dynamics of coupled oscillatory networks.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Vertex coloring of graphs via phase dynamics of coupled oscillatory networks.

While Boolean logic has been the backbone of digital information processing, there exist classes of computationally hard problems wherein this paradigm is fundamentally inefficient. Vertex coloring of graphs, belonging to the class of combinatorial optimization, represents one such problem. It is well studied for its applications in data sciences, life sciences, social sciences and technology, and hence, motivates alternate, more efficient non-Boolean pathways towards its solution. Here we demonstrate a coupled relaxation oscillator based dynamical system that exploits insulator-metal transition in Vanadium Dioxide (VO2) to efficiently solve vertex coloring of graphs. Pairwise coupled VO2 oscillator circuits have been analyzed before for basic computing operations, but using complex networks of VO2 oscillators, or any other oscillators, for more complex tasks have been challenging in theory as well as in experiments. The proposed VO2 oscillator network harnesses the natural analogue between optimization problems and energy minimization processes in highly parallel, interconnected dynamical systems to approximate optimal coloring of graphs. We further indicate a fundamental connection between spectral properties of linear dynamical systems and spectral algorithms for graph coloring. Our work not only elucidates a physics-based computing approach but also presents tantalizing opportunities for building customized analog co-processors for solving hard problems efficiently.

Quantitative mapping of phase coexistence in Mott-Peierls insulator during electronic and thermally driven phase transition.

Quantitative impedance mapping of the spatially inhomogeneous insulator-to-metal transition (IMT) in vanadium dioxide (VO2) is performed with a lateral resolution of 50 nm through near-field scanning microwave microscopy (SMM) at 16 GHz. SMM is used to measure spatially resolved electronic properties of the phase coexistence in an unstrained VO2 film during the electrically as well as thermally induced IMT. A quantitative impedance map of both the electrically driven filamentary conduction and the thermally induced bulk transition is established. This was modeled as a 2-D heterogeneous resistive network where the distribution function of the IMT temperature across the sample is captured. Applying the resistive network model for the electrically induced IMT case, we reproduce the filamentary nature of electronically induced IMT, which elucidates a cascading avalanche effect triggered by the local electric field across nanoscale insulating and metallic domains.

Observation of the nonlocal spin-orbital effective field.

The spin-orbital interaction in heavy nonmagnetic metal/ferromagnetic metal bilayer systems has attracted great attention and exhibited promising potentials in magnetic logic devices, where the magnetization direction is controlled by passing an electric current. It is found that the spin-orbital interaction induces both an effective field and torque on the magnetization, which have been attributed to two different origins: the Rashba effect and the spin Hall effect. It requires quantitative analysis to distinguish the two mechanisms. Here we show sensitive spin-orbital effective field measurements up to 10 nm thick ferromagnetic layer and find the effective field rapidly diminishes with the increase of the ferromagnetic layer thickness. We further show that this effective field persists even with the insertion of a copper spacer. The nonlocal measurement suggests that the spin-orbital effective field does not rely on the heavy normal metal/ferromagnetic metal interface.