Synchronized charge oscillations in correlated electron systems

Demonstration of an energy-efficient Ising solver composed of Ovonic threshold switch (OTS)-based nano-oscillators (OTSNOs)

As there is an increasing need for an efficient solver of combinatorial optimization problems, much interest is paid to the Ising machine, which is a novel physics-driven computing system composed of coupled oscillators mimicking the dynamics of the system of coupled electronic spins. In this work, we propose an energy-efficient nano-oscillator, called OTSNO, which is composed of an Ovonic Threshold Switch (OTS) and an electrical resistor. We demonstrate that the OTSNO shows the synchronization behavior, an essential property for the realization of an Ising machine. Furthermore, we have discovered that the capacitive coupling is advantageous over the resistive coupling for the hardware implementation of an Ising solver by providing a larger margin of the variations of components. Finally, we implement an Ising machine composed of capacitively-coupled OTSNOs to demonstrate that the solution to a 14-node MaxCut problem can be obtained in 40 µs while consuming no more than 2.3 µJ of energy. Compared to a previous hardware implementation of the phase-transition nano-oscillator (PTNO)-based Ising machine, the OTSNO-based Ising machine in this work shows the performance of the increased speed by more than one order while consuming less energy by about an order.

Physical Origin of Negative Differential Resistance in V3 O5 and Its Application as a Solid-State Oscillator

Oxides that exhibit an insulator-metal transition can be used to fabricate energy-efficient relaxation oscillators for use in hardware-based neural networks but there are very few oxides with transition temperatures above room temperature. Here the structural, electrical, and thermal properties of V₃ O₅ thin films and their application as the functional oxide in metal/oxide/metal relaxation oscillators are reported. The V₃ O₅ devices show electroforming-free volatile threshold switching and negative differential resistance (NDR) with stable (<3% variation) cycle-to-cycle operation. The physical mechanisms underpinning these characteristics are investigated using a combination of electrical measurements, in situ thermal imaging, and device modeling. This shows that conduction is confined to a narrow filamentary path due to self-confinement of the current distribution and that the NDR response is initiated at temperatures well below the insulator-metal transition temperature where it is dominated by the temperature-dependent conductivity of the insulating phase. Finally, the dynamics of individual and coupled V₃ O₅ -based relaxation oscillators is reported, showing that capacitively coupled devices exhibit rich non-linear dynamics, including frequency and phase synchronization. These results establish V₃ O₅ as a new functional material for volatile threshold switching and advance the development of robust solid-state neurons for neuromorphic computing.

Hyper-FET's Phase-Transition-Materials Design Guidelines for Ultra-Low Power Applications at 3 nm Technology Node

In this work, a hybrid-phase transition field-effects-transistor (hyper-FET) integrated with phase-transition materials (PTM) and a multi-nanosheet FET (mNS-FET) at the 3 nm technology node were analyzed at the device and circuit level. Through this, a benchmark was performed for presenting device design guidelines and for using ultra-low-power applications. We present an optimization flow considering hyper-FET characteristics at the device and circuit level, and analyze hyper-FET performance according to the phase transition time (TT) and baseline-FET off-leakage current (I_OFF) variations of the PTM. As a result of inverter ring oscillator (INV RO) circuit analysis, the optimized hyper-FET increases speed by +8.74% and reduces power consumption by -16.55%, with I_OFF = 5 nA of baseline-FET and PTM TT = 50 ps compared to the conventional mNS-FET in the ultra-low-power region. As a result of SRAM circuit analysis, the read static noise margin is improved by 43.9%, and static power is reduced by 58.6% in the near-threshold voltage region when the PTM is connected to the pull-down transistor source terminal of 6T SRAM for high density. This is achieved at 41% read current penalty.

Role of ambient temperature in modulation of behavior of vanadium dioxide volatile memristors and oscillators for neuromorphic applications

Volatile memristors are versatile devices whose operating mechanism is based on an abrupt and volatile change of resistivity. This switching between high and low resistance states is at the base of cutting edge technological implementations such as neural/synaptic devices or random number generators. A detailed understanding of this operating mechanisms is essential prerequisite to exploit the full potentiality of volatile memristors. In this respect, multi-physics device simulations provide a powerful tool to single out material properties and device features that are the keys to achieve desired behaviors. In this paper, we perform 3D electrothermal simulations of volatile memristors based on vanadium dioxide (VO[Formula: see text]) to accurately investigate the interplay among Joule effect, heat dissipation and the external temperature [Formula: see text] over their resistive switching mechanism. In particular, we extract from our simulations a simplified model for the effect of [Formula: see text] over the negative differential resistance (NDR) region of such devices. The NDR of VO[Formula: see text] devices is pivotal for building VO[Formula: see text] oscillators, which have been recently shown to be essential elements of oscillatory neural networks (ONNs). ONNs are innovative neuromorphic circuits that harness oscillators' phases to compute. Our simulations quantify the impact of [Formula: see text] over figures of merit of VO[Formula: see text] oscillator, such as frequency, voltage amplitude and average power per cycle. Our findings shed light over the interlinked thermal and electrical behavior of VO[Formula: see text] volatile memristors and oscillators, and provide a roadmap for the development of ONN technology.

How Frequency Injection Locking Can Train Oscillatory Neural Networks to Compute in Phase

Brain-inspired computing employs devices and architectures that emulate biological functions for more adaptive and energy-efficient systems. Oscillatory neural networks (ONNs) are an alternative approach in emulating biological functions of the human brain and are suitable for solving large and complex associative problems. In this work, we investigate the dynamics of coupled oscillators to implement such ONNs. By harnessing the complex dynamics of coupled oscillatory systems, we forge a novel computation model-information is encoded in the phase of oscillations. Coupled interconnected oscillators can exhibit various behaviors due to the strength of the coupling. In this article, we present a novel method based on subharmonic injection locking (SHIL) for controlling the oscillatory states of coupled oscillators that allow them to lock in frequency with distinct phase differences. Circuit-level simulation results indicate SHIL effectiveness and its applicability to large-scale oscillatory networks for pattern recognition.

A three-terminal non-volatile ferroelectric switch with an insulator-metal transition channel

Ferroelectrics offer a promising material platform to realize energy-efficient non-volatile memory technology with the FeFET-based implementations being one of the most area-efficient ferroelectric memory architectures. However, the FeFET operation entails a fundamental trade-off between the read and the program operations. To overcome this trade-off, we propose in this work, a novel device concept, Mott-FeFET, that aims to replace the Silicon channel of the FeFET with VO₂- a material that exhibits an electrically driven insulator-metal phase transition. The Mott-FeFET design, which demonstrates a (ferroelectric) polarization-dependent threshold voltage, enables the read current distinguishability (i.e., the ratio of current sensed when the Mott-FeFET is in state 1 and 0, respectively) to be independent of the program voltage. This enables the device to be programmed at low voltages without affecting the ability to sense/read the state of the device. Our work provides a pathway to realize low-voltage and energy-efficient non-volatile memory solutions.

Hardware Implementation of Differential Oscillatory Neural Networks Using VO 2-Based Oscillators and Memristor-Bridge Circuits

Oscillatory Neural Networks (ONNs) are currently arousing interest in the research community for their potential to implement very fast, ultra-low-power computing tasks by exploiting specific emerging technologies. From the architectural point of view, ONNs are based on the synchronization of oscillatory neurons in cognitive processing, as occurs in the human brain. As emerging technologies, VO₂ and memristive devices show promising potential for the efficient implementation of ONNs. Abundant literature is now becoming available pertaining to the study and building of ONNs based on VO₂ devices and resistive coupling, such as memristors. One drawback of direct resistive coupling is that physical resistances cannot be negative, but from the architectural and computational perspective this would be a powerful advantage when interconnecting weights in ONNs. Here we solve the problem by proposing a hardware implementation technique based on differential oscillatory neurons for ONNs (DONNs) with VO₂-based oscillators and memristor-bridge circuits. Each differential oscillatory neuron is made of a pair of VO₂ oscillators operating in anti-phase. This way, the neurons provide a pair of differential output signals in opposite phase. The memristor-bridge circuit is used as an adjustable coupling function that is compatible with differential structures and capable of providing both positive and negative weights. By combining differential oscillatory neurons and memristor-bridge circuits, we propose the hardware implementation of a fully connected differential ONN (DONN) and use it as an associative memory. The standard Hebbian rule is used for training, and the weights are then mapped to the memristor-bridge circuit through a proposed mapping rule. The paper also introduces some functional and hardware specifications to evaluate the design. Evaluation is performed by circuit-level electrical simulations and shows that the retrieval accuracy of the proposed design is comparable to that of classic Hopfield Neural Networks.

Universal phase dynamics in VO2 switches revealed by ultrafast operando diffraction

Understanding the pathways and time scales underlying electrically driven insulator-metal transitions is crucial for uncovering the fundamental limits of device operation. Using stroboscopic electron diffraction, we perform synchronized time-resolved measurements of atomic motions and electronic transport in operating vanadium dioxide (VO₂) switches. We discover an electrically triggered, isostructural state that forms transiently on microsecond time scales, which is shown by phase-field simulations to be stabilized by local heterogeneities and interfacial interactions between the equilibrium phases. This metastable phase is similar to that formed under photoexcitation within picoseconds, suggesting a universal transformation pathway. Our results establish electrical excitation as a route for uncovering nonequilibrium and metastable phases in correlated materials, opening avenues for engineering dynamical behavior in nanoelectronics.

Using synchronized oscillators to compute the maximum independent set

Not all computing problems are created equal. The inherent complexity of processing certain classes of problems using digital computers has inspired the exploration of alternate computing paradigms. Coupled oscillators exhibiting rich spatio-temporal dynamics have been proposed for solving hard optimization problems. However, the physical implementation of such systems has been constrained to small prototypes. Consequently, the computational properties of this paradigm remain inadequately explored. Here, we demonstrate an integrated circuit of thirty oscillators with highly reconfigurable coupling to compute optimal/near-optimal solutions to the archetypally hard Maximum Independent Set problem with over 90% accuracy. This platform uniquely enables us to characterize the dynamical and computational properties of this hardware approach. We show that the Maximum Independent Set is more challenging to compute in sparser graphs than in denser ones. Finally, using simulations we evaluate the scalability of the proposed approach. Our work marks an important step towards enabling application-specific analog computing platforms to solve computationally hard problems.

Designing efficient analog dynamical systems for solving hard optimization problems remains a challenge. Here, the authors demonstrate a dynamical system of thirty oscillators with reconfigurable coupling to compute optimal/near-optimal solutions to the hard Maximum Independent Set problem with over 90% accuracy.

Variable spin-charge conversion across metal-insulator transition

The charge-to-spin conversion efficiency is a crucial parameter in determining the performance of many useful spintronic materials. Usually, this conversion efficiency is predetermined by the intrinsic nature of solid-state materials, which cannot be easily modified without invoking chemical or structural changes in the underlying system. Here we report on successful modulation of charge-spin conversion efficiency via the metal-insulator transition in a quintessential strongly correlated electron compound vanadium dioxide (VO₂). By employing ferromagnetic resonance driven spin pumping and the inverse spin Hall effect measurement, we find a dramatic change in the spin pumping signal (decrease by > 80%) and charge-spin conversion efficiency (increase by five times) upon insulator to metal transition. The abrupt change in the structural and electrical properties of this material therefore provides useful insights on the spin related physics in a strongly correlated material undergoing a phase transition.

The interconversion of spin and charge is fundamental to the operation of spintronic devices. Here the authors demonstrate spin-to-charge conversion in the correlated material vanadium dioxide, and show that the efficiency changes dramatically across the metal-insulator transition.

Low-Voltage Oscillatory Neurons for Memristor-Based Neuromorphic Systems

Neuromorphic systems consisting of artificial neurons and synapses can process complex information with high efficiency to overcome the bottleneck of von Neumann architecture. Artificial neurons are essentially required to possess functions such as leaky integrate-and-fire and output spike. However, previous reported artificial neurons typically have high operation voltage and large leakage current, leading to significant power consumption, which is contrary to the energy-efficient biological model. Here, an oscillatory neuron based on Ag filamentary threshold switching memristor (TS) that has a low operation voltage (<0.6 V) with ultralow power consumption (<1.8 µW) is presented. It can trigger neuronal functions, including leaky integrate-and-fire and threshold-driven spiking output, with high endurance (>108 cycles). Being connected to an external resistor or a resistive switching memristor (RS) as synaptic weight, the TS clearly demonstrates self-oscillation behavior once the input pulse voltage exceeds the threshold voltage. Meanwhile, the oscillation frequency is proportional to the input pulse voltage and the conductance of RS synapse, which can be used to integrate the weighted sum current. As an energy-efficient memristor-based spiking neural network, this combination of TS oscillatory neuron with RS synapse is further evaluated for image recognition achieving an accuracy of 79.2 ± 2.4% for CIFAR-10 subset.

Localized Triggering of the Insulator-Metal Transition in VO2 Using a Single Carbon Nanotube

Vanadium dioxide (VO₂) has been widely studied for its rich physics and potential applications, undergoing a prominent insulator-metal transition (IMT) near room temperature. The transition mechanism remains highly debated, and little is known about the IMT at nanoscale dimensions. To shed light on this problem, here we use ∼1 nm-wide carbon nanotube (CNT) heaters to trigger the IMT in VO₂. Single metallic CNTs switch the adjacent VO₂ at less than half the voltage and power required by control devices without a CNT, with switching power as low as ∼85 μW at 300 nm device lengths. We also obtain potential and temperature maps of devices during operation using Kelvin probe microscopy and scanning thermal microscopy. Comparing these with three-dimensional electrothermal simulations, we find that the local heating of the VO₂ by the CNT plays a key role in the IMT. These results demonstrate the ability to trigger IMT in VO₂ using nanoscale heaters and highlight the significance of thermal engineering to improve device behavior.

Fast Spiking of a Mott VO2-Carbon Nanotube Composite Device

The recent surge of interest in brain-inspired computing and power-efficient electronics has dramatically bolstered development of computation and communication using neuron-like spiking signals. Devices that can produce rapid and energy-efficient spiking could significantly advance these applications. Here we demonstrate direct current or voltage-driven periodic spiking with sub-20 ns pulse widths from a single device composed of a thin VO₂ film with a metallic carbon nanotube as a nanoscale heater, without using an external capacitor. Compared with VO₂-only devices, adding the nanotube heater dramatically decreases the transient duration and pulse energy, and increases the spiking frequency, by up to 3 orders of magnitude. This is caused by heating and cooling of the VO₂ across its insulator-metal transition being localized to a nanoscale conduction channel in an otherwise bulk medium. This result provides an important component of energy-efficient neuromorphic computing systems and a lithography-free technique for energy-scaling of electronic devices that operate via bulk mechanisms.

Large Scale Synthesis of Nanopyramidal-Like VO₂ Films by an Oxygen-Assisted Etching Growth Method with Significantly Enhanced Field Emission Properties

The present investigation reported on a novel oxygen-assisted etching growth method that can directly transform wafer-scale plain VO₂ thin films into pyramidal-like VO₂ nanostructures with highly improved field-emission properties. The oxygen applied during annealing played a key role in the formation of the special pyramidal-like structures by introducing thin oxygen-rich transition layers on the top surfaces of the VO₂ crystals. An etching related growth and transformation mechanism for the synthesis of nanopyramidal films was proposed. Structural characterizations confirmed the formation of a composite VO₂ structure of monoclinic M1 (P21/c) and Mott insulating M2 (C2/m) phases for the films at room temperature. Moreover, by varying the oxygen concentration, the nanocrystal morphology of the VO₂ films could be tuned, ranging over pyramidal, dot, and/or twin structures. These nanopyramidal VO₂ films showed potential benefits for application such as temperature-regulated field emission devices. For one typical sample deposited on a 3-inch silicon substrate, its emission current (measured at 6 V/μm) increased by about 1000 times after the oxygen-etching treatment, and the field enhancement factor β reached as high as 3810 and 1620 for the M and R states, respectively. The simple method reported in the present study may provide a protocol for building a variety of large interesting surfaces for VO₂-based device applications.

Growth without Postannealing of Monoclinic VO2 Thin Film by Atomic Layer Deposition Using VCl4 as Precursor

Vanadium dioxide (VO2) is a multifunctional material with semiconductor-to-metal transition (SMT) property. Organic vanadium compounds are usually employed as ALD precursors to grow VO2 films. However, the as-deposited films are reported to have amorphous structure with no significant SMT property, therefore a postannealing process is necessary for converting the amorphous VO2 to crystalline VO2. In this study, an inorganic vanadium tetrachloride (VCl4) is used as an ALD precursor for the first time to grow VO2 films. The VO2 film is directly crystallized and grown on the substrate without any postannealing process. The VO2 film displays significant SMT behavior, which is verified by temperature-dependent Raman spectrometer and four-point-probing system. The results demonstrate that the VCl4 is suitably employed as a new ALD precursor to grow crystallized VO2 films. It can be reasonably imagined that the VCl4 can also be used to grow various directly crystallized vanadium oxides by controlling the ALD-process parameters.

A New Method of the Pattern Storage and Recognition in Oscillatory Neural Networks Based on Resistive Switches

Development of neuromorphic systems based on new nanoelectronics materials and devices is of immediate interest for solving the problems of cognitive technology and cybernetics. Computational modeling of two- and three-oscillator schemes with thermally coupled VO2-switches is used to demonstrate a novel method of pattern storage and recognition in an impulse oscillator neural network (ONN), based on the high-order synchronization effect. The method allows storage of many patterns, and their number depends on the number of synchronous states Ns. The modeling demonstrates attainment of Ns of several orders both for a three-oscillator scheme Ns ~ 650 and for a two-oscillator scheme Ns ~ 260. A number of regularities are obtained, in particular, an optimal strength of oscillator coupling is revealed when Ns has a maximum. Algorithms of vector storage, network training, and test vector recognition are suggested, where the parameter of synchronization effectiveness is used as a degree of match. It is shown that, to reduce the ambiguity of recognition, the number coordinated in each vector should be at least one unit less than the number of oscillators. The demonstrated results are of a general character, and they may be applied in ONNs with various mechanisms and oscillator coupling topology.

Anatomy of filamentary threshold switching in amorphous niobium oxide

The threshold switching behavior of Pt/NbO _x /TiN devices is investigated as a function device area and NbO _x film thickness and shown to reveal important insight into the structure of the self-assembled switching region. The devices exhibit combined selector-memory (1S1R) behavior after an initial voltage-controlled forming process, but exhibit symmetric threshold switching when the RESET and SET currents are kept below a critical value. In this mode, the threshold and hold voltages are independent of the device area and film thickness but the threshold current (power), while independent of device area, decreases with increasing film thickness. These results are shown to be consistent with a structure in which the threshold switching volume is confined, both laterally and vertically, to the region between the residual memory filament and the TiN electrode, and where the memory filament has a core-shell structure comprising a metallic core and a semiconducting shell. The veracity of this structure is demonstrated by comparing experimental results with the predictions of a simple circuit model, and more detailed finite element simulations. These results provide further insight into the structure and operation of NbO _x threshold switching devices that have application in emerging memory and neuromorphic computing fields.

Tuning the synchronization of a network of weakly coupled self-oscillating gels via capacitors

We consider a network of coupled oscillating units, where each unit comprises a self-oscillating polymer gel undergoing the Belousov-Zhabotinsky (BZ) reaction and an overlaying piezoelectric (PZ) cantilever. Through chemo-mechano-electrical coupling, the oscillations of the networked BZ-PZ units achieve in-phase or anti-phase synchronization, enabling, for example, the storage of information within the system. Herein, we develop numerical and computational models to show that the introduction of capacitors into the BZ-PZ system enhances the dynamical behavior of the oscillating network by yielding additional stable synchronization modes. We specifically show that the capacitors lead to a redistribution of charge in the system and alteration of the force that the PZ cantilevers apply to the underlying gel. Hence, the capacitors modify the strength of the coupling between the oscillators in the network. We utilize a linear stability analysis to determine the phase behavior of BZ-PZ networks encompassing different capacitances, force polarities, and number of units and then verify our findings with numerical simulations. Thus, through analytical calculations and numerical simulations, we determine the impact of the capacitors on the existence of the synchronization modes, their stability, and the rate of synchronization within these complex dynamical systems. The findings from our study can be used to design robotic materials that harness the materials' intrinsic, responsive properties to perform such functions as sensing, actuation, and information storage.

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.

Selective High-Frequency Mechanical Actuation Driven by the VO2 Electronic Instability

Relaxation oscillators consist of periodic variations of a physical quantity triggered by a static excitation. They are a typical consequence of nonlinear dynamics and can be observed in a variety of systems. VO₂ is a correlated oxide with a solid-state phase transition above room temperature, where both electrical resistance and lattice parameters undergo a drastic change in a narrow temperature range. This strong nonlinear response allows to realize spontaneous electrical oscillations in the megahertz range under a DC voltage bias. These electrical oscillations are employed to set into mechanical resonance a microstructure without the need of any active electronics, with small power consumption and with the possibility to selectively excite specific flexural modes by tuning the value of the DC electrical bias in a range of few hundreds of millivolts. This actuation method is robust and flexible and can be implemented in a variety of autonomous DC-powered devices.

Samarium Monosulfide (SmS): Reviewing Properties and Applications

In this review, we give an overview of the properties and applications of samarium monosulfide, SmS, which has gained considerable interest as a switchable material. It shows a pressure-induced phase transition from the semiconducting to the metallic state by polishing, and it switches back to the semiconducting state by heating. The material also shows a magnetic transition, from the paramagnetic state to an antiferromagnetically ordered state. The switching behavior between the semiconducting and metallic states could be exploited in several applications, such as high density optical storage and memory materials, thermovoltaic devices, infrared sensors and more. We discuss the electronic, optical and magnetic properties of SmS, its switching behavior, as well as the thin film deposition techniques which have been used, such as e-beam evaporation and sputtering. Moreover, applications and possible ideas for future work on this material are presented. Our scope is to present the properties of SmS, which were mainly measured in bulk crystals, while at the same time we describe the possible deposition methods that will push the study of SmS to nanoscale dimensions, opening an intriguing range of applications for low-dimensional, pressure-induced semiconductor-metal transition compounds.

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.

Coupling dynamics of Nb/Nb2O5 relaxation oscillators

The coupling dynamics of capacitively coupled Nb/Nb₂O₅ relaxation oscillators are shown to exhibit rich collective behaviour depending on the negative differential resistance response of the individual devices, the operating voltage and the coupling capacitance. These coupled oscillators are shown to exhibit stable frequency and phase locking states at source voltages as low as 2.2 V, with frequency control in the range from 0.85 to 16.2 MHz and frequency tunability of ∼8 MHz V^-1. The experimental realisation of such compact, scalable and low power coupled-oscillator systems is of particular significance for the development and implementation of large oscillator networks in non-Boolean computing architectures.

A Steep-Slope Transistor Combining Phase-Change and Band-to-Band-Tunneling to Achieve a sub-Unity Body Factor

Steep-slope transistors allow to scale down the supply voltage and the energy per computed bit of information as compared to conventional field-effect transistors (FETs), due to their sub-60 mV/decade subthreshold swing at room temperature. Currently pursued approaches to achieve such a subthermionic subthreshold swing consist in alternative carrier injection mechanisms, like quantum mechanical band-to-band tunneling (BTBT) in Tunnel FETs or abrupt phase-change in metal-insulator transition (MIT) devices. The strengths of the BTBT and MIT have been combined in a hybrid device architecture called phase-change tunnel FET (PC-TFET), in which the abrupt MIT in vanadium dioxide (VO₂) lowers the subthreshold swing of strained-silicon nanowire TFETs. In this work, we demonstrate that the principle underlying the low swing in the PC-TFET relates to a sub-unity body factor achieved by an internal differential gate voltage amplification. We study the effect of temperature on the switching ratio and the swing of the PC-TFET, reporting values as low as 4.0 mV/decade at 25 °C, 7.8 mV/decade at 45 °C. We discuss how the unique characteristics of the PC-TFET open new perspectives, beyond FETs and other steep-slope transistors, for low power electronics, analog circuits and neuromorphic computing.

The structures of interstitial hydrogen centers in VO2 in the dilute limit from their vibrational properties and theory

The introduction of a large concentration of H into VO2 is known to suppress the insulating phase of the metal-insulator transition that occurs upon cooling below 340 K. We have used infrared spectroscopy and complementary theory to study the properties of interstitial H and D in VO2 in the dilute limit to determine the vibrational frequencies, thermal stabilities, and equilibrium positions of isolated interstitial H and D centers. The vibrational lines of several OH and OD centers were observed to have thermal stabilities similar to that of the hydrogen that suppresses the insulating phase. Theory associates two of the four possible OH configurations for Hi in the insulating VO2 monoclinic phase with OH lines seen by experiment. Furthermore, theory predicts the energies and vibrational frequencies for configurations with Hi trapped near a substitutional impurity and suggests such defects as candidates for additional OH centers that have been observed.

A charge-density-wave oscillator based on an integrated tantalum disulfide-boron nitride-graphene device operating at room temperature

The charge-density-wave (CDW) phase is a macroscopic quantum state consisting of a periodic modulation of the electronic charge density accompanied by a periodic distortion of the atomic lattice in quasi-1D or layered 2D metallic crystals. Several layered transition metal dichalcogenides, including 1T-TaSe₂, 1T-TaS₂ and 1T-TiSe₂ exhibit unusually high transition temperatures to different CDW symmetry-reducing phases. These transitions can be affected by the environmental conditions, film thickness and applied electric bias. However, device applications of these intriguing systems at room temperature or their integration with other 2D materials have not been explored. Here, we demonstrate room-temperature current switching driven by a voltage-controlled phase transition between CDW states in films of 1T-TaS₂ less than 10 nm thick. We exploit the transition between the nearly commensurate and the incommensurate CDW phases, which has a transition temperature of 350 K and gives an abrupt change in current accompanied by hysteresis. An integrated graphene transistor provides a voltage-tunable, matched, low-resistance load enabling precise voltage control of the circuit. The 1T-TaS₂ film is capped with hexagonal boron nitride to provide protection from oxidation. The integration of these three disparate 2D materials in a way that exploits the unique properties of each yields a simple, miniaturized, voltage-controlled oscillator suitable for a variety of practical applications.

Joule Heating-Induced Metal-Insulator Transition in Epitaxial VO2/TiO2 Devices

DC and pulse voltage-induced metal-insulator transition (MIT) in epitaxial VO2 two terminal devices were measured at various stage temperatures. The power needed to switch the device to the ON-state decrease linearly with increasing stage temperature, which can be explained by the Joule heating effect. During transient voltage induced MIT measurement, the incubation time varied across 6 orders of magnitude. Both DC I-V characteristic and incubation times calculated from the electrothermal simulations show good agreement with measured values, indicating Joule heating effect is the cause of MIT with no evidence of electronic effects. The width of the metallic filament in the ON-state of the device was extracted and simulated within the thermal model.

Wafer-scale growth of VO2 thin films using a combinatorial approach

Transition metal oxides offer functional properties beyond conventional semiconductors. Bridging the gap between the fundamental research frontier in oxide electronics and their realization in commercial devices demands a wafer-scale growth approach for high-quality transition metal oxide thin films. Such a method requires excellent control over the transition metal valence state to avoid performance deterioration, which has been proved challenging. Here we present a scalable growth approach that enables a precise valence state control. By creating an oxygen activity gradient across the wafer, a continuous valence state library is established to directly identify the optimal growth condition. Single-crystalline VO₂ thin films have been grown on wafer scale, exhibiting more than four orders of magnitude change in resistivity across the metal-to-insulator transition. It is demonstrated that ‘electronic grade' transition metal oxide films can be realized on a large scale using a combinatorial growth approach, which can be extended to other multivalent oxide systems.

Precise valence state control to avoid performance deterioration in transition metal oxide films has proved challenging. Here, the authors establish a combinatorial approach to create a valence state library of VO₂, allowing for the growth of wafer size VO₂ thin films.

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.