Tantalum Oxide Memristors Research Articles

Direct Visualization of Charge Migration in Bilayer Tantalum Oxide Films by Multimodal Imaging

AbstractInspired by biological neuromorphic computing, artificial neural networks based on crossbar arrays of bilayer tantalum oxide memristors have shown to be promising alternatives to conventional complementary metal‐oxide‐semiconductor (CMOS) architectures. In order to understand the driving mechanism in these oxide systems, tantalum oxide films are resistively switched by conductive atomic force microscopy (C‐AFM), and subsequently imaged by kelvin probe force microscopy (KPFM) and spatially resolved time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS). These workflows enable induction and analysis of the resistive switching mechanism as well as control over the resistively switched region of the film. In this work it is shown that the resistive switching mechanism is driven by both current and electric field effects. Reversible oxygen motion is enabled by applying low (<1 V) electric fields, while high electric fields generate irreversible breakdown of the material (>1 V). Fully understanding oxygen motion and electrical effects in bilayer oxide memristor systems is a fundamental step toward the adoption of memristors as a neuromorphic computing technology.

Low‐Conductance and Multilevel CMOS‐Integrated Nanoscale Oxide Memristors

AbstractUsing memristors, such as oxide and phase change resistive switches, as tunable resistors to construct analog computing hardware accelerators is gaining keen attention. Such accelerators have demonstrated the potential to significantly outperform digital computers in highly relevant applications such as machine learning and image processing. However, improvements in device‐level performance of memristors, including reducing power consumption and high current–induced metal migration in interconnects, need continued developments. Nanoscaling and complementary metal‐oxide semiconductor (CMOS) integration are also of significant importance in commercialization of such accelerators. Here tantalum oxide memristors scaled down to 25 nm sizes and integrated on CMOS transistor circuits are presented. The memristor conductance is programmable with a 6 order‐of‐magnitude operating range, especially with 3‐bits below 10 µS for low current operation. The stability of such levels and the size scaling of the operating parameters are further studied. These results will aid device engineering of memristors and bolster development of neuromorphic hardware accelerators.

Characteristics and transport mechanisms of triple switching regimes of TaOx memristor

While tantalum oxide (TaOx) memristors have shown superior multilevel switching performances and emerged as one of the leading candidates for analog memory and neuromorphic applications, its microscopic switching mechanisms at different resistance regimes remain obscure. In this work, electron transport mechanisms of TaOx memristors have been revealed by analyzing transport characteristics in three different resistance switching regimes. A quantum point contact model coupled with a first principles calculation has been validated to account for different conduction behaviors, which further sheds light on the evolution of the conducting filaments during switching processes. The high endurance observed in the low resistance switching regime is rationalized based on the observation of an enhanced instability and noise in the presence of a single conduction channel, i.e., quantum conductance G0=2e2/h.

Temperature and field-dependent transport measurements in continuously tunable tantalum oxide memristors expose the dominant state variable

Applications of memristor devices are quickly moving beyond computer memory to areas of analog and neuromorphic computation. These applications require the design of devices with different characteristics from binary memory, such as a large tunable range of conductance. A complete understanding of the conduction mechanisms and their corresponding state variable(s) is crucial for optimizing performance and designs in these applications. Here we present measurements of low bias I–V characteristics of 6 states in a Ta/ tantalum-oxide (TaOx)/Pt memristor spanning over 2 orders of magnitude in conductance and temperatures from 100 K to 500 K. Our measurements show that the 300 K device conduction is dominated by a temperature-insensitive current that varies with non-volatile memristor state, with an additional leakage contribution from a thermally-activated current channel that is nearly independent of the memristor state. We interpret these results with a parallel conduction model of Mott hopping and Schottky emission channels, fitting the voltage and temperature dependent experimental data for all memristor states with only two free parameters. The memristor conductance is linearly correlated with N, the density of electrons near EF participating in the Mott hopping conduction, revealing N to be the dominant state variable for low bias conduction in this system. Finally, we show that the Mott hopping sites can be ascribed to oxygen vacancies, where the local oxygen vacancy density responsible for critical hopping pathways controls the memristor conductance.

Evaluating Resistive Memory Devices for Neuromorphic Computing Using Ultrashort Voltage Pulses

A special purpose neural algorithm accelerator based on resistive memory could potentially reduce the energy requirements of neural algorithm implementation by six orders of magnitude over conventional general purpose GPU/CPU hardware (1). The device requirements for such a neural algorithm accelerator depend on attributes including write variability, write linearity, and read noise, as described in reference (2). Devices with multiple resistance states accessible via symmetric voltage pulses of constant magnitude are highly desired for neuromorphic hardware implementations. Tantalum oxide resistive memory devices have been previously shown to have low energy requirements and better control of conductivity during switching in the ultrashort time domain (3). We will report on how employing voltage pulses with ultrashort pulse widths allow for finer control of tantalum oxide based device conductance change per pulse (ΔG/G) unlocking additional neuromorphic states. A parameter space of pulse voltage and time is used to elucidate switching kinetics and switching energy expenditure during device operation. Lastly, the performance of several different resistive memory device structures will be comparatively evaluated for suitability in implementing a neural algorithm accelerator. This work was supported by Sandia National Laboratories’ Laboratory Directed Research and Development (LDRD) Program under the Hardware Acceleration of Adaptive Neural Algorithms Grand Challenge. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-AC04-94AL85000. REFERENCES: 1. Kadetotad, Deepak, et al. "Parallel architecture with resistive crosspoint array for dictionary learning acceleration." IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 5.2 (2015): 194-204. 2. S. Agarwal, et. al. “Resistive Memory Device Requirements for a Neural Algorithm Accelerator,” International Joint Conference on Neural Networks, (2016) 3. Strachan, John Paul, et al. “Measuring the switching dynamics and energy efficiency of tantalum oxide memristors” Nanotechnology22.50 (2011): 505402. Figure 1

Quantized conductance coincides with state instability and excess noise in tantalum oxide memristors.

Tantalum oxide memristors can switch continuously from a low-conductance semiconducting to a high-conductance metallic state. At the boundary between these two regimes are quantized conductance states, which indicate the formation of a point contact within the oxide characterized by multistable conductance fluctuations and enlarged electronic noise. Here, we observe diverse conductance-dependent noise spectra, including a transition from 1/f2 (activated transport) to 1/f (flicker noise) as a function of the frequency f, and a large peak in the noise amplitude at the conductance quantum GQ=2e2/h, in contrast to suppressed noise at the conductance quantum observed in other systems. We model the stochastic behaviour near the point contact regime using Molecular Dynamics–Langevin simulations and understand the observed frequency-dependent noise behaviour in terms of thermally activated atomic-scale fluctuations that make and break a quantum conductance channel. These results provide insights into switching mechanisms and guidance to device operating ranges for different applications.

Memristors: Direct Observation of Localized Radial Oxygen Migration in Functioning Tantalum Oxide Memristors (Adv. Mater. 14/2016)

Memristors: Direct Observation of Localized Radial Oxygen Migration in Functioning Tantalum Oxide Memristors (Adv. Mater. 14/2016)

Direct Observation of Localized Radial Oxygen Migration in Functioning Tantalum Oxide Memristors.

Oxygen migration in tantalum oxide, a promising next-generation storage material, is studied using in operando X-ray absorption spectromicroscopy. This approach allows a physical description of the evolution of conduction channel and eventual device failure. The observed ring-like patterns of oxygen concentration are modeled using thermophoretic forces and Fick diffusion, establishing the critical role of temperature-driven oxygen migration.

In-operando synchronous time-multiplexed O K-edge x-ray absorption spectromicroscopy of functioning tantalum oxide memristors

Memristors are receiving keen interest because of their potential varied applications and promising large-scale information storage capabilities. Tantalum oxide is a memristive material that has shown promise for high-performance nonvolatile computer memory. The microphysics has been elusive because of the small scale and subtle physical changes that accompany conductance switching. In this study, we probed the atomic composition, local chemistry, and electronic structure of functioning tantalum oxide memristors through spatially mapped O K-edge x-ray absorption. We developed a time-multiplexed spectromicroscopy technique to enhance the weak and possibly localized oxide modifications with spatial and spectral resolutions of <30 nm and 70 meV, respectively. During the initial stages of conductance switching of a micrometer sized crosspoint device, the spectral changes were uniform within the spatial resolution of our technique. When the device was further driven with millions of high voltage-pulse cycles, we observed lateral motion and separation of ∼100 nm-scale agglomerates of both oxygen interstitials and vacancies. We also demonstrate a unique capability of this technique by identifying the relaxation behavior in the material during electrical stimuli by identifying electric field driven changes with varying pulse widths. In addition, we show that changes to the material can be localized to a spatial region by modifying its topography or uniformity, as against spatially uniform changes observed here during memristive switching. The goal of this report is to introduce the capability of time-multiplexed x-ray spectromicroscopy in studying weak-signal transitions in inhomogeneous media through the example of the operation and temporal evolution of a memristor.

The Susceptibility of <formula formulatype="inline"> <tex Notation="TeX">${\hbox {TaO}}_{\rm x}$</tex></formula>-Based Memristors to High Dose Rate Ionizing Radiation and Total Ionizing Dose

This paper investigates the effects of high dose rate ionizing radiation and total ionizing dose (TID) on tantalum oxide (TaOx) memristors. Transient data were obtained during the pulsed exposures for dose rates ranging from approximately 5.0 ×107 rad(Si)/s to 4.7 ×108 rad(Si)/s and for pulse widths ranging from 50 ns to 50 μs. The cumulative dose in these tests did not appear to impact the observed dose rate response. Static dose rate upset tests were also performed at a dose rate of ~3.0 ×108 rad(Si)/s. This is the first dose rate study on any type of memristive memory technology. In addition to assessing the tolerance of TaOx memristors to high dose rate ionizing radiation, we also evaluated their susceptibility to TID. The data indicate that it is possible for the devices to switch from a high resistance off-state to a low resistance on-state in both dose rate and TID environments. The observed radiation-induced switching is dependent on the irradiation conditions and bias configuration. Furthermore, the dose rate or ionizing dose level at which a device switches resistance states varies from device to device; the enhanced susceptibility observed in some devices is still under investigation. As a result, numerical simulations aremore » used to qualitatively capture the observed transient radiation response and provide insight into the physics of the induced current/voltages.« less

Tuning resistive switching characteristics of tantalum oxide memristors through Si doping.

An oxide memristor device changes its internal state according to the history of the applied voltage and current. The principle of resistive switching (RS) is based on ion transport (e.g., oxygen vacancy redistribution). To date, devices with bi-, triple-, or even quadruple-layered structures have been studied to achieve the desired switching behavior through device structure optimization. In contrast, the device performance can also be tuned through fundamental atomic-level design of the switching materials, which can directly affect the dynamic transport of ions and lead to optimized switching characteristics. Here, we show that doping tantalum oxide memristors with silicon atoms can facilitate oxygen vacancy formation and transport in the switching layer with adjustable ion hopping distance and drift velocity. The devices show larger dynamic ranges with easier access to the intermediate states while maintaining the extremely high cycling endurance (>10(10) set and reset) and are well-suited for neuromorphic computing applications. As an example, we demonstrate different flavors of spike-timing-dependent plasticity in this memristor system. We further provide a characterization methodology to quantitatively estimate the effective hopping distance of the oxygen vacancies. The experimental results are confirmed through detailed ab initio calculations which reveal the roles of dopants and provide design methodology for further optimization of the RS behavior.

Rutherford forward scattering and elastic recoil detection (RFSERD) as a method for characterizing ultra-thin films

We present a novel ion beam analysis technique combining Rutherford forward scattering and elastic recoil detection (RFSERD) and demonstrate its ability to increase efficiency in determining stoichiometry in ultrathin (5–50nm) films as compared to Rutherford backscattering. In the conventional forward geometries, scattering from the substrate overwhelms the signal from light atoms but in RFSERD, scattered ions from the substrate are ranged out while forward scattered ions and recoiled atoms from the thin film are simultaneously detected in a single detector. The technique is applied to tantalum oxide memristors but can be extended to a wide range of materials systems.

State Dynamics and Modeling of Tantalum Oxide Memristors

A key requirement for using memristors in circuits is a predictive model for device behavior that can be used in simulations and to guide designs. We analyze one of the most promising materials, tantalum oxide, for high density, low power, and high-speed memory. We perform an ensemble of measurements, including time dynamics across nine decades, to deduce the underlying state equations describing the switching in Pt/TaO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> /Ta memristors. A predictive, compact model is found in good agreement with the measured data. The resulting model, compatible with SPICE, is then used to understand trends in terms of switching times and energy consumption, which in turn are important for choosing device operating points and handling interactions with other circuit elements.

Measuring the switching dynamics and energy efficiency of tantalum oxide memristors

We measured the real-time switching of metal–oxide memristors with sub-nanosecondresolution and recorded the evolution of the current and voltage during both ON (set) andOFF (reset) events. From these we determined the dynamical behavior of the conductivityfor different applied bias amplitudes. Quantitative analysis of the energy cost andswitching dynamics showed 115 fJ for ON-switching and 13 pJ for OFF-switching whenresistance change was limited to 200%. Results are presented that show a favorablescaling with speed in terms of energy cost and reducing unnecessary damage to thedevices.