Reliability effects of lateral filament confinement by nano-scaling the oxide in memristive devices.

Write-variability and resistance instability are major reliability concerns impeding implementation of oxide-based memristive devices in neuromorphic systems. The root cause of the reliability issues is the stochastic nature of conductive filament formation and dissolution, whose impact is particularly critical in the high resistive state (HRS). Optimizing the filament stability requires mitigating diffusive processes within the oxide, but these are unaffected by conventional electrode scaling. Here we propose a device design that laterally confines the switching oxide volume and thus the filament to 10 nm, which yields reliability improvements in our measurements and simulations. We demonstrate a 50% decrease in HRS write-variability for an oxide nano-fin device in our full factorial analysis of modulated current-voltage sweeps. Furthermore, we use ionic noise measurements to quantify the HRS filament stability against diffusive processes. The laterally confined filaments exhibit a change in the signal-to-noise ratio distribution with a shift to higher values. Our complementing kinetic Monte Carlo simulation of oxygen vacancy (re-)distribution for confined filaments shows improved noise behavior and elucidates the underlying physical mechanisms. While lateral oxide volume scaling down to filament sizes is challenging, our efforts motivate further examination and awareness of filament confinement effects in regards to reliability.

Coherent noise enables probabilistic sequence replay in spiking neuronal networks.

Animals rely on different decision strategies when faced with ambiguous or uncertain cues. Depending on the context, decisions may be biased towards events that were most frequently experienced in the past, or be more explorative. A particular type of decision making central to cognition is sequential memory recall in response to ambiguous cues. A previously developed spiking neuronal network implementation of sequence prediction and recall learns complex, high-order sequences in an unsupervised manner by local, biologically inspired plasticity rules. In response to an ambiguous cue, the model deterministically recalls the sequence shown most frequently during training. Here, we present an extension of the model enabling a range of different decision strategies. In this model, explorative behavior is generated by supplying neurons with noise. As the model relies on population encoding, uncorrelated noise averages out, and the recall dynamics remain effectively deterministic. In the presence of locally correlated noise, the averaging effect is avoided without impairing the model performance, and without the need for large noise amplitudes. We investigate two forms of correlated noise occurring in nature: shared synaptic background inputs, and random locking of the stimulus to spatiotemporal oscillations in the network activity. Depending on the noise characteristics, the network adopts various recall strategies. This study thereby provides potential mechanisms explaining how the statistics of learned sequences affect decision making, and how decision strategies can be adjusted after learning.

A high throughput generative vector autoregression model for stochastic synapses.

By imitating the synaptic connectivity and plasticity of the brain, emerging electronic nanodevices offer new opportunities as the building blocks of neuromorphic systems. One challenge for large-scale simulations of computational architectures based on emerging devices is to accurately capture device response, hysteresis, noise, and the covariance structure in the temporal domain as well as between the different device parameters. We address this challenge with a high throughput generative model for synaptic arrays that is based on a recently available type of electrical measurement data for resistive memory cells. We map this real-world data onto a vector autoregressive stochastic process to accurately reproduce the device parameters and their cross-correlation structure. While closely matching the measured data, our model is still very fast; we provide parallelized implementations for both CPUs and GPUs and demonstrate array sizes above one billion cells and throughputs exceeding one hundred million weight updates per second, above the pixel rate of a 30 frames/s 4K video stream.

Sequence learning, prediction, and replay in networks of spiking neurons.

Sequence learning, prediction and replay have been proposed to constitute the universal computations performed by the neocortex. The Hierarchical Temporal Memory (HTM) algorithm realizes these forms of computation. It learns sequences in an unsupervised and continuous manner using local learning rules, permits a context specific prediction of future sequence elements, and generates mismatch signals in case the predictions are not met. While the HTM algorithm accounts for a number of biological features such as topographic receptive fields, nonlinear dendritic processing, and sparse connectivity, it is based on abstract discrete-time neuron and synapse dynamics, as well as on plasticity mechanisms that can only partly be related to known biological mechanisms. Here, we devise a continuous-time implementation of the temporal-memory (TM) component of the HTM algorithm, which is based on a recurrent network of spiking neurons with biophysically interpretable variables and parameters. The model learns high-order sequences by means of a structural Hebbian synaptic plasticity mechanism supplemented with a rate-based homeostatic control. In combination with nonlinear dendritic input integration and local inhibitory feedback, this type of plasticity leads to the dynamic self-organization of narrow sequence-specific subnetworks. These subnetworks provide the substrate for a faithful propagation of sparse, synchronous activity, and, thereby, for a robust, context specific prediction of future sequence elements as well as for the autonomous replay of previously learned sequences. By strengthening the link to biology, our implementation facilitates the evaluation of the TM hypothesis based on experimentally accessible quantities. The continuous-time implementation of the TM algorithm permits, in particular, an investigation of the role of sequence timing for sequence learning, prediction and replay. We demonstrate this aspect by studying the effect of the sequence speed on the sequence learning performance and on the speed of autonomous sequence replay.

On the role of the metal oxide/reactive electrode interface during the forming procedure of valence change ReRAM devices.

One of the key issues of resistive switching memory devices is the so called "forming" process, a one time process at a high voltage, which initializes the resistive switching at significantly lower voltages. With this study we identify the influence of the different layers - namely the insulating oxide layer (ZrO2 and Ta2O5) and the reactive ohmic electrode layer (Hf, Ta and Pt) - on the forming voltage and the pristine capacitance of the devices. For this, the forming voltage and pristine capacitance is measured in dependence of the oxide layer thickness with different electrodes. The different slopes of the forming voltage - thickness relation for different top electrodes give an indication that the reactive ohmic electrode is oxidized from the oxide layer underneath and that the degree of the oxidation depends on the thickness of the oxide layer as well as the materials used for the oxide and electrode layer. This finding could be confirmed by X-ray photoelectron spectroscopy (XPS) and transmission electron microscopy (TEM) measurements. From the electrical measurements and the TEM images the thickness of the oxidized electrode layer could be estimated. The degree of the oxidation depends on the oxygen affinity of the oxide and electrode material. The interface dependent (thickness independent) part of the forming voltage is determined by the material of the electrode. The magnitude of this interface voltage could be correlated to the oxide free energy of the electrode material. These results can support the ongoing research towards resistive switching memory devices with a very low forming voltage or forming free behaviour.

Metallic filamentary conduction in valence change-based resistive switching devices: the case of TaOx thin film with x∼ 1.

The resistive switching in metal-oxide thin films typically occurs via modulation of the oxygen content in nano-sized conductive filaments. For Ta2O5-based resistive switching devices, the two current models consider filaments composed of oxygen vacancies and those containing metallic Ta clusters. The present work tries to resolve this dispute. The filaments in Ta2O5 were formerly shown to exhibit the same electrical transport mechanisms as TaOx thin films with x∼ 1.0. In this paper, sputtered thin films of pure ß-Ta and of TaOx with different oxygen concentrations are studied and compared in terms of their structure and electrical transport. The structural analysis reveals the presence of Ta clusters in the TaOx films. Identical electrical transport characteristics were observed in the TaOx films with x∼ 1.0 and in the ß-Ta film. Both show the same transport mechanism, a carrier concentration on the order of 1022 cm-3 and a positive magnetoresistance associated with weak antilocalization at T < 30 K. It is concluded that the electrical transport in the TaOx films with x∼ 1.0 is dominated by percolation through Ta clusters. This means that the transport in the filaments is also determined by percolation through Ta clusters, strongly supporting the metallic Ta filament model.

On the universality of the I-V switching characteristics in non-volatile and volatile resistive switching oxides.

The I-V switching curves of bipolar switching non-volatile ReRAM devices show peculiar characteristics, such as an abrupt ON switching and the existence of a universal switching voltage. This switching behavior has been explained by the presence of a filamentary process, in which the width of a conductive filament changes during switching resulting in different resistance states. Vice versa, similar (ON) switching behavior, e.g. that of volatile switching Cr-doped V2O3 devices, has been interpreted as an indication of the presence of similar filamentary switching. In this paper, we want to review the correlation between filamentary (width) switching and the (SET) I-V characteristics by discussing the existing models. For the Cr-doped V2O3 devices, on the other hand, it is argued that a different, constant filament width switching mode may be present.

Understanding the Coexistence of Two Bipolar Resistive Switching Modes with Opposite Polarity in Pt/TiO2/Ti/Pt Nanosized ReRAM Devices.

Redox-type resistive random access memories based on transition-metal oxides are studied as adjustable two-terminal devices for integrated network applications beyond von Neumann computing. The prevailing, so-called, counter-eight-wise (c8w) polarity of the switching hysteresis in filamentary-type valence change mechanism devices originates from a temperature- and field-controlled drift-diffusion process of mobile ions, predominantly oxygen vacancies in the switching oxide. Recently, a bipolar resistive switching (BRS) process with opposite polarity, so-called, eight-wise (8w) switching, has been reported that, especially for TiO2 cells, is still not completely understood. Here, we report on nanosized (<0.01 µm2) asymmetric memristive cells from 3 to 6 nm thick TiO2 films by atomic layer deposition, which reveal a coexistence of c8w and 8w switching in the same cell. As important characteristics for the studied Pt/TiO2/Ti/Pt devices, the resistance states of both modes are nonvolatile and share one common state; i.e., the high-resistance state of the c8w mode equals the low-resistance state of the 8w-mode. A transition between the opposite hysteresis loops is possible by voltage control. Specifically, 8w BRS in the TiO2 cells is a self-limited low-energy nonvolatile switching process. Additionally, the 8w reset process enables the programming of multilevel high-resistance states. Combining the experimental results with data from simulation studies allows to propose a model, which explains 8w BRS by an oxygen transfer process across the Pt/TiO2 Schottky interface at the position of the c8w filament. Therefore, the coexistence of c8w and 8w BRS in the nanoscale asymmetric Pt/TiO2/Ti/Pt cells is understood from a competition between drift/diffusion of oxygen vacancies in the oxide layer and an oxygen exchange reaction across the Pt/TiO2 interface.

Improvement of SET variability in TaO x based resistive RAM devices.

Improvement or at least control of variability is one of the key challenges for Redox based resistive switching memory technology. In this paper, we investigate the impact of a serial resistor as a voltage divider on the SET variability in Pt/Ta2O5/Ta/Pt nano crossbar devices. A partial RESET in a competing complementary switching (CS) mode is identified as a possible failure mechanism of bipolar switching SET in our devices. Due to a voltage divider effect, serial resistance value shows unequal impact on switching voltages of both modes which allows for a selective suppression of the CS mode. The impact of voltage divider on SET variability is demonstrated. A combination of appropriate write voltage and serial resistance allows for a significant improvement of the SET variability.

Volatile HRS asymmetry and subloops in resistive switching oxides.

Current-voltage characteristics of oxide-based resistive switching memories often show a pronounced asymmetry with respect to the voltage polarity in the high resistive state (HRS), where the HRS after the RESET is more conducting than the one before the SET. Here, we report that most of this HRS asymmetry is a volatile effect as the HRS obtained from a read operation differs from the one taken from the switching cycle at identical polarity and voltages. Transitions between the relaxed and the volatile excited states can be achieved via voltage sweeps, which are named subloops. The excited states are stable over time as long as a voltage is applied to the device and have a higher conductance than the stable relaxed state. Experimental data on the time and voltage dependence of the excitation and decay are presented for Ta/TaOx/Pt and Ta/ZrOx/Pt devices. The effect is not limited to one oxide or electrode material but is observed with different magnitudes (up to 10× current change) in several oxide systems. These observations describe an additional state variable of the memristive system that is controlled in a highly polarity dependent manner.

Impact of oxygen exchange reaction at the ohmic interface in Ta2O5-based ReRAM devices.

Interface reactions constitute essential aspects of the switching mechanism in redox-based resistive random access memory (ReRAM). For example, the modulation of the electronic barrier height at the Schottky interface is considered to be responsible for the toggling of the resistance states. On the other hand, the role of the ohmic interface in the resistive switching behavior is still ambigious. In this paper, the impact of different ohmic metal-electrode (M) materials, namely W, Ta, Ti, and Hf on the characteristics of Ta2O5 ReRAM is investigated. These materials are chosen with respect to their free energy for metal oxide formation and, associated, their impact on the formation energy of oxygen vacancy defects at the M/Ta2O5 interface. The resistive switching devices with Ti and Hf electrodes that have a negative defect formation energy, show an early RESET failure during the switching cycles. This failure process with Ti and Hf electrode is attributed to the accumulation of oxygen vacancies in the Ta2O5 layer, which leads to permanent breakdown of the metal-oxide to a low resistive state. In contrast, the defect formation energy in the Ta2O5 with respect to Ta and W electrodes is positive and for those highly stable resistive switching behavior is observed. During the quasi-static and transient-pulse characterization, the ReRAM devices with the W electrode consistently show an increased high resistance state (HRS) than with the Ta electrode for all RESET stop voltages. This effect is attributed to the faster oxygen exchange reaction at the W-electrode interface during the RESET process in accordance to lower stability of WO3 than Ta2O5. Based on these findings, an advanced resistive switching model, wherein also the oxygen exchange reaction at the ohmic M-electrode interface plays a vital role in determining of the resistance states, is presented.

Standardization of preanalytical aspects of cerebrospinal fluid biomarker testing for Alzheimer's disease diagnosis: a consensus paper from the Alzheimer's Biomarkers Standardization Initiative.

BACKGROUND: Numerous studies show that the cerebrospinal fluid biomarkers total tau (T-tau), tau phosphorylated at threonine 181 (P-tau(181P)), and amyloid-ß (1-42) (Aß(1-42)) have high diagnostic accuracy for Alzheimer's disease. Variability in concentrations for Aß(1-42), T-tau, and P-tau(181P) drives the need for standardization. METHODS: Key issues were identified and discussed before the first meeting of the members of the Alzheimer's Biomarkers Standardization Initiative (ABSI). Subsequent ABSI consensus meetings focused on preanalytical issues. RESULTS: Consensus was reached on preanalytical issues such as the effects of fasting, different tube types, centrifugation, time and temperature before storage, storage temperature, repeated freeze/thaw cycles, and length of storage on concentrations of Aß(1-42), T-tau, and P-tau(181P) in cerebrospinal fluid. CONCLUSIONS: The consensus reached on preanalytical issues and the recommendations put forward during the ABSI consensus meetings are presented in this paper.

Electrodeposition of copper tetracyanoquinodimethane for bipolar resistive switching non-volatile memories.

Electrodeposition experiments of the charge-transfer complex copper tetracyanoquinodimethane (CuTCNQ) (where TCNQ denotes 7,7',8,8'-tetracyanoquinodimethane) on noble metal electrodes (M=Pt and Au) were optimized in order to produce suitable layers for bipolar resistive switching cross-bar M/CuTCNQ/Al memory cells. Corresponding memories exhibited up to more than 10 000 consecutive write/erase cycles, with very stable on and off reading currents and an on/off current ratio of 10. CuTCNQ electrodeposition techniques were furthermore optimized for growing the material in 250 nm diameter contact holes of complementary metal oxide semiconductor dies with tungsten bottom contacts.