Early resistance change and stress/electromigration evolution in near bamboo interconnects

A complete description for early resistance change and mechanical stress evolution in near-bamboo interconnects, related to the electromigration, is given in this paper. The proposed model, for the first time, combines the stress/vacancy concentration evolution with the early resistance change of the Al line with a near-bamboo microstructure, which has been proven to be a fast technique for prediction of the MTF of a line compared to the conventional (accelerated) stres

Te-based chalcogenide materials for selector applications

The implementation of dense, one-selector one-resistor (1S1R), resistive switching memory arrays, can be achieved with an appropriate selector for correct information storage and retrieval. Ovonic threshold switches (OTS) based on chalcogenide materials are a strong candidate, but their low thermal stability is one of the key factors that prevents rapid adoption by emerging resistive switching memory technologies. A previously developed map for phase change materials is expanded and improved for OTS materials. Selected materials from different areas of the map, belonging to binary Ge-Te and Si-Te systems, are explored. Several routes, including Si doping and reduction of Te amount, are used to increase the crystallization temperature. Selector devices, with areas as small as 55 x 55 nm(2), were electrically assessed. Sub-threshold conduction models, based on Poole-Frenkel conduction mechanism, are applied to fresh samples in order to extract as-processed material parameters, such as trap height and density of defects, tailoring of which could be an important element for designing a suitable OTS material. Finally, a glass transition temperature estimation model is applied to Te-based materials in order to predict materials that might have the required thermal stability. A lower average number of p-electrons is correlated with a good thermal stability

Probing the Critical Region of Conductive Filament in Nanoscale HfO₂ Resistive-Switching Device by Random Telegraph Signals

Resistive-switching random access memory (RRAM) is widely considered as a disruptive technology. Despite tremendous efforts in theoretical modeling and physical analysis, details of how the conductive filament (CF) in metal-oxide-based filamentary RRAM devices is modified during normal device operations remain speculative, because direct experimental evidence at defect level has been missing. In this paper, a random-telegraph-signal-based defect-tracking technique (RDT) is developed for probing the location and movements of individual defects and their statistical spatial and energy characteristics in the CF of state-of-the-art hafnium-oxide RRAM devices. For the first time, the critical filament region of the CF is experimentally identified, which is located near, but not at, the bottom electrode with a length of nanometer scale. We demonstrate with the RDT technique that the modification of this key constriction region by defect movements can be observed and correlated with switching operation conditions, providing insight into the resistive switching mechanism

The over-reset phenomenon in Ta2O5 RRAM device investigated by the RTN-based defect probing technique

IEEE Despite the tremendous efforts in the past decade devoted to the development of filamentary resistive-switching devices (RRAM), there is still a lack of in-depth understanding of its over-reset phenomenon. At higher reset stop voltages that exceed a certain threshold, the resistance at high resistance state reduces, leading to an irrecoverable window reduction. The over-reset phenomenon limits the maximum resistance window that can be achieved by using a higher Vreset, which also degrades its potential in applications such as multi-level memory and neuromorphic synapses. In this work, the over-reset is investigated by cyclic reset operations with incremental stop voltages, and is explained by defect generation in the filament constriction region of Ta2O5 RRAM devices. This is supported by the statistical spatial defects profile obtained from the random telegraph noise based defect probing technique. The impact of forming compliance current on the over-reset is also evaluated

Doped GeSe materials for selector applications

We report on the thermal and electrical performance of nitrogen (N) and carbon (C) doped GeSe thin films for selector applications. Doping of GeSe successfully improved its thermal stability to 450 degrees C. N doping led to a decrease in the off-state leakage and an increase in threshold voltage (V-th), while C doping led to an increase in leakage and reduced V-th. Hence, we show an effective method to tune the electrical parameters of GeSe selectors by using N and C as dopants

Investigation of pre-existing and generated defects in non-filamentary a-Si/TiO2 RRAM and their impacts on RTN amplitude distribution

An extensive investigation of the pre-existing and generated defects in amorphous-Si/TiO2 based non-filamentary (a-VMCO) RRAM device has been carried out in this work to identify the switching and degradation mechanisms, through a combination of random-telegraph-noise (RTN) and constant- voltage-stress (CVS) analysis. The amplitude of RTN, which leads to read instability, is also evaluated statistically at different stages of cell degradation and correlated with different defects, for the first time. It is found that the switching between low and high resistance states (LRS and HRS) are correlated with the profile modulation of pre-existing defects in the ‘defect-less’ region near the a-Si/TiO2 interface. The RTN amplitude observed at this stage is small and has a tight distribution. At longer stress times, a percolation path is formed due to defects generation, which introduces larger RTN amplitude and a significant tail in its distribution

Tunnel Barrier Engineering of Titanium Oxide for High Non-Linearity of Selector-less Resistive Random Access Memory

In this study, the effect of the oxygen profile and thickness of multiple-layers TiOx on tunnel barrier characteristics was investigated to achieve high non-linearity in low-resistance state current (I-LRS). To form the tunnel barrier in multiple-layer of TiOx, tunnel barrier engineering in terms of the thickness and oxygen profile was attempted using deposition and thermal oxidation times. It modified the defect distribution of the tunnel barrier for effective suppression of ILRS at off-state (1/2V(Read)). By inserting modified tunnel barrier in resistive random access memory, a high non-linear I-LRS was exhibited with a significantly lowered I-LRS for 1/2V(Read). (C) 2014 AIP Publishing LLC.ope

Microscopic origin of random telegraph noise fluctuations in aggressively scaled RRAM and its impact on read disturb variability

Random telegraph noise (RTN) is an important intrinsic phenomenon of any logic or memory device that is indicative of the reliability and stochastic variability in its performance. In the context of the resistive random access memory (RRAM), RTN becomes a key criterion that determines the read disturb immunity and memory window between the low (LRS) and high resistance states (HRS). With the drive towards ultra-low power memory (low reset current) and aggressive scaling to 10 × 10 nm2 area, contribution of RTN is significantly enhanced by every trap (vacancy) in the dielectric. The underlying mechanisms governing RTN in RRAM are yet to be fully understood. In this study, we aim to decode the role of conductance fluctuations caused by oxygen vacancy transport and inelastic electron trapping and detrapping processes. The influence of resistance state (LRS, shallow and deep HRS), reset depth and reset stop voltage (VRESET-STOP) on the conductance variability is also investigated. © 2013 IEEE

Quantitative image analysis for the characterization of microbial aggregates in biological wastewater treatment : a review

Quantitative image analysis techniques have gained an undeniable role in several fields of research during the last decade. In the field of biological wastewater treatment (WWT) processes, several computer applications have been developed for monitoring microbial entities, either as individual cells or in different types of aggregates. New descriptors have been defined that are more reliable, objective, and useful than the subjective and time-consuming parameters classically used to monitor biological WWT processes. Examples of this application include the objective prediction of filamentous bulking, known to be one of the most problematic phenomena occurring in activated sludge technology. It also demonstrated its usefulness in classifying protozoa and metazoa populations. In high-rate anaerobic processes, based on granular sludge, aggregation times and fragmentation phenomena could be detected during critical events, e.g., toxic and organic overloads. Currently, the major efforts and needs are in the development of quantitative image analysis techniques focusing on its application coupled with stained samples, either by classical or fluorescent-based techniques. The use of quantitative morphological parameters in process control and online applications is also being investigated. This work reviews the major advances of quantitative image analysis applied to biological WWT processes.The authors acknowledge the financial support to the project PTDC/EBB-EBI/103147/2008 and the grant SFRH/BPD/48962/2008 provided by Fundacao para a Ciencia e Tecnologia (Portugal)