Probing the resistance switching mechanism in silicon suboxide memory devices

Redox-based resistive random access memory has the scope to greatly improve upon current electronic data storage, though the mechanism by which devices operate is not understood completely. In particular, the connection between oxygen migration, the formation of conductive filaments and device longevity is still disputed. Here, I used atomic force microscopy, scanning electron microscopy and x-ray photoelectron spectroscopy to characterise the growth of filaments and the movement of oxygen in silicon-rich silicon oxide memory devices. As such, I was able to establish some of the chemical and structural differences between states of different resistance, which would correspond to binary data storage states. The oxide active layer is reduced simultaneously to the appearance of surface distortion and volumes of high conductivity in an otherwise-insulating material. These results support the established model of a resistance switching mechanism that relies on the migration of oxygen ions under an electrical bias, forming conductive pathways in the switching material. Notably, I demonstrate a reduction in the active layer stoichiometry as a result of electrical stress and show for the first time the presence of multiple filamentary growths in three dimensions in an intrinsic switching material. In addition, I have proven the efficacy of an extension to the method of profiling conductivity variations in insulators in three dimensions using conductive atomic force microscopy. However, in this case my findings conflict with the status quo of this methodology. In particular, I demonstrate that the measurement process significantly affects the scanning probe, leading to the likelihood of data inaccuracy. This highlights the needed for further development of the technique and careful analysis of the data obtained

Advanced physical modeling of SiOx resistive random access memories

We apply a three-dimensional (3D) physical simulator, coupling self-consistently stochastic kinetic Monte Carlo descriptions of ion and electron transport, to investigate switching in silicon-rich silica (SiOx) redox-based resistive random-access memory (RRAM) devices. We explain the intrinsic nature of resistance switching of the SiOx layer, and demonstrate the impact of self-heating effects and the initial vacancy distributions on switching. We also highlight the necessity of using 3D physical modelling to predict correctly the switching behavior. The simulation framework is useful for exploring the little-known physics of SiOx RRAMs and RRAM devices in general. This proves useful in achieving efficient device and circuit designs, in terms of performance, variability and reliability

Investigation of resistance switching in SiOx RRAM cells using a 3D multi-scale kinetic Monte Carlo simulator

We employ an advanced three-dimensional (3D) electro-thermal simulator to explore the physics and potential of oxide-based resistive random-access memory (RRAM) cells. The physical simulation model has been developed recently, and couples a kinetic Monte Carlo study of electron and ionic transport to the self-heating phenomenon while accounting carefully for the physics of vacancy generation and recombination, and trapping mechanisms. The simulation framework successfully captures resistance switching, including the electroforming, set and reset processes, by modeling the dynamics of conductive filaments in the 3D space. This work focuses on the promising yet less studied RRAM structures based on silicon-rich silica (SiOx) RRAMs. We explain the intrinsic nature of resistance switching of the SiOx layer, analyze the effect of self-heating on device performance, highlight the role of the initial vacancy distributions acting as precursors for switching, and also stress the importance of using 3D physics-based models to capture accurately the switching processes. The simulation work is backed by experimental studies. The simulator is useful for improving our understanding of the little-known physics of SiOx resistive memory devices, as well as other oxide-based RRAM systems (e.g. transition metal oxide RRAMs), offering design and optimization capabilities with regard to the reliability and variability of memory cells

Up in smoke: Considerations for lithium-ion batteries in disposable e-cigarettes

In recent years, the use of disposable electric (e)-cigarettes containing lithium-ion batteries in the UK has led to remarkable wastage, the full environmental impact of which is yet to be realized. This study investigates the suitability for reuse and safety aspects of cells found in disposable e-cigarettes. Through electrochemical and safety characterization techniques, the cells’ performance and hazards were evaluated. Rate capability and long-term cycling experiments showed that cells sold as disposable were capable of completing 474 cycles at 1C charge/discharge before reaching 80% capacity fade. A nail penetration test revealed significant gas expulsion and a maximum temperature of 495°C. However, the cell format prevented significant material ejection. This work outlines the potential health hazards and highlights the possibility for second-life use of disposable e-cigarette cells, shedding light on the environmental impact and safety considerations

Quantitative spatiotemporal mapping of thermal runaway propagation rates in lithium-ion cells using cross-correlated Gabor filtering

Abuse testing of lithium-ion batteries is widely performed in order to develop new safety standards and strategies. However, testing methodologies are not standardised across the research community, especially with failure mechanisms being inherently difficult to reproduce. High-speed X-ray radiography is proven to be a valuable tool to capture events occurring during cell failure, but the observations made remain largely qualitative. We have therefore developed a robust image processing toolbox that can quantify, for the first time, the rate of propagation of battery failure mechanisms revealed by high-speed X-ray radiography. Using Gabor filter, the toolbox selectively tracks the electrode structure at the onset of failure. This facilitated the estimation of the displacement of electrodes undergoing abuse via nail penetration, and also the tracking of objects, such as the nail, as it propagates through a cell. Further, by cross-correlating the Gabor signals, we have produced practical, illustrative spatiotemporal maps of the failure events. From these, we can quantify the propagation rates of electrode displacement prior to the onset of thermal runaway. The highest recorded acceleration (≈514 mm s−2) was when a nail penetrated a cell radially (perpendicular to the electrodes) as opposed to axially (parallel to the electrodes). The initiation of thermal runaway was also resolved in combination with electrode displacement, which occurred at a lower acceleration (≈108 mm s−2). Our assistive toolbox can also be used to study other types of failure mechanisms, extracting otherwise unattainable kinetic data. Ultimately, this tool can be used to not only validate existing theoretical mechanical models, but also standardise battery failure testing procedures

A reversible inhibitor of ?-lactamase I from Bacillus cereus

a-Methyl (3S,5R,6R)benzylpenicilloate is a reversible competitive inhibitor of -lactamase l from Bacillus cereus; the inhibition constant Ki is 6.38 × 10–4M and is independent of pH between pH 5 and 8 which is compatible with binding of the free base form of the thiazolidine residue to the enzym

Spike-Timing Dependent Plasticity in Unipolar Silicon Oxide RRAM Devices

Resistance switching, or Resistive RAM (RRAM) devices show considerable potential for application in hardware spiking neural networks (neuro-inspired computing) by mimicking some of the behavior of biological synapses, and hence enabling non-von Neumann computer architectures. Spike-timing dependent plasticity (STDP) is one such behavior, and one example of several classes of plasticity that are being examined with the aim of finding suitable algorithms for application in many computing tasks such as coincidence detection, classification and image recognition. In previous work we have demonstrated that the neuromorphic capabilities of silicon-rich silicon oxide (SiOx) resistance switching devices extend beyond plasticity to include thresholding, spiking, and integration. We previously demonstrated such behaviors in devices operated in the unipolar mode, opening up the question of whether we could add plasticity to the list of features exhibited by our devices. Here we demonstrate clear STDP in unipolar devices. Significantly, we show that the response of our devices is broadly similar to that of biological synapses. This work further reinforces the potential of simple two-terminal RRAM devices to mimic neuronal functionality in hardware spiking neural networks

Quantitative spatiotemporal mapping of thermal runaway propagation rates in lithium-ion cells using cross-correlated Gabor filtering

Abuse testing of lithium-ion batteries is widely performed in order to develop new safety standards and strategies. However, testing methodologies are not standardised across the research community, especially with failure mechanisms being inherently difficult to reproduce. High-speed X-ray radiography is proven to be a valuable tool to capture events occurring during cell failure, but the observations made remain largely qualitative. We have therefore developed a robust image processing toolbox that can quantify, for the first time, the rate of propagation of battery failure mechanisms revealed by high-speed X-ray radiography. Using Gabor filter, the toolbox selectively tracks the electrode structure at the onset of failure. This facilitated the estimation of the displacement of electrodes undergoing abuse via nail penetration, and also the tracking of objects, such as the nail, as it propagates through a cell. Further, by cross-correlating the Gabor signals, we have produced practical, illustrative spatiotemporal maps of the failure events. From these, we can quantify the propagation rates of electrode displacement prior to the onset of thermal runaway. The highest recorded acceleration (≈ 514 mm s-2) was when a nail penetrated a cell radially (perpendicular to the electrodes) as opposed to axially (parallel to the electrodes). The initiation of thermal runaway was also resolved in combination with electrode displacement, which occurred at a lower acceleration (≈ 108 mm s-2). Our assistive toolbox can also be used to study other types of failure mechanisms, extracting otherwise unattainable kinetic data. Ultimately, this tool can be used to not only validate existing theoretical mechanical models, but also standardise battery failure testing procedures