Applications of memristors in conventional analogue electronics

This dissertation presents the steps employed to activate and utilise analogue memristive devices in conventional analogue circuits and beyond. TiO2 memristors are mainly utilised in this study, and their large variability in operation in between similar devices is identified. A specialised memristor characterisation instrument is designed and built to mitigate this issue and to allow access to large numbers of devices at a time. Its performance is quantified against linear resistors, crossbars of linear resistors, stand-alone memristive elements and crossbars of memristors. This platform allows for a wide range of different pulsing algorithms to be applied on individual devices, or on crossbars of memristive elements, and is used throughout this dissertation. Different ways of achieving analogue resistive switching from any device state are presented. Results of these are used to devise a state-of-art biasing parameter finder which automatically extracts pulsing parameters that induce repeatable analogue resistive switching. IV measurements taken during analogue resistive switching are then utilised to model the internal atomic structure of two devices, via fittings by the Simmons tunnelling barrier model. These reveal that voltage pulses modulate a nano-tunnelling gap along a conical shape. Further retention measurements are performed which reveal that under certain conditions, TiO2 memristors become volatile at short time scales. This volatile behaviour is then implemented into a novel SPICE volatile memristor model. These characterisation methods of solid-state devices allowed for inclusion of TiO2 memristors in practical electronic circuits. Firstly, in the context of large analogue resistive crossbars, a crosspoint reading method is analysed and improved via a 3-step technique. Its scaling performance is then quantified via SPICE simulations. Next, the observed volatile dynamics of memristors are exploited in two separate sequence detectors, with applications in neuromorphic engineering. Finally, the memristor as a programmable resistive weight is exploited to synthesise a memristive programmable gain amplifier and a practical memristive automatic gain control circuit.Open Acces

An FPGA-based system for generalised electron devices testing

Electronic systems are becoming more and more ubiquitous as our world digitises. Simultaneously, even basic components are experiencing a wave of improvements with new transistors, memristors, voltage/current references, data converters, etc, being designed every year by hundreds of R &D groups world-wide. To date, the workhorse for testing all these designs has been a suite of lab instruments including oscilloscopes and signal generators, to mention the most popular. However, as components become more complex and pin numbers soar, the need for more parallel and versatile testing tools also becomes more pressing. In this work, we describe and benchmark an FPGA system developed that addresses this need. This general purpose testing system features a 64-channel source-meter unit, and [Formula: see text] banks of 32 digital pins for digital I/O. We demonstrate that this bench-top system can obtain [Formula: see text] current noise floor, [Formula: see text] pulse delivery at [Formula: see text] and [Formula: see text] maximum current drive/channel. We then showcase the instrument's use in performing a selection of three characteristic measurement tasks: (a) current-voltage characterisation of a diode and a transistor, (b) fully parallel read-out of a memristor crossbar array and (c) an integral non-linearity test on a DAC. This work introduces a down-scaled electronics laboratory packaged in a single instrument which provides a shift towards more affordable, reliable, compact and multi-functional instrumentation for emerging electronic technologies

Real-time encoding and compression of neuronal spikes by metal-oxide memristors

Advanced brain-chip interfaces with numerous recording sites bear great potential for investigation of neuroprosthetic applications. The bottleneck towards achieving an efficient bio-electronic link is the real-time processing of neuronal signals, which imposes excessive requirements on bandwidth, energy and computation capacity. Here we present a unique concept where the intrinsic properties of memristive devices are exploited to compress information on neural spikes in real-time. We demonstrate that the inherent voltage thresholds of metal-oxide memristors can be used for discriminating recorded spiking events from background activity and without resorting to computationally heavy off-line processing. We prove that information on spike amplitude and frequency can be transduced and stored in single devices as non-volatile resistive state transitions. Finally, we show that a memristive device array allows for efficient data compression of signals recorded by a multi-electrode array, demonstrating the technology’s potential for building scalable, yet energy-efficient on-node processors for brain-chip interfaces

Reconfigurable writing architecture for reliable RRAM operation in wide temperature ranges

Resistive switching memories [resistive RAM (RRAM)] are an attractive alternative to nonvolatile storage and nonconventional computing systems, but their behavior strongly depends on the cell features, driver circuit, and working conditions. In particular, the circuit temperature and writing voltage schemes become critical issues, determining resistive switching memories performance. These dependencies usually force a design time tradeoff among reliability, device endurance, and power consumption, thereby imposing nonflexible functioning schemes and limiting the system performance. In this paper, we present a writing architecture that ensures the correct operation no matter the working temperature and allows the dynamic load of application-oriented writing profiles. Thus, taking advantage of more efficient configurations, the system can be dynamically adapted to overcome RRAM intrinsic challenges. Several profiles are analyzed regarding power consumption, temperature-variations protection, and operation speed, showing speedups near 700x compared with other published drivers

Advanced Memristor Modeling

The investigation of new memory schemes, neural networks, computer systems and many other improved electronic devices is very important for future generations of electronic circuits and for their widespread application in all the areas of industry. Relatedly, the analysis of new efficient and advanced electronic elements and circuits is an essential field of highly developed electrical and electronic engineering. The resistance-switching phenomenon, observed in many amorphous oxides, has been investigated since 1970 and is promising for inclusion in technologies for constructing new electronic memories. It has been established that such oxide materials have the ability to change their conductance in accordance to the applied voltage and memorizing their state for a long time interval. Similar behavior was predicted for the memristor element by Leon Chua in 1971. The memristor was proposed in accordance with symmetry considerations and the relationships between the four basic electric quantities—electric current i, voltage v, charge q and flux linkage Ψ. The memristor is a passive one-port element, together with the capacitor, inductor and resistor. The Williams Hewlett Packard (HP) research group has made a link between resistive switching devices and the memristor proposed by Chua. In addition, a number of scientific papers related to memristors and memristor devices have been issued and several models for them have been proposed. The memristor is a highly nonlinear component. It relates the electric charge q and the flux linkage Ψ, expressed as a time integral of the voltage v. It has the important capability of remembering the electric charge passing through its cross-section, and its respective resistance, when the electrical signals are switched off. Due to its nano-scale dimensions, non-volatility and memorizing properties, the memristor is a sound potential candidate for applications in high-density computer memories, artificial neural networks, and many other electronic devices

Practical determination of individual element resistive states in selectorless RRAM arrays

Three distinct methods of reading multi-level cross-point resistive states from selector-less RRAM arrays are implemented in a physical system and compared for read-out accuracy. They are: the standard, direct measurement method and two methods that attempt to enhance accuracy by computing cross-point resistance on the basis of multiple measurements. Results indicate that the standard method performs as well as or better than its competitors. SPICE simulations are then performed with controlled amounts of non-idealities introduced in the system in order to test whether any technique offers particular resilience against typical practical imperfections such as crossbar line resistance. We conclude that even though certain non-idealities are shown to be minimized by different circuit-level read-out strategies, line resistance within the crossbar remains an outstanding challeng