The Role of Hydrogen in ReRAM.

Previous research on transistor gate oxides reveals a clear link between hydrogen content and oxide breakdown. This has implications for redox-based resistive random access memory (ReRAM) devices, which exploit soft, reversible, dielectric breakdown, as hydrogen is often not considered in modeling or measured experimentally. Here quantitative measurements, corroborated across multiple techniques are reported, that reveal ReRAM devices, whether manufactured in a university setting or research foundry, contain concentrations of hydrogen at levels likely to impact resistance switching behavior.

Nonideality-Aware Training for Accurate and Robust Low-Power Memristive Neural Networks.

Recent years have seen a rapid rise of artificial neural networks being employed in a number of cognitive tasks. The ever-increasing computing requirements of these structures have contributed to a desire for novel technologies and paradigms, including memristor-based hardware accelerators. Solutions based on memristive crossbars and analog data processing promise to improve the overall energy efficiency.

Standards for the Characterization of Endurance in Resistive Switching Devices.

Resistive switching (RS) devices are emerging electronic components that could have applications in multiple types of integrated circuits, including electronic memories, true random number generators, radiofrequency switches, neuromorphic vision sensors, and artificial neural networks. The main factor hindering the massive employment of RS devices in commercial circuits is related to variability and reliability issues, which are usually evaluated through switching endurance tests. However, we note that most studies that claimed high endurances >10 cycles were based on resistance cycle plots that contain very few data points (in many cases even <20), and which are collected in only one device.

Memristor-Based Edge Detection for Spike Encoded Pixels.

Memristors have many uses in machine learning and neuromorphic hardware. From memory elements in dot product engines to replicating both synapse and neuron wall behaviors, the memristor has proved a versatile component. Here we demonstrate an analog mode of operation observed in our silicon oxide memristors and apply this to the problem of edge detection.

Simulation of Inference Accuracy Using Realistic RRAM Devices.

Resistive Random Access Memory (RRAM) is a promising technology for power efficient hardware in applications of artificial intelligence (AI) and machine learning (ML) implemented in non-von Neumann architectures. However, there is an unanswered question if the device non-idealities preclude the use of RRAM devices in this potentially disruptive technology. Here we investigate the question for the case of inference.

Sensing and Discrimination of Explosives at Variable Concentrations with a Large-Pore MOF as Part of a Luminescent Array.

Metal-organic frameworks (MOFs) have shown great promise for sensing of dangerous chemicals, including environmental toxins, nerve agents, and explosives. However, challenges remain, such as the sensing of larger analytes and the discrimination between similar analytes at different concentrations. Herein, we present the synthesis and development of a new, large-pore MOF for explosives sensing and demonstrate its excellent sensitivity against a range of relevant explosive compounds including trinitrotoluene and pentaerythritol tetranitrate.

The interplay between structure and function in redox-based resistance switching.

We report a study of the relationship between oxide microstructure at the scale of tens of nanometres and resistance switching behaviour in silicon oxide. In the case of sputtered amorphous oxides, the presence of columnar structure enables efficient resistance switching by providing an initial structured distribution of defects that can act as precursors for the formation of chains of conductive oxygen vacancies under the application of appropriate electrical bias. Increasing electrode interface roughness decreases electroforming voltages and reduces the distribution of switching voltages.

Silicon Oxide (SiO ): A Promising Material for Resistance Switching?

Interest in resistance switching is currently growing apace. The promise of novel high-density, low-power, high-speed nonvolatile memory devices is appealing enough, but beyond that there are exciting future possibilities for applications in hardware acceleration for machine learning and artificial intelligence, and for neuromorphic computing. A very wide range of material systems exhibit resistance switching, a number of which-primarily transition metal oxides-are currently being investigated as complementary metal-oxide-semiconductor (CMOS)-compatible technologies.

Controlling and modelling the wetting properties of III-V semiconductor surfaces using re-entrant nanostructures.

Inorganic semiconductors such as III-V materials are very important in our everyday life as they are used for manufacturing optoelectronic and microelectronic components with important applications span from energy harvesting to telecommunications. In some applications, these components are required to operate in harsh environments. In these cases, having waterproofing capability is essential.

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 (SiO) resistance switching devices extend beyond plasticity to include thresholding, spiking, and integration.

Investigation of resistance switching in SiO 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.

Nanoscale Transformations in Metastable, Amorphous, Silicon-Rich Silica.

Electrically biasing thin films of amorphous, substoichiometric silicon oxide drives surprisingly large structural changes, apparent as density variations, oxygen movement, and ultimately, emission of superoxide ions. Results from this fundamental study are directly relevant to materials that are increasingly used in a range of technologies, and demonstrate a surprising level of field-driven local reordering of a random oxide network.

Emulating the Electrical Activity of the Neuron Using a Silicon Oxide RRAM Cell.

In recent years, formidable effort has been devoted to exploring the potential of Resistive RAM (RRAM) devices to model key features of biological synapses. This is done to strengthen the link between neuro-computing architectures and neuroscience, bearing in mind the extremely low power consumption and immense parallelism of biological systems. Here we demonstrate the feasibility of using the RRAM cell to go further and to model aspects of the electrical activity of the neuron.

Flexible and fluorophore-doped luminescent solar concentrators based on polydimethylsiloxane.

We demonstrate a simple and inexpensive method to fabricate flexible and fluorophore-doped luminescent solar concentrators (LSCs). Polydimethylsiloxane (PDMS) serves as a host material which additionally offers the potential to cast LSCs in arbitrary shapes. The laser dye Pyrromethene 567 is used as a prototype fluorophore, and it is shown that it has a high quantum yield of 93% over the concentration range investigated.

Electrospray synthesis and properties of hierarchically structured PLGA TIPS microspheres for use as controlled release technologies.

Microsphere-based controlled release technologies have been utilized for the long-term delivery of proteins, peptides and antibiotics, although their synthesis poses substantial challenges owing to formulation complexities, lack of scalability, and cost. To address these shortcomings, we used the electrospray process as a reproducible, synthesis technique to manufacture highly porous (>94%) microspheres while maintaining control over particle structure and size. Here we report a successful formulation recipe used to generate spherical poly(lactic-co-glycolic) acid (PLGA) microspheres using the electrospray (ES) coupled with a novel thermally induced phase separation (TIPS) process with a tailored Liquid Nitrogen (LN2) collection scheme.

Conductance tomography of conductive filaments in intrinsic silicon-rich silica RRAM.

We present results from an imaging study of filamentary conduction in silicon suboxide resistive RAM devices. We used a conductive atomic force microscope to etch through devices while measuring current, allowing us to produce tomograms of conductive filaments. To our knowledge this is the first report of such measurements in an intrinsic resistance switching material.

Efficiency and loss mechanisms of plasmonic Luminescent Solar Concentrators.

Using a hybrid nanoscale/macroscale model, we simulate the efficiency of a luminescent solar concentrator (LSC) which employs silver nanoparticles to enhance the dye absorption and scatter the incoming light. We show that the normalized optical efficiency can be increased from 10.4% for a single dye LSC to 32.

Electrically tailored resistance switching in silicon oxide.

Resistive switching in a metal-free silicon-based material offers a compelling alternative to existing metal oxide-based resistive RAM (ReRAM) devices, both in terms of ease of fabrication and of enhanced device performance. We report a study of resistive switching in devices consisting of non-stoichiometric silicon-rich silicon dioxide thin films. Our devices exhibit multi-level switching and analogue modulation of resistance as well as standard two-level switching.

Structural factors impacting carrier transport and electroluminescence from Si nanocluster-sensitized Er ions.

We present an analysis of factors influencing carrier transport and electroluminescence (EL) at 1.5 µm from erbium-doped silicon-rich silica (SiOx) layers. The effects of both the active layer thickness and the Si-excess content on the electrical excitation of erbium are studied.

Electrically pumped silicon waveguide light sources.

We report simulations of electrically pumped waveguide emitters in which the emissive layer contains silicon nanoclusters and erbium ions. Plasmonic coupling to metallic or semi-metallic overlayers provides enhancement of the radiative rate of erbium ions, enabling high quantum efficiency emission. Using 2D and 3D finite difference time domain (FDTD) simulations we show that up to 75% of the light emitted from the active layer can be coupled into a nanowire silicon rib waveguide.