So-called "resistive-switching" devices are based on nanostructured dielectric materials, in which the resistance can be varied and memorised. Arguably these devices will lead to a range of disruptive technologies in the field of infromation storage over the next 20 years. Potentially these non-volatile resistive-switching devices can have potentially high speeds, high densities, long retention times and high endurance which will drastically enhance the performance of non-volatile memories and also revolutionise the computer architectures. This research sets out to understand the property - process - structure relationships of oxide dielectrics with programmable resistance. A combination of modelling, synthesis and characterisation will be used to advance the understanding of defects in oxide materials and their control. The aims of the proposed research are to elucidate the nature and mechanisms of the formation and migration of the defects and to explore ways to control and enhance their electrical properties for resistive-switching applications. The global market for memory devices amounts to more than $57 billion and has been projected to grow to $99 billion by 2015. Within this market, a number of existing memory technologies, (DRAM, SRAM, and NAND Flash) have inherent scaling issues to overcome beyond the next generation. The search for alternative solutions is gaining momentum and an alternative candidate is Resistive RAM which exploits the resistive-switching mechanism. The UK Electronic Systems Community employs more than 850,000 people, which constitutes approximately 3% of the UK workforce. Approximately half of this employment is found in the 30,000 enterprises whose business is overtly the provision of Electronic Systems and the technologies and capabilities they need. The rest are within businesses that occupy market sectors spanning aerospace, defence, healthcare, retail, media and education. The potential impact of this project will be the development of a new manufacturing process technology, which will have applications across these sectors in the UK. The impact in terms of new materials, chemistry, products and processes will be significant if the projeproposed objectives are realised.

This fellowship will lay the foundations for a new AI paradigm featuring algorithms based on the free energy principle (FEP) and hardware platforms leveraging the stochasticity of novel nanoscale devices based on 2-dimensional materials, enabling embedded systems with unprecedented efficiency. Artificial Intelligence (AI) models based on deep learning algorithms have demonstrated super-human performance for a wide variety of such tasks - ranging from language translation to protein folding. However, the cost of developing such models - both in terms of energy and time - has been sky-rocketing. For example, recent studies estimate that the carbon footprint for training a state-of-the-art language translation model can be as high as 3 round-trip flights between New York and San Francisco. One major contributor to this inefficiency is the von Neumann architecture used in today's computing platforms - the data storage and data processing units are physically separated. Hence, running these algorithms require data that is represented in high precision to be constantly shuttled back and forth. Contrast this with the human brain, nature's most evolved computation engine, which continuously makes complex cognitive decisions, that too based on noisy sensory data and an imprecise computational infrastructure. The brain achieves this amazing feat by encoding information in tiny electrical signals called spikes that are transmitted through a seamlessly interconnected network of 'logic' and 'memory' units - neurons and synapses - all while consuming less than 20 Watts. Clearly, there is something fundamentally unique about the algorithms and hardware of the brain! The research in this fellowship is motivated by a theory called the free energy principle (FEP), which provides a unified foundation that underlies the cognitive efficiency of the brain. The central tenet of FEP is that biological organisms tend to minimize the occurrence of surprising events by acting to change the sensory inputs they receive from the environment or by modifying the internal states that allow them to perceive the world and make decisions. Furthermore, since the theoretical foundation of FEP assumes that the brain's models are inherently probabilistic, representing data or the model in high precision is not a strict requirement. Hence, the research in the fellowship will pursue the novel approach of using the undesirable imperfections of nanoscale devices as a resource for implementing the probabilistic parameters of the model. This approach can hence lead to computational systems with unprecedented efficiency as the basic building blocks can be operated at drastically lower voltages and currents, avoiding unnecessary data movement. This research will first develop artificial neural networks that mimic the spike-triggered communication feature of the brain based on the mathematical ideas of the free energy principle. We will create AI models that can generate decisions that are trustworthy and can be supported with quantifiable confidence metrics. In parallel, we will also demonstrate prototype hardware platforms that implement these algorithms using the stochastic properties of nanoscale devices as a resource for computation. Hardware prototypes will be built using novel nanoscale devices that are based on 2-dimensional materials as well as nanoscale memory arrays built by industrial partners targeting a 1000-fold improvement in computational efficiency compared to what is possible today. Thus, the fellowship will lay the foundations of a new Smart and Green AI paradigm.

The sensing, processing and transport of information is at the heart of modern life, as can be seen from the ubiquity of smart-phone usage on any street. From our interactions with the people who design, build and use the systems that make this possible, we have created a programme to make possible the first data interconnects, switches and sensors that use lasers monolithically integrated on silicon, offering the potential to transform Information and Communication Technology (ICT) by changing fundamentally the way in which data is sensed, transferred between and processed on silicon chips. The work builds on our demonstration of the first successful telecommunications wavelength lasers directly integrated on silicon substrates. The QUDOS Programme will enable the monolithic integration of all required optical functions on silicon and will have a similar transformative effect on ICT to that which the creation of silicon integrated electronic circuits had on electronics. This will come about through removing the need to assemble individual components, enabling vastly increased scale and functionality at greatly reduced cost.

Thin oxide films are critical components in a very wide range of electronic devices, including CMOS transistors in microprocessors and memory, piezoelectric and thermoelectric devices and electroluminescent devices. In most cases we assume that the oxide itself is stable under the levels of electrical stress encountered during normal device operation, and a great deal of work has gone into growing extremely high quality films. Nevertheless, recent developments in devices and materials have led to the growing use of amorphous and polycrystalline sub-stoichiometric oxide thin films (SSOTFs). These materials are fundamentally different to their stoichiometric and crystalline cousins - a fact that can have very important consequences for their use in electronic devices - but it is usually assumed that they behave in the same way. It is increasingly clear that this assumption is incorrect. Recent studies, some performed by us, have demonstrated that amorphous sub-stoichiometric oxides are surprisingly dynamic under device-level electrical stress. In the case of silicon oxide, for example, we have shown that electrical stress drives the segregation of the oxide into regions with varying oxygen deficiency, and that such changes can be precursors to major changes in the electrical properties of the material. Our initial results suggest that oxide microstructure determines the ease with which oxygen can segregate, and we have seen, in extreme cases, emission of oxygen from the thin films. These changes can be permanent or they can be reversible, enabling cycling between two or more resistance states. Ultimately, such large-scale changes can lead to device failure. Consequently, by understanding how to control their dynamics we can both understand the early stages of oxide failure, and develop exciting new technologies that exploit the dynamic nature of functional oxides. In this study we propose to investigate these changes using a combination of high resolution experimental characterisation and atomistic modelling of oxygen movement. Studying sub-stoichiometric amorphous oxide thin films is a considerable challenge, both for experiment and for modelling, which is partly why these materials are poorly understood. We will rely on close interaction between experiment and theory to develop, in an iterative process, new models for the structure of substoichiometric amorphous oxides of varying morphology, and their dynamic response to electrical stress. These models will shed light on the physical processes governing electrical changes, and we will use them to generate a set of design rules for material and device optimisation. We have chosen a representative set of materials to study, each of which has important applications in microelectronics. We will grow the materials in-house, giving us control over their composition and structure and enabling rapid feedback from characterisation and modelling. The majority of our characterisation will also be performed at UCL, but we have long-standing and fruitful collaborations with two leading Transmission Electron Microscopy centres - Forschungszentrum Jülich and the Institute of Materials Research and Engineering in Singapore - which will give us access additional world-leading microscopy techniques to study these challenging materials. Our close collaboration with other leading research and development institutions, including our industrial partners, gives us access to further state-of-the-art facilities and industrially relevant samples.

Quantum information science and technologies offer a completely new and powerful approach to processing and transmitting information by combining two of the great scientific discoveries of the 20th century - quantum mechanics and information theory. By encoding information in quantum systems, quantum information processing promises huge computation power, while quantum communications is already in its first stages of commercialisation, and offers the ultimate in information security. However, for quantum technologies to have as big an impact on science, technology and society as anticipated, a practical scalable integration platform is required where all the key components can be integrated to a single micro-chip technology, very much akin to the development of the first microelectronic integrated circuits. Of the various approaches to realising quantum technologies, single particles of light (photons) are particularly appealing due to their low-noise properties and ease of manipulation at the single qubit level. It is possible to harness the quantum mechanical properties of single photons, taking advantage of strange quantum properties such as superposition and entanglement to provide new ways to encode, process and transmit information. Quantum photonics promises to be a truly disruptive technology in information processing, communications and sensing, and for deepening our understanding of fundamental quantum physics and quantum information science. However, current approaches are limited to simple optical circuits with low photon numbers, inefficient detectors and no clear routes to scalability. For quantum optic information science to go beyond current limitations, and for quantum applications to have a significant real-world impact, there is a clear and urgent need to develop a fully integrated quantum photonic technology platform to realise large and complex quantum circuits capable of generating, manipulating and detecting large photon-number states. This Fellowship will enable the PI and his research team to develop such a technology platform, based on silicon photonics. Drawing from the advanced fabrication technologies developed for the silicon microelectronics industry, state of the art silicon quantum photonic devices will enable compact, large-scale and complex quantum circuits, experiments and applications. This technology platform will overcome the current 8-photon barrier in a scalable way, enable circuits of unprecedented complexity, and will be used to address important fundamental questions, develop new approaches to quantum communications, enhance the performance of quantum sensing, provide a platform for new routes to quantum simulations, and achieve computational complexities that can challenge the limits of conventional computing. This multidisciplinary research programme will bring together engineers, physicists and industrial partners to tackle these scientific and technological challenges.