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Information technology (IT) has penetrated all aspects of life in modern society. At the heart of IT are miniature devices that can process and store information in one or another form. Currently, the information is processed mainly within semiconductor based data architectures based on tiny "transistors". In contrast, long-term data storage is dominated by magnetic hard disk drives, within which the information is stored as direction of tiny "magnetic needles" the two opposite orientations of which represent "0" and "1" values in binary logics. However, the semiconductor industry is predicted to reach the limit of miniaturisation within the coming decade, while the energy consumption becomes increasingly important both for environmental concerns and to align with use in portable battery fed devices. In this project, we aim to demonstrate a key component of a novel device for information technology, which has the potential to lead to combined data processing and storage on the same chip. This device will be based upon 'magnonics', in which wave-like perturbations of magnetisation ('spin waves') travel through and interact in patterned magnetic tracks ('waveguides') to perform operations. We propose to construct a spin wave source such that the wave properties of many such sources are linked; technically, this is known as 'coherence'. Our proposed spin wave source consists of a magnetic nanowire antenna placed across the waveguides. Microwave radiation will create magnetic oscillations in the antennae, which in turn will induce the spin waves in the nearby waveguides. Spin waves are proposed as logic signal carriers, thereby assisting their seamless integration with existing and future magnetic data storage technologies. This integration of signal processing and storage within a single architecture promises reduced energy consumption and fast device operation. In addition, we will exploit how the spin waves interact with the magnetic configuration of the various components. The materials and geometry of the antennae and waveguides causes the magnetisation to prefer to lie along their length. However, opposite magnetisations can be engineered to meet within, say, the waveguide to create a transition region called a 'magnetic domain wall'. By selectively configuring the orientation of the magnetic waveguide and antennae, including incorporation of magnetic domain walls, we will be able to program the magnonic device functionalities. The magnetic materials we propose to use don't require power to retain their magnetisation (non-volatility), meaning our devices will store the configuration when powered off and, therefore, will be instantaneously bootable upon switch on. The multiple stable configurations of the magnetic components and associated multiple functionalities will also provide an opportunity for creating more complex devices that could replace several semiconductor transistors in conventional electronics. Apart from consumer electronics, the devices will be advantageous for use in aerospace, space and sub-marine technologies in which their non-volatility and resistance to radiation will allow vital weight and cost savings to be made. The collaborative research programme will be conducted jointly by the Department of Materials Science and Engineering at the University of Sheffield and the College of Engineering, Mathematics and Physical Sciences at the University of Exeter. The Sheffield team will contribute to the project their internationally leading expertise in nanotechnology and manipulation of magnetic domain walls, while the Exeter team will contribute their world leading expertise in dynamical characterization and theoretical modelling of magnonic devices. By joining their forces together, the two teams will ensure that UK will remain at the forefront at the magnetic logic technology, in particular opening the new interdisciplinary field of domain wall magnonics.

The modern world is completely dependent upon electronic devices that operate through the flow of charged particles called electrons i.e. electric current. However the electron also carries 'spin' angular momentum, and has an associated magnetic moment, like a tiny bar magnet. The aim of Spintronics is to use the spin of an electron to control its motion and how it interacts with magnetic materials. The most celebrated spintronic device is the 'spin-valve', a trilayer structure in which two ferromagnetic (FM) layers are separated by a non-magnetic spacer layer. The spin-valve is engineered so that the magnetic moment of one FM layer is fixed, while that of the other is free to align with an applied magnetic field, like a compass needle. As the relative orientation of the two magnetic moments varies, a large change in electrical resistance of the trilayer is observed. Since the resistance is easily measured, the spin-valve can act as a magnetic field sensor. In fact a spin-valve sensor is used to read back information in every hard disk that is sold today. When current is passed between the fixed and free FM layers an inverse effect can be observed. The flow of electrons transfers angular momentum from one FM to the other, and, by Newton's 2nd Law, exerts a spin transfer torque (STT). This torque can act upon the magnetic moment of the free layer, causing it to change its orientation. The spin-valve can also be designed to have two stables states, with different electrical resistance, that can be used to store digital information. Arrays of such devices are used in magnetic random access memory (MRAM). Alternatively, in a spin transfer oscillator (STO), the free layer magnetization oscillates at microwave frequency when DC current is applied. Since the resistance also oscillates, microwave voltage oscillations are generated. The STO is unusual in that its frequency can be tuned through multiple octaves by varying the DC current. Multiple STOs can be defined at chip level, as circuit components, or in arrays for increased power output. In recent years it has been realized and demonstrated that the spin-orbit interaction, a relativistic effect, may also be used to manipulate the electron spin. The spin can in turn be used to generate a STT, which has been termed spin-orbit torque (SOT) in light of its origin. SOTs are generated by the spin Hall effect (SHE) and the Rashba effect, but the separation of these torques from each other, and from the torque generated by the flow of charge (Oersted torque), is still being debated. The optimization of SOT for use in MRAM has attracted enormous interest because it removes the need to pass large electric currents through fragile insulating layers that conduct electricity by quantum mechanical tunneling. In this project we will use time resolved scanning Kerr microscopy (TRSKM) to explore, understand and optimize SOTs in device structures of the highest quality supplied by HGST, Brown University and the University of Gothenburg, all of whom are leaders in their respective fields. Crucially we will modify our TRSKM so that a magnetic field can be applied with any orientation in 3 dimensional space, while high frequency electrical probes are connected to the device, and a focused optical probe is used to determine the instantaneous orientation of the magnetization vector. This internationally unique instrument will allow us to determine the SOTs from the static and dynamic response of the magnetization, rather than the electrical resistance, as different electrical stimuli are applied. Furthermore the sub-micron spatial resolution of TRSKM will allow us to separate different torques through their spatial variation, and understand how SOTs interact with dynamic magnetic modes in a confined geometry. Finally, we will use this same instrument to understand how SOTs induce magnetic precession in STOs and switching in candidate MRAM devices.

The achievements of modern research and their rapid progress from theory to application are increasingly underpinned by computation. Computational approaches are often hailed as a new third pillar of science - in addition to empirical and theoretical work. While its breadth makes computation almost as ubiquitous as mathematics as a key tool in science and engineering, it is a much younger discipline and stands to benefit enormously from building increased capacity and increased efforts towards integration, standardization, and professionalism. The development of new ideas and techniques in computing is extremely rapid, the progress enabled by these breakthroughs is enormous, and their impact on society is substantial: modern technologies ranging from the Airbus 380, MRI scans and smartphone CPUs could not have been developed without computer simulation; progress on major scientific questions from climate change to astronomy are driven by the results from computational models; major investment decisions are underwritten by computational modelling. Furthermore, simulation modelling is emerging as a key tool within domains experiencing a data revolution such as biomedicine and finance. This progress has been enabled through the rapid increase of computational power, and was based in the past on an increased rate at which computing instructions in the processor can be carried out. However, this clock rate cannot be increased much further and in recent computational architectures (such as GPU, Intel Phi) additional computational power is now provided through having (of the order of) hundreds of computational cores in the same unit. This opens up potential for new order of magnitude performance improvements but requires additional specialist training in parallel programming and computational methods to be able to tap into and exploit this opportunity. Computational advances are enabled by new hardware, and innovations in algorithms, numerical methods and simulation techniques, and application of best practice in scientific computational modelling. The most effective progress and highest impact can be obtained by combining, linking and simultaneously exploiting step changes in hardware, software, methods and skills. However, good computational science training is scarce, especially at post-graduate level. The Centre for Doctoral Training in Next Generation Computational Modelling will develop 55+ graduate students to address this skills gap. Trained as future leaders in Computational Modelling, they will form the core of a community of computational modellers crossing disciplinary boundaries, constantly working to transfer the latest computational advances to related fields. By tackling cutting-edge research from fields such as Computational Engineering, Advanced Materials, Autonomous Systems and Health, whilst communicating their advances and working together with a world-leading group of academic and industrial computational modellers, the students will be perfectly equipped to drive advanced computing over the coming decades.

Data storage is right at the centre of the digital age and a core developer and user of nanoscale technology. The ability to store and retrieve vast amounts of information on demand, and at miniscule cost, has revolutionised the way society functions. The device at the heart of this revolution is the hard disk drive (HDD) where over the last 50 years data densities have increased by a factor of 100,000,000 so that 1TB of storage capacity is now available in a single 3.5 inch device. The key magnetic components that have enabled this explosion in capacity are the recording head and the storage medium. The research work which forms the basis of recording head transducers, the giant magnetoresistive (GMR) effect was recognised with the 2007 Nobel prize in physics.In the work proposed here, the potential of new, highly engineered magnetic media based on thin film exchange springs will be explored. These materials allow the relationship between medium thermal stability and switching field to be tailored, so that thin films with sufficient anisotropy to avoid thermally activated reversal can still be reversed by the fields available from a write head. In order to take full advantage of these materials there is a pressing need to address the exciting fundamental questions in thin film exchange spring magnets. Specifically, what is the optimum exchange spring structure for thin films at technologically relevant thicknesses (~10 nm) that achieves maximum thermal stability whilst retaining addressability; in dense packed granular materials how does intergranular or, for patterned structures, inter-island exchange coupling modify the reversal behaviour and the thermal stability; what are the details of the spring structure during reversal; how resistant are exchange spring thin film to reversal from stray fields; what other application areas can thin film exchange springs provide enhanced functionality. The goal of our research is to provide quantitative answers to the important questions surrounding thin film exchange spring magnets. We plan to achieve this by building on the innovative vector magnetometry measurement protocols developed by the PI to determine the magnetic properties of specially designed samples, where we will systematically control the thin film exchange spring by choice of materials, coupling layers and lithographic processing. The proposed measurement programme makes full use of the vector magnetometer's ability to track the position and moment of the magnetisation vector whilst applying a field at an arbitrary angle and maintaining the sample at a set temperature. This capability allows the reversal process to be accurately characterised so that, for example, the relationship between nucleation and domain wall processes can be quantified.A critical part our programme is the work to model the behaviour of thin film exchange spring magnets and so obtain the maximum scientific output from our unique data. A simulation framework based on a kinetic Monte Carlo scheme to compute energy barriers and remanent hysteresis loops will be developed for thin film exchange spring media. This expansion of the existing simulation code will make it possible to study the effect of exchange and magnetostatic interactions on the magnetization reversal behavior. Using this newly developed capability, remanent hysteresis loops of exchange spring media will be computed for different field angles and different intergrain exchange interactions and compared directly with the experimental results.