Many technological advances in modern day life are dependent upon the development of new materials, or better control and understanding of existing materials. Understanding the detailed properties of materials has therefore never been more important. The development of high quality computer simulation techniques has played an increasingly significant role in this endeavour over recent years. The UK has been at the forefront of this new wave, and the UKCP consortium has played an important part, in both developing computer codes and algorithms, and exploiting these new advances to increase our understanding of many industrially relevant materials and processes. The preferred mechanism for providing computational resources on the UK national supercomputer (ARCHER) is via large research consortia, and this proposal funds the UKCP consortium. This is a large and established consortium, containing 22 different nodes and over 160 active researchers. Each node is a different University Department and is represented by one key academic - see the "Linked Proposals" or the Track Record for a complete list of current members of UKCP. This proposal seeks computational support for a large body of research (see "Other Support") with a substantial allocation of ARCHER resources and also the support of a named Research Software Engineer (RSE). The RSE will assist with training and supporting different members of the consortium in using the principle codes used within the consortium (e.g. CASTEP), and also develop some of the new code features required to complete some of these projects. As part of this proposal, the researchers will have to develop new algorithms and also make theoretical improvements that will increase our simulation abilities (either by increasing the accuracy and reliability of calculations, or by enabling us to simulate bigger systems for longer). New algorithms include machine learning to generate new model potentials derived from accurate quantum mechanical calculations for fast calculations of large systems, improved structure optimisation, and uncertainty quantification. New functionality includes new spectroscopies, including magnetic structure, vibrations, neutron scattering and muon decay. Together, these innovations will enable the next generation of simulations and further widen our computational horizons. The research described in this proposal will make significant impacts on many areas of future technology, such as semiconductor nanostructures, protein-drug optimization, ultra-high temperature ceramics, nanoscale devices, hybrid perovskites and solar cells and inorganic nanotubes and metal-air battery anodes. There are also areas of fundamental research, designed to push our understanding of basic properties of matter, such as interfacial water, nanocrystal growth, structure of grain boundaries, pigment-protein complexes, radiation damage in DNA and high-pressure hydrogen phases. The research proposed does not easily fit into any of the traditional categories of 'physics' or 'chemistry' etc. Instead, the UKCP is a multi-disciplinary consortium using a common theoretical foundation to advance many different areas of materials-based science which has the potential for significant impact both in the short and long-term.

In the UK, musculoskeletal disorders (joint and back problems) affect one in five people long term. While joint replacements are successful, they are challenged by demands of an active and younger population presenting with disorders due to trauma, obesity, or other lifestyle choices. One of the causes for joint and back pain is the deterioration of the different soft tissues acting as cushions in the joints. New surgical interventions are being developed to repair or locally replace those soft tissues in order to delay or prevent a total joint replacement. There is no clear indication yet on which patients benefit the most from them. There is an urgent need to define the type of patients for which new and existing interventions are most beneficial. The local anatomy or level of tissue deterioration differs greatly between patients, and there is currently a lack of biomechanical evidence that takes into account these large variations to help matching patients to interventions. To tackle these issues, this Fellowship, MSKDamage, will develop novel testing methods and tools combining laboratory simulation with computer modelling and imaging. MSKDamage methods will be used to predict the variation in the mechanical performance of a series of treatments at various levels of joint deterioration. This will enable the different interventions to be matched to different patient's characteristics. I will focus on three musculoskeletal disorders and associated repairs: 1. Emerging treatments involving the injection of biomaterials in the intervertebral disc: I will produce realistic testing conditions that can be personalised to a specific patient, assessing each patient's chance of success and identifying areas for treatment optimisation. 2. Evaluation of meniscus repairs in the knee and their interaction with cartilage defects: I will provide new information on the type of cartilage defect that reduces the chances of success of a meniscus replacement in the knee. The research will develop guidance on the type of cartilage defects that need repair for a meniscus replacement to be successful. 3. Optimisation of custom wrist repair: I will help optimise patient-specific wrist repairs so that they reduce the damage in tendons and ligaments in the wrist. MSKDamage builds on my strong track-record in the field and network of industry, clinical and academic collaborators, as well as my recent work that demonstrates the specific information which need to be included in models of degraded tissues in the spine and the knee. MSKDamage aims to (1) develop a methodology to test interventions for a specific patient and its specific tissue degradation, (2) carry out a series of case studies which demonstrate the capacity to test a range tissues disorders and repairs. This work is a particularly suitable for a Fellowship, as it will allow me to develop fundamental engineering tools and methods while engaging with end users for significant economic and societal impact. I will also develop as a leader in the field, leading a growing research group and taking actions for the research community, directly related to the research, with advocacy on sharing more research outcomes openly for creation of more impact, and indirectly related to act as an ambassador for public and patient involvement for research related to computer simulations in healthcare.

The introduction of Carbon Fibre Reinforced Plastics (CFRP) for major structural parts in commercial aircraft leads to the need to predict the mechanical response, including failure and damage tolerance for these materials. The difficulty in predicting accurately failure and damage tolerance lies both on the complexity of the failure processes and in the scale at which they occur. In fact, the scales at which failure must be analysed (micro meters) are much smaller than the typical aerospace component scale (metres), and it is well known that strength and toughness depend on component size.This proposal will address the above, by focusing on three challenges. Firstly, the project will assess how tough these composites are at opposing the propagation of cracks which break entire panels (mixed mode translaminar fracture toughness). In continuation, the failure processes will be looked at in detail, so that suitable micromechanical models may be developed. Finally, the project will focus on developing computer codes which will assist Engineers in more effectively designing composite components.

Traditional engineering ignores complex interactions across several space-time scales, which does not fit the context of modelling of biological systems where scales overlap and the inherent complexity of multi-scale interaction cannot be avoided. For this reason, in the previously funded MultiSim project, we established a computational platform for the investigation of musculoskeletal disorders, which we successfully applied to the prediction of the risk of fracture in osteoporotic and osteopenic women, and to the pre-clinical investigation of bone remodelling in animal models to assess the effect of new treatments. Full exploitation of this platform, however, is limited by the fact that most of the MultiSim activities evolved around skeletal health only. MultiSim2 will allow us to expand the focus of our Centre to include an equivalently robust and detailed modelling of the skeletal muscles to predict the effects of pathologies such as sarcopenia or neurodegenerative diseases. To do so, we will develop new approaches for better imaging, characterisation and modelling of the muscles and of their interaction with the skeletal system. In our murine work, we will focus on developing noninvasive longitudinal imaging techniques and computational models to support the reduction and partial replacement of the use of mice in musculoskeletal research. We will measure longitudinal changes in muscle properties by using a micro-magnetic resonance imaging (microMRI) system and advanced image processing to predict tissue changes over time. These measurements will be integrated to a framework of available tools to obtain bone properties at high resolution with in vivo micro-Computed Tomography (microCT) and to co-register all the acquired data in space and time. We will use our human models to predict physiological and pathological changes of muscle volumes and masses, variations in muscle fibres, tendon geometric and elastic properties and changes associated with degeneration in the neuromotor control. The comprehensive assessment of changes in different musculoskeletal tissues (bone, muscles, tendons) over time in both patients and animals will allow us to create a combined experimental and computational framework to better understand and model the effect of diseases and to optimise future treatments.

Models of complex chemical processes such as combustion or atmospheric chemistry assume that the molecules taking part are thermalized, that is that their energy is characterized by the temperature of the system. Chemical activation (CA) occurs when the energy released by a reaction is channelled into the products and they have an energy greater than would be thermally predicted. How does the reactivity of these activated species compare with their thermalized equivalents? What is the significance of CA? How can CA be incorporated into chemical models of complex systems? These are the questions at the heart of our project: Complex Chemistry and Chemical Activation (C3A). Aspects of CA have been known about for more than 100 years, indeed 2022 marks the centenary of the Lindemann Mechanism, the first theory proposed to explain the pressure dependence of some chemical reactions. Models of CA have grown in sophistication, yet uncertainties in key processes (energy transfer, calculation of densities of states) limit the accuracy of kinetic and thermodynamic predictions from such systems. Addressing the uncertainties in these aspects of current models through new experimental data and developments in fundamental models is one strand of C3A. More recently, work in this group and elsewhere has shown that systems which were thought to be adequately modelled by thermalized reagents, such as abstraction reactions (e.g. OH + HCHO), do need to considered in the context of chemical activation. In a 2018 review, Klippenstein states: 'These studies ultimately led us to the realization that at combustion temperatures, the foundational assumption of thermalization prior to reaction is not always valid, and further that its breakdown significantly affects key combustion properties' (Proceedings of the Combustion Institute, 36, p77). These phenomena are not limited to combustion; plasma chemistry and the atmospheric chemistry of Earth and other planets provide other important examples of applications. C3A is a collaboration between leading groups from Leeds and Oxford, both with interests in experiments and theory. C3A will generate a wealth of new experimental data, which in combination with theoretical interpretation, will allow us to assess the significance of CA in real systems and provide the tools to allow CA to be accurately incorporated into chemical models of of these processes. The impact of C3A to industry will be facilitated by collaborations with Shell, Dassault Systemes and AirLabs. Such models are essential tools for understanding important questions from current highly practical issues (how can combustion systems be optimized to minimize CO2 emissions and improve air quality) to future questions (biofuels for aviation, novel methods of renewable energy storage such as ammonia generation and combustion) to important, fundamental questions such as modelling the atmospheres of hot-Jupiter exo-planets or the interstellar medium. The accurate assessment and incorporation of CA into such models will significantly enhance their reliability and predictive value.