Heterogeneous catalysts are well regarded as the workhorses of chemical transformations, being involved in over 90% of all industrial processes. Although heterogeneous catalysis offers many advantages over traditional synthetic routes, there are still some major areas where it is still lacking. For instance, with albeit a history of around 200 years, the majority of industrial processes and research using heterogeneous catalysed systems have thus far focused on either relatively small molecules (e.g. ammonia synthesis, Fischer-Tropsch process, natural gas reforming and water gas shift reactions), or traditional petrochemical/biomass feedstock (e.g. hydrocracking, polymerisation and biomass gasification, pyrolysis) and has neglected large biological molecules (such as the enzymatic cofactors) as reactants or products (in this context, "heterogeneous" refers to conventional solid bulk phase or supported metal catalysts, not immobilised enzymes or mimics). To expand the boundaries of heterogeneous catalysis to biochemistry in areas traditionally seen as belonging to biological enzymes will be fundamentally interesting, novel and attractive, facilitating potentially new routes for clean pharmaceutical and chemical production. Cofactor NAD(P)H is a critical reducing agent participating in enzymatic reductions for the synthesis of pharmaceutical/chemical products. A notable example of these products is "atorvastatin" (the active ingredient) for Lipitor ($11.9 billion global sale in 2010) which can lower the risk for heart attack and stroke, etc. or risk factors for heart disease (age, smoking, high blood pressure, etc.). The high cost of NAD(P)H and stoichiometric use make its regeneration essential for practical applications. There have been five existing methods (enzymatic, chemical, homogeneous catalytic, photo- and electro- catalytic) for this regeneration. Astonishingly, at least in part because there has been little knowledge in introducing supported metal catalysts to biological chemistry, nobody has embarked on serious studies of the potential of heterogeneous catalysts in cofactor regeneration and associated applications. This is what we plan to do. A fundamental understanding of the mechanism in the heterogeneous catalytic regeneration pathway and optimal solid catalysts will be obtained. The ultimate goal is to develop an efficient and clean process for cofactor regeneration that can work with biotransformations, taking enzymatic synthesis of pharmaceutical intermediates and CO2 conversion as representative applications.

Aerospace manufacturers are looking for flexible agile machines for automated aircraft assembly to overcome limitations of current machines, i.e., inflexibility of conventional large expensive dedicated equipments and the low stiffness and accuracy of industrial robots. Recent research shows (Hybrid) Parallel Kinematic Machine ((H)PKM) has the potential to provide the required flexibility, stiffness and accuracy. It is an emerging technology, which has been identified as the key enabler for next generation manufacturing systems, although its development is still in the initial stage. Obviously, various types of H(PKM)s will be needed for different manufacturing processes, and modular design is required for ease of reconfiguration. Therefore the machine design has to be process dependent and driven by real engineering requirements. The travel grant is for visiting the world-leading research Group of Manufacturing Equipments and Systems (GMES) in Tianjin University in China, and working together with Prof. Tian Huang and his research team for one month to explore innovative design method of PKM/HPKMs for next generation manufacturing systems for aircraft assembly. The project will initially focus on aerospace manufacturing, once successful, it will be extended to other manufacturing sectors, such as automotive and transport industries. To contribute to the UK national priority in high value manufacturing, the success of this project will bring a huge impact to the UK economy, where manufacturing accounts for 13% of GDP and more than 50% of exports. The scope of this investigation is as follows. 1) Assessing existing PKM/HPKM performance 2) Categorisation of manufacturing processes for automated aircraft assembly 3) New PKM/HPKM design and development 4) Novel performance indices for design and production 5) Topological and dimensional optimization method 6) Innovative method of productive system integration for aircraft assembly The main deliverable will be the writing of a post-visit report, which will form the basis for two to three funding applications (at least one for fundamental research and one for applications). Other deliverables will include joint publications and research exchanges in the future.

UK manufacture accounts for 13% of GDP, 50% of exports and directly employs 2.5 million people. Parallel Kinematic Machines (PKM) are a new type of machine tools and have been identified as a key technology that fills in the gap between computer numerical controlled machines and industrial robots due to their superior dynamic performance, flexibility and versatility to large-scaled parts machining. The use of PKMs creates more flexibility and dexterity in manufacturing processes while achieving high precision and high speed. This contributes significantly to the economy by improving efficiency, reducing product defects, and saving time/money/energy. The PKM integrated manufacturing system would inevitably introduce errors due to stiffness and motion of the components in the system. These errors will be accumulated through the production chain, and influence the geometrical quality of the machined parts. Predicting part quality based on error propagation in the PKM manufacturing processes represents a step change in managing production processes, as it removes the current cumbersome trial-and-error processes and enables rapid reconfiguration of production systems. Other benefits would include 20% reduction of part defects and rework, leading to a significant cost saving. Part quality resulted from interaction of manufacturing systems and machining processes, with intertwined machining errors and their propagation through multiple operations, machine tools, and fixtures and jigs. At the moment, there is no robust industrial or international standard to evaluate machining capability of PKM tools with these errors. Current trial-and-error based approach that requires a large amount of time, materials and energy, is not sustainable and suitable for future smart factories to meet frequent changes with reconfigurability. Therefore new analytical methods are urgently needed. The proposed research is adventurous in creating a new quality prediction capability for PKM based flexible manufacturing processes by revealing the relationship between manufacturing system errors and part or assembly quality. This leads to an effective error discrimination control strategy to achieve a better process control while ensuring the required product quality. Error propagation in a production process is to be explored by investigating the role of stiffness characteristics of a PKM in influencing the machining process. This will lead to the development of machining load-models in both milling and drilling on a specific machining process. Experiments are to be implemented at QUB's PKM laboratory and KCL PKM laboratory, and a map between errors and part quality is to be created through modeling and testing. This will deliver an enhanced understanding of errors and their propagation mechanism thereby leading to the identification of potential strategies for reducing individual, propagated, and residual errors. An integrated validation system that consists of a kinematic/dynamic analysis module, kinetostatic model, CAD module, and FEM module will be implemented in a virtual environment and in a manufacturing site. The project will access expertise from world-leading groups in advanced PKM machining processes. The research is highly transformative in its nature of connecting academic cutting-edge research to the practical issues encountered in complex PKM manufacture processes. Key results are to be generated and fundamental science is to be revealed in the collaborative work, training and workshops with support of AMRC, MTC and Tianjin University. The research will benefit the academic community in manufacture and robotics, and industrial sectors who will gain knowledge for reduction of errors particularly propagated errors in manufacturing processes integrated with PKMs.

Controllable Large Displacement Continuum Surfaces, LCDS, hold the potential for application across a diverse range of applications including the highly dexterous manipulation of parts in manufacturing environments, soft/flexible exoskeleton systems in healthcare, and jointless surface control in the aerospace, automotive, energy and food processing industries. Another application with immediate benefit across multiple industries would be to replace conventional mould surfaces used in the development of bespoke carbon fibre components with a single, reconfigurable surface capable of forming on-demand to desired mould profiles from digital files. Currently low volume production line moulds are produced through expensive (hand carved, milling, turning, and more recently 3D printing) methods that can account for upwards of 20% of a component's manufacturing cost. The use of LCDS systems to form on-demand mould shapes for low volume parts would result in massive savings to the production of such components. The problem is that to date LDCS operate in 'open loop' with little or no sensor feedback capability to maintain desired curvature under changing conditions, or consideration as to how external forces might best be accounted for. Additionally, placement of actuation elements on the surface to achieve complex profiles is largely accomplished through user intuition and experience, limiting efficiency at the design stage. This results in 'trial and error' methods to LDCS design and control that increase production costs and reduce surface performance under operation. To move beyond 'trial by error' design and control of LDCS undergoing large elastic deformations, accurate, yet computationally efficient, methodologies to model and simulate in both the kinematic and dynamic domains are required. This project will advance the use of LDCS into the next realm by providing the tools necessary to enable robust procedures for their design and control based not on 'trial and error', but physical model information within an accurate and efficient structure. This will not only make direct, meaningful contributions to the use of LDCS in carbon fibre production. But open further applications of LDCS to areas such as the highly dexterous manipulation of parts in manufacturing environments, soft/flexible exoskeleton systems in healthcare, and deformable surface control in the aerospace, automotive, energy and food processing industries.

Red soils cover 20% of each of China and India, the most populated countries on earth, as well as large areas of developing countries in southeast Asia, Africa and South America. They form in sub-tropical climates where excessive leaching from rainwater has produced an infertile, unstable soil that is very vulnerable to mismanagement, climate change and pollution such as acid rain. In China, red soils support about 40% of the population, made possible through the intensive use of fertilisers to boost crop yields. This farming system is unsustainable; fertilisers reaching groundwater, freshwater and the atmosphere pose a significant environmental threat, and soil degradation through intensive cultivation can result in tens of tonnes of soil being eroded each year from a hectare of land into water courses during the intensive monsoonal, spring rains. Red soil management for agriculture affects local farmers who depend on them for their livelihood, the surrounding population who need them for food, China because of dependence for national food production and globally because of the area red soils covers, their importance for food production and the large environmental footprint. Although extensive research has studied red soils, particularly related to management for agricultural sustainability, the integrated effects of various affected aspects of the critical zone, as well as the wider environmental impacts are poorly understood. In this proposal we adopt a critical zone approach, to reach beyond soil processes to encompass the atmosphere above, geology and groundwater below, surrounding freshwater and vegetation. By definition, the critical zone is the constantly evolving boundary layer at the surface of the earth where rock, soil, water, air and living organisms interact. Two essential components are essential for delivery. First, we have the major advantage of the Sunjia Critical Zone Observatory (CZO), the only international CZO in China where soil and water data have been collected since 2002. Second, we have assembled a team of Chinese and UK scientists who integrate a range of specialisations in soil science, with atmospheric, geological, hydrological and agronomical sciences. A skill gap identified amongst the Chinese partners in terrestrial environmental modelling is filled by the UK team, with training and joint positions proposed that will develop this capability in China. We build on existing Sunjia CZO monitoring by incorporating subsurface and atmospheric processes not included in the past. Further experiments in the lab and the field will allow us to explore impacts of environmental threats such as climate change, water scarcity and acid rain. We span from processes involved in weathering minerals, how these minerals interact with life to form soils, and how we can optimise these processes in soil evolution for the benefit of the environment and food security. These processes then enhance our understanding of hydrological and erosion impacts in red soils induced by different management practices. Detailed monitoring of these processes in the Sunjia CZO and other red soil areas provides data that inform our modelling of ecosystem processes. This process benefits immensely from a critical zone monitoring data-set for red soils that will span almost 20 years by the end of the project. The new science generated in this project, particularly the modelling outputs, provides valuable data for policy decisions in China about the management of red soils. We provide training to project partners in interdisciplinary science that is essential to CZO research and will benefit the research capabilities of the Chinese team. Moreover, we bring new skills to the Chinese team in terrestrial modelling. Coupled with our intended outcome of more sustainable food production from red soils, our training and government agency engagement ensures delivery of OECD Official Development Assistance from this project.