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XAAR PLC

12 Projects, page 1 of 3
  • Funder: UK Research and Innovation Project Code: 100670
    Funder Contribution: 316,400 GBP

    The public description for this project has been requested but has not yet been received.

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  • Funder: UK Research and Innovation Project Code: EP/E502784/1
    Funder Contribution: 88,935 GBP

    High Speed Sintering (HSS) has been invented under EPSRC funded research at Loughborough University. The process allows the manufacture of complex components by sintering powder in successive layers, in a manner similar to an existing commercially valuable Rapid Manufacturing process called Selective Laser Sintering (SLS). At Loughborough we have been able to prove that HSS works when making polymeric parts in a small area (50mmxl00mm). However it is only by making parts over a big area that HSS will be commercially competitive. If we are able to make high strength parts over a much bigger area (280mmx330mm) then HSS should prove to be 10 times faster than SLS and around 5 times cheaper. By successfully making parts on a big area using HSS we are confident that we will be able to convince companies to license the technology (under our patents) and make commercial HSS machines. We have various research projects in progress and in the pipeline to support this work, however the Follow on Fund project is the only work directly aimed at securing a license.

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  • Funder: UK Research and Innovation Project Code: EP/J010685/1
    Funder Contribution: 120,959 GBP

    Piezoelectric ceramics are becoming used increasingly as the basis for electromechanical sensors and actuators for control, medical, electronic and microelectronic machine (MEMS) applications. Electromechanical actuators take benefit from the strain resulting from the application of an electric field in ferroelectric materials. Many sources of internal stress can arise in actuation devices. First the manufacturing process can introduce residual stresses. The boundary conditions related to the actuator packaging is another source of operating stress. At a finer scale still, due to the heterogeneity of ferroelectric materials (polycrystalline structure), the piezoelectric strain is usually not compatible, resulting in internal stresses when an electric field is applied. Despite its significant role, the dependence of the internal stress on the piezoelectric strain is rarely accounted for in the design of actuators, mainly because it is difficult to quantify or predict. The development of micro-macro models of ferroelectric behaviour provides a pathway to establish fully coupled electro-mechanical constitutive laws for ferroelectric materials. Such constitutive laws will improve the quantitative description of electric field induced strains, and allow the optimisation of piezoelectric actuator design. Consequently, through the development of multiscale tools the objective of this project is to describe in a quantitative way the effect of applied and internal stress on ferroelectric behaviour. This will provide the tools to design high performance ferroelectric actuators.

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  • Funder: UK Research and Innovation Project Code: EP/N024915/1
    Funder Contribution: 1,945,930 GBP

    Toothpastes - and especially specialised pharmaceutical toothpastes, whose major gel component is not water-based - have a surprisingly complex and ill-understood manufacturing process. There is the background fluid, which is already a mixture of a viscous liquid and a polymer; then solid particles are added. These are abrasive and do much of the tooth cleaning; but they also swell during processing, and the system becomes much thicker when they are added. Finally surfactant is added to help the toothpaste to foam in the mouth; and just to complicate matters further, air bubbles also creep in during processing. In this project, we will systematically address all the stages of toothpaste processing. We will carry out precise small-scale rheological measurements to discover how the particles swell and how they interact once they have swollen: for example, do they absorb parts of the long polymer molecules to form a network, or do partly-absorbed polymers act as "brushes" to push swollen particles apart? We will also measure the overall behaviour of each stage of the system (the background fluid on its own, or with particles, or with bubbles) and create a phase map of system behaviour in terms of its composition. We will use advanced mathematical modelling techniques to derive new equations that can describe the behaviour of a mixture - for example, background fluid and swollen particles - as if it were a single material. Finally, we will use our new constitutive equations in computer simulations to predict the behaviour of the paste in a real processing environment, address the manufacturing challenges such novel formulations entail and propose new strategies to overcome these. The research needs a team with many different specialist abilities, across experimentation, modelling and simulation, and also needs close ties with industry to ensure we are asking the right questions. GSK is a major collaborator on this project. The project is also supported by Xaar the leader in inkjet printing technology. With the understanding we generate, they hope to make their manufacturing processes both more efficient and more reliable and also develop new formulations to address future customer needs.

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  • Funder: UK Research and Innovation Project Code: EP/R028826/1
    Funder Contribution: 321,647 GBP

    The surface topography of a component part can have a profound effect on the function of the part. In tribology, it is the surface interactions that influence such quantities as friction, wear and the lifetime of a component. In fluid dynamics, it is the surface that determines how fluids flow and it affects such properties as aerodynamic lift, therefore, influencing efficiency and fuel consumption of aircraft. Examples of the relationships between the topography of a surface and how that surface functions in use can be found in almost every manufacturing sector, both traditional and high-tech. To control surface topography, and hence the function and/or performance of a component, it must be measured and useful parameters extracted from the measurement data. There are a large number instruments that can measure surface topography, but many of them cannot be used realistically for real-time in-process applications due to the need for scanning in either the lateral axes and/or the vertical axis. There have been developments in area-integrating (scattering) methods for measuring surface topography that can be fast enough to use during a manufacturing process, but these are limited in the height range of surface topography with which they can be used. In conventional machining, there has been a significant research effort to determine the surface topography of the machined parts during the manufacturing process. The dominant technology for this has been machine vision approaches, where a relationship between a texture parameter and an aspect of the measured field from an intensity sensor is determined. Such approaches have two major drawbacks: 1. they are usually applied to surfaces with geometrical features over a limited range and 2. they do not have the benefit of a physical model of the measurement process, i.e. they are purely empirical. As an example, the measurement and characterisation of the surface topography of additive manufactured parts remains a significant challenge, especially where measurement speed may be an issue. Typical metal additive manufactured surfaces have a large range of surface features, with the dominant features often being the weld tracks with typical wavelengths of a few hundred micrometres and amplitudes of a few tens of micrometres; such structures are beyond what can be measured effectively with existing commercial approaches. In the proposed project, we aim to demonstrate that it is possible to measure rough and structured, machined or additive surfaces using a simple, cost-effective real-time measurement system. This will involve the development of a fully rigorous three-dimensional optical scattering model, which will be combined with a machine learning approach to mine optical scattering data for topographic information that is not within the range of commercial scattering instruments. The proposed system could be mounted into a machining or additive operation without slowing down the process, therefore, reducing the cost of many advanced products that require engineered surfaces. To demonstrate the commercial potential of the project outputs, we have several advanced manufacturing partners who will supply industrially relevant case studies and one partner who could act as the commercial exploitation route for the instrument.

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