4,934 research outputs found

    Fabrication of metal matrix composites under intensive shearing

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    Current processing methods for metal matrix composites (MMC) often produces agglomerated reinforced particles in the ductile matrix and also form unwanted brittle secondary phases due to chemical reaction between matrix and the reinforcement. As a result they exhibit extremely low ductility. In addition to the low ductility, the current processing methods are not economical for producing engineering components. In this paper we demonstrate that these problems can be solved to a certain extent by a novel rheo-process. The key step in this process is application of sufficient shear stress on particulate clusters embedded in liquid metal to overcome the average cohesive force of the clusters. Very high shear stress can be achieved by using the specially designed twin-screw machine, developed at Brunel University, in which the liquid undergoes high shear stress and high intensity of turbulence. Experiments with Al alloys and SiC reinforcement reveal that, under high shear stress and turbulence conditions Al liquid penetrates into the clusters and disperse the individual particle within the cluster, thus leading to a uniform microstructure

    Computational prediction of the refinement of oxide agglomerates in a physical conditioning process for molten aluminium alloy

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    Physically conditioning molten scrap aluminium alloys using high shear processing (HSP) was recently found to be a promising technology for purification of contaminated alloys. HSP refines the solid oxide agglomerates in molten alloys, so that they can act as sites for the nucleation of Fe-rich intermetallic phases which can subsequently be removed by the downstream de-drossing process. In this paper, a computational modelling for predicting the evolution of size of oxide clusters during HSP is presented. We used CFD to predict the macroscopic flow features of the melt, and the resultant field predictions of temperature and melt shear rate were transferred to a population balance model (PBM) as its key inputs. The PBM is a macroscopic model that formulates the microscopic agglomeration and breakage of a population of a dispersed phase. Although it has been widely used to study conventional deoxidation of liquid metal, this is the first time that PBM has been used to simulate the melt conditioning process within a rotor/stator HSP device. We employed a method which discretizes the continuous profile of size of the dispersed phase into a collection of discrete bins of size, to solve the governing population balance equation for the size of agglomerates. A finite volume method was used to solve the continuity equation, the energy equation and the momentum equation. The overall computation was implemented mainly using the FLUENT module of ANSYS. The simulations showed that there is a relatively high melt shear rate between the stator and sweeping tips of the rotor blades. This high shear rate leads directly to significant fragmentation of the initially large oxide aggregates. Because the process of agglomeration is significantly slower than the breakage processes at the beginning of HSP, the mean size of oxide clusters decreases very rapidly. As the process of agglomeration gradually balances the process of breakage, the mean size of oxide clusters converges to a steady value. The model enables formulation of the quantitative relationship between the macroscopic flow features of liquid metal and the change of size of dispersed oxide clusters, during HSP. It predicted the variation in size of the dispersed phased with operational parameters (including the geometry and, particularly, the speed of the rotor), which is of direct use to experimentalists optimising the design of the HSP device and its implementation.This research is financially supported by the EC FP7 project “High Shear Processing of Recycled Aluminium Scrap for Manufacturing High Performance Aluminium Alloys” (Grant No. 603577)

    Thermal Runaway of a Li-Ion Battery Studied by Combined ARC and Multi-Length Scale X-ray CT

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    Lithium ion battery failure occurs across multiple length scales. In this work, the properties of thermal failure and its effects on electrode materials were investigated in a commercial battery using a combination of accelerating rate calorimetry (ARC) and multi-length scale X-ray computed tomography (CT). ARC measured the heat dissipated from the cell during thermal runaway and enabled the identification of key thermal failure characteristics such as onset temperature and the rate of heat generation during the failure. Analysis before and after failure using scanning electron microscopy (SEM) and X-ray CT were performed to reveal the effects of failure on the architecture of the whole cell and microstructure of the cathode material. Mechanical deformations to the cell architecture were revealed due to gas generation at elevated temperatures (>200 °C). The extreme conditions during thermal runaway caused the cathode particles to reduce in size by a factor of two. Electrode surface analysis revealed surface deposits on both the anode and cathode materials. The link between electrode microstructure and heat generation within a cell during failure is analysed and compared to commercially available lithium ion cells of varying cathode chemistries. The optimisation of electrode designs for safer battery materials is discussed

    Application of whole genome and RNA sequencing to investigate the genomic landscape of common variable immunodeficiency disorders.

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    Common Variable Immunodeficiency Disorders (CVIDs) are the most prevalent cause of primary antibody failure. CVIDs are highly variable and a genetic causes have been identified in <5% of patients. Here, we performed whole genome sequencing (WGS) of 34 CVID patients (94% sporadic) and combined them with transcriptomic profiling (RNA-sequencing of B cells) from three patients and three healthy controls. We identified variants in CVID disease genes TNFRSF13B, TNFRSF13C, LRBA and NLRP12 and enrichment of variants in known and novel disease pathways. The pathways identified include B-cell receptor signalling, non-homologous end-joining, regulation of apoptosis, T cell regulation and ICOS signalling. Our data confirm the polygenic nature of CVID and suggest individual-specific aetiologies in many cases. Together our data show that WGS in combination with RNA-sequencing allows for a better understanding of CVIDs and the identification of novel disease associated pathways

    Melt Conditioned Direct Chill Casting (MC-DC) Process for Production of High Quality Aluminium Alloy Billets

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    A novel direct chill (DC) casting process, melt conditioned direct chill (MC-DC) casting process, has been developed for production of high quality aluminium alloy billets. In the MC-DC casting process, a high shear device is submerged in the sump of the DC mould to provide intensive melt shearing, which in turn, disperses potential nucleating particles, creates a macroscopic melt flow to uniformly distribute the dispersed particles, and maintains a uniform temperature and chemical composition throughout the melt in the sump. Experimental results have demonstrated that, the MC-DC casting process can produce aluminium alloy billets with significantly refined microstructure and reduced cast defects. In this paper, we give an overview of the MC-DC casting process and report on results obtained from an industrial scale trial
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