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ICME guided development of cemented carbides with alternative binder systemsWalbrühl, Martin January 2017 (has links)
The development of alternative binder systems for tungsten carbide (WC) based cemented carbides has again become of relevance due to possible changes in EU regulations regarding the use of Cobalt (Co). A framework for the ICME (Integrated Computational Materials Engineering) based Materials Design is presented to accelerate the development of alternative binder systems. Part one of this work deals with the design of the cemented carbide composite hardness. It has been shown that the intrinsic binder hardness is comparable to a bulk metal alloy and that based on the binder solubilities a solid solution strengthening model developed in this work can be employed. Using a method presented in this work the non-equilibrium, frozen-in binder solubilities can be obtained. Both the design of the binder phase and composite hardness is presented based on a general Materials Design approach. Part two deals with a multiscale approach to model the surface gradient formation. The experimentally missing data on liquid binder diffusion has been calculated using AIMD (Ab initio Molecular Dynamics). The diffusion through the liquid cemented carbide binder has to be reduced to an effective diffusion value due to the solid carbides acting as obstacles that increase the diffusion path. The geometrical reduction of the diffusion has been investigated experimentally using the SIMS (secondary ion mass spectroscopy) technique in WC-Nickel-58Nickel diffusion couples. The geometrical contribution of the so-called labyrinth factor has been proven by the combination of the experiments and in conjunction with DICTRA simulations using the precise liquid AIMD diffusivities. Unfortunately, despite the improved kinetic database and the geometrical diffusion reduction, the surface gradient formation cannot be explained satisfactory in complex cemented carbide grades. Additional, but so far unidentified, contributions have to be considered to predict the surface gradient thickness. / <p>QC 20170919</p>
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