Browsing by Subject "Shape memory alloys"

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    Cofactor Conditions in the Design of Reversible Martensitic Phase Transformation Materials
    (2020-08) Gu, Hanlin
    Shape memory materials are widely used in solid-state actuators, medical implants, elastocaloric cooling devices and so on. In these applications, the materials are subjected to stress or thermal cyclic load. The fatigue of the materials is critical to the lifetime of the devices. This thesis is focused on the development of shape memory alloys (SMAs) and ceramics (SMCs) with low stress or thermal hysteresis to resist functional fatigue by tuning the lattice parameters of the materials to satisfy strong compatibility conditions between martensite and austenite phases – Cofactor Conditions. Cofactor conditions are derived from geometrically nonlinear theory of martensitic transformation. It has been proved that, for SMAs, the fatigue life can be dramatically improved by satisfying these conditions. To have a better understanding of the strong compatibility conditions of martensitic transformation, a new visualization method is developed. In medical device industry, shape memory alloys are terribly interested as their superelastic property. Binary NiTi alloys are frequently used in heart stent devices. Study about the potential of low fatigue binary NiTi alloys with cubic to orthorhombic or cubic to R-phase to monoclinic transformation is discussed. A summary of a number of alloy systems using the new visualization method implies the limitation of cubic to orthorhombic transformation and the advantage of cubic to monoclinic transformation in medical device applications. In general, ceramic materials are known as brittle materials. To achieve low func- tional fatigue for SMCs, the experiments of lattice parameter tuning are conducted. The results prove that the cofactor conditions are also correlated to the thermal hysteresis in Ba(Ti1−xZrx)O3, (Y0.5Ta0.5O2)1−x–(Zr0.5Hf0.5O2)x, and (ZryHf1−yO2)x–(Y0.5Nb0.5O2)1−x ceramic sys- tems. In the development of (ZryHf1−yO2)0.775–(Y0.5Nb0.5O2)0.225, when y > 0.8, the material exhibits exploding or weeping behavior. It’s affected by the mismatch of neighboring grains with plane strain dominated martensitic transformation. The study of cofactor conditions is an efficient tool to develop low functional fatigue shape memory materials. Although for polycrystalline materials further research is demanded, they still reveal the essence of the functional fatigue problem related to the microstructure of martensitic transformation and bring the potential for material design from microstructure to macro behavior.
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    A new framework for the interpretation of modulated martensites in shape memory alloys
    (2013-06) Jusuf, Vincent
    Shape memory alloys (SMAs) are a class of materials with unusual properties that have been attributed to the material undergoing a martensitic phase transformation (MPT). An MPT consists of the material's crystal structure evolving in a coordinated fashion from a high symmetry austenite phase to a low symmetry martensite phase. Often in SMAs, the austenite is a B2 cubic configuration that transforms into a Modulated Martensite (MM) phase. MMs are long-period stacking order structures consisting of cubic (110) basal planes. First-principles computational results have shown that the minimum energy phase for these materials is not a MM, but a short-period structure called the ground state martensite. It is commonly argued that energy contributions associated with kinematic compatibility constraints at the austenite-martensite interface explain the experimental observation of meta-stable MMs, as opposed to the expected ground state martensite phase. To date, a general approach for predicting the properties of the MM structure that will be observed for a particular material has not been available. In this work, we develop a new framework for the interpretation of MMs as natural features of the material's energy landscape (expressed as a function of the lattice parameters and individual atomic positions within a perfect infinite crystal). From this energy-based framework, a new understanding of MMs as a mixture of two short-period base martensite phases is developed. Using only a small set of input data associated with the two base martensites, this Modulated Martensite Mixture Model is capable of accurately predicting the energy, lattice constants, and structural details of an arbitrary modulated martensite phase. This is demonstrated by comparing the Modulated Martensite Mixture Model predictions to computational results from a particular empirical atomistic model.