Search for compatible Zirconia-based shape memory ceramics

金属形状记忆合金（SMA）显示出两种感兴趣的性质：用于固态致动器的形状记忆效应和例如用于自膨胀医疗植入物的超弹性。它们基于奥氏体和马氏体相之间的可逆的、热或应力诱导的一级相变，具有大的内应力，这导致大的应变和焓变化。通过两相的相容性实现可逆性，这导致界面处的局部应力和滞后的减小。这种兼容性可以通过转换矩阵的平均特征向量理想情况下必须为1的条件来表示。由于金属SMA中使用的元素，在腐蚀性化学条件或极端温度下使用是困难的。这促使了一类新的形状记忆材料，它由金属氧化物组成，被称为形状记忆陶瓷（SMC）。虽然Swain在1986年首次发现了一种合适的氧化物（MgO稳定的ZrO 2），但迄今为止缺乏相容性导致了循环时裂纹和严重疲劳的发展。在先前的研究中，关于金属SMA中相容性的发现被转移到系统（Y0.5Ta0.5O2）1-x（Zr0.5Hf0.5O2）x中的陶瓷对应物中。的主要结果是一个显着的组合物上的相变滞后的依赖性和强烈的依赖性的应力诱导的取向的马氏体变体上的滞后，但没有接近金属SMA的性能。平均特征值的依赖性也不同：鉴于两个可能的转换机制，结果表明，组合物，其中的兼容性为两个转换同样很好地履行，定义了最低的滞后点（等距条件）。本申请的主要目标是寻找SMC具有低滞后和良好的形状记忆性能。该搜索是基于包含大约70种不同的基于ZrO 2的SMC的数据集，其具有转变温度和晶体学数据。相应的工作假设是，对于SMC， 除了这个主要目标之外，我们还将研究基于物理参数的可用数据集的机器学习方法是否适合于识别SMC的组合物，该SMC在滞后方面具有显着改善的性能，变换可逆性

Metallic shape memory alloys (SMA) show two properties of interest: the shape memory effect used for solid state actuators and the superelasticity e.g. for self-expanding medical implants. They are based on a reversible, thermal or stress-induced phase transition of the first order between austenite and martensite phases with large internal stresses, which lead to large strains and enthalpy changes. The reversibility is achieved through the compatibility of the two phases, which leads to a reduction in the local stresses at the interface and the hysteresis. This compatibility can be expressed by the condition that the mean eigenvector of the transformation matrix ideally has to be one.Due to the elements used in metallic SMA, use under corrosive chemical conditions or at extreme temperatures is difficult. This motivates a new class of shape memory materials, which consist of metal oxides and are called shape memory ceramics (SMC). Although Swain first identified a suitable oxide (MgO-stabilized ZrO2) in 1986, the lack of compatibility to date leads to the development of cracks and severe fatigue upon cycling.In prior own research the findings regarding compatibility in metallic SMA were transferred to their ceramic counterparts in the system (Y0.5Ta0.5O2)1-x (Zr0.5Hf0.5O2)x. The main results were a significant dependence of the transformation hysteresis on the composition and a strong dependency of the stress-induced orientation of the martensitic variants on the hysteresis, without however approaching the properties of metallic SMA. The dependence on the mean eigenvalue also differs: Given the two probable transformation mechanisms, the results suggest that the composition, in which the compatibility for both transformations is equally well fulfilled, defines the point of lowest hysteresis (equidistance condition).The main goal of this application is the search for SMC with low hysteresis and good shape memory properties. This search is based on a data set containing approximately 70 different ZrO2-based SMC with the transformation temperatures and the crystallographic data. The corresponding working hypotheses are that for SMC the mean eigenvalues ​​of both lattice correspondences must be as close as possible to one and that these conditions lead to two lattice parameter relations that suggest searching for dopants that reduce the tetragonality.In addition to this main objective we will investigate whether a machine learning approach based on the available data set of physical parameters will be appropriate to identify compositions for SMC with significantly improved properties in terms of hysteresis and transformation reversibility.