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Composition dependence and thermal hysteresis of martensitic transformations in Ni-Ti based shape memory alloys

Ni-Ti 基形状记忆合金中马氏体相变的成分依赖性和热滞后

基本信息

批准号：
211979735
负责人：
Dr. Oleg Shchyglo
金额：
--
依托单位：
Interdisciplinary Centre for Advanced Materials Simulations
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2012
资助国家：
德国
起止时间：
2011-12-31 至 2014-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/211979735?language=en
关键词：
Composition dependence thermal hysteresis martensitic

项目摘要

Martensite is formed by a massive phase transformation without solute redistribution and long range diffusion, but strongly dependent on the composition in many materials. In this project we address the effect of composition on the martensite phase formation in Ni-Ti shape memory alloys. We plan to develop a CALPHAD type Gibbs energy model to derive elastic constants of a binary alloy in dependence of its composition and temperature. The model data will be calculated from first principles. Special emphasis will be given to soft modes which are expected to play an important role in starting martensitic transformation. The model will be coupled to a phase-field model of martensitic transformation. Large scale 3-D simulations will be performed to investigate the effect of varying alloy composition and its gradients (segregation bands) on the martensitic transformation temperature. Further-on, nucleation of martensitic variants during the propagation of the martensitic front will be investigated to establish a relation between the scale of the martensitic lamellae, undercooling and alloy composition. The simulations will be compared to available experimental observations of martensitic transformation in Ni-Ti shape memory alloys. The model is expected to contribute to a physically based explanation of the strong dependence of martensite hysteresis on composition. It shall be extendable to different types of martensitic transformations and material classes.

马氏体是由大量相变形成的，没有溶质再分布和长距离扩散，但在许多材料中强烈依赖于成分。在这个项目中，我们研究了成分对Ni-Ti形状记忆合金中马氏体相形成的影响。我们计划建立一个CALPHAD型吉布斯能量模型来推导二元合金的弹性常数与其成分和温度的关系。模型数据将根据第一性原理进行计算。特别强调软模态，它们在马氏体相变中起着重要的作用。该模型将与马氏体相变相场模型耦合。将进行大规模三维模拟，以研究不同合金成分及其梯度（偏析带）对马氏体相变温度的影响。此外，还将研究马氏体锋扩展过程中马氏体变异体的形核，以建立马氏体片层规模、过冷度和合金成分之间的关系。模拟结果将与Ni-Ti形状记忆合金中马氏体相变的实验观察结果进行比较。该模型有望为马氏体迟滞对成分的强烈依赖提供基于物理的解释。它应扩展到不同类型的马氏体相变和材料类别。