Collaborative Research: Design of Low-Hysteresis High-Susceptibility Materials by Nanodomain Engineering

该奖项支持理论和计算研究，旨在为形状记忆合金以及铁电和铁磁材料开发新的设计概念和原则，以实现各种应用的改进功能。在这些材料中，结构域可以通过施加外场(如应力、电场或磁场)从一个切换到另一个，从而允许同时实现传感和驱动。这些智能材料在许多领域都有关键的应用，包括医疗设备、卫星、机器人、导航系统、数据存储和检索、机电和光电系统等等。然而，在这些材料中形成的典型的磁畴结构太大，导致性能不适合应用。另一个常见的问题是导致过早衰竭的功能疲劳。PI将使用先进的计算和理论方法来研究新的设计概念和原理，这些设计概念和原理将晶体结构、缺陷、磁区结构和功能特性联系起来。这些设计概念和原则旨在指导实验工作，加速发现具有最佳性能的新型智能和结构材料。这与材料基因组倡议是一致的。这个项目将直接培养研究生，让他们立即为综合计算材料科学和工程的成功做出贡献。此外，对参与材料开发的研究人员的培训将使他们能够迅速接受新的设计概念和方法，从而提高材料技术员的效率。该项目的教育推广旨在对鼓励代表不足群体的高中生进入科学和工程学科产生重大影响。技术总结该奖项支持专注于铁基功能材料的理论和计算研究，包括形状记忆合金，以及铁电和铁磁材料。该项目的主要目标是通过设计(A)转变路径网络和(B)结构和化学异质性，加速发现新型低滞后、高灵敏度、抗疲劳的铁基功能材料。前者探索了通过识别具有孤立的圆形相变路径的系统来获得高磁化率的方法，而后者探索了如何通过抑制自催化和调节铁相相变期间磁畴生长和粗化的空间程度来将传统的微米级、长程有序、自适应的应变、极化和磁化磁畴转变为纳米磁畴。基于群论、相变结晶学和图论方法，我们将建立一个严密的理论框架来分析转化途径网络。通过对TPN图的对称性和拓扑性的研究，提出了一种新的结构相变分类。PI旨在区分三种不同的TPN类型：一种是可以提供高敏感性的，一种是可逆的并表现出形状记忆效应，另一种是可以通过引起功能疲劳的转变产生错位的。PI将对特定的体系进行系统的第一原理和原子计算，以帮助构建和分类TPN图，量化能量景观，并调查各种晶体缺陷的影响。最后，将进行相场模拟，以研究可能的连续相分离和其他在母相中产生纳米级结构和化学不均匀的机制，并研究它们对随后的铁相相变和铁相纳米结构域形成的影响。这些铁性纳米结构域对温度和外场的响应将被记录下来。微域材料具有与微域材料截然不同的特性，特别是超低模数准线性伪弹性、低磁滞、高灵敏度，如巨压电性、超大磁致伸缩和大的非滞后应变响应，以及较强的抗疲劳性能。该项目的教育宣传旨在对鼓励属于代表性不足群体的高中生进入科学和工程学科产生重大影响。

NONTECHICAL SUMMARYThis award supports theoretical and computational research aimed to develop new design concepts and principles for shape memory alloys, and ferroelectric and ferromagnetic materials to achieve improved functionality for various applications. In these materials structural domains can switch from one to another by the application of an external field, such as stress, electric or magnetic fields, allowing sensing and actuation to be realized simultaneously. These smart materials have found critical applications in many fields, including medical devices, satellites, robots, navigation systems, data storage and retrieving, electromechanical and electro-optic systems, to name a few. However, typical domain structures formed in these materials are too large leading to properties that are not optimal for applications. Another common problem is that functional fatigue that leads to premature failure. The PIs will use advanced computational and theoretical methods to investigate new design concepts and principles that connect crystal structure, defects, domain structure and functional properties. These design concepts and principles are aimed to guide experimental efforts and accelerate the discovery of new smart as well as structural materials with optimal properties. This is in alignment with the Materials Genome Initiative. This project will directly prepare graduate students to immediately contribute to the success of integrated computational materials science and engineering. Additionally, the training of researchers involved in materials development will afford a rapid uptake of new design concepts and methodology, resulting in increased effectiveness of materials technologists. The educational outreach of the project is designed to have a significant influence on encouraging high school students who are members of underrepresented groups to enter science and engineering disciplines.TECHNICAL SUMMARYThis award supports theoretical and computational research that focuses on ferroic-based functional materials including shape memory alloys, and ferroelectric and ferromagnetic materials. The main objective of this project is to accelerate the discovery of novel low-hysteresis high-susceptibility ferroic-based functional materials with strong fatigue resistance via the design of (a) transformation pathway networks, and (b) structural and chemical heterogeneities. The former explores the means to achieve high susceptibility by identifying systems with isolated circular transformation pathways, while the latter explores how to transform conventional micron-sized, long-range ordered, self-accommodating strain, polarization and magnetization domains into nanodomains by suppressing autocatalysis and regulating the spatial extent of domain growth and coarsening during ferroic phase transitions. A rigorous theoretical framework will be developed based on group theory, phase transformation crystallography and graph methods to analyze transformation pathway networks (TPNs). Through investigating the symmetry and topology of TPN graphs, a new classification of structural phase transformations will be introduced. The PIs aim to distinguish three distinct TPN types: ones that could provide high susceptibility, ones that are reversible and exhibit shape memory effect, and ones that could generate dislocations through transformations causing functional fatigue. The PI will perform systematic first principles and atomistic calculations for specific systems to assist in constructing and classifying TPN graphs, to quantify the energy landscapes, and to investigate the effects of various crystalline defects. Finally phase field simulations will be carried out to examine possible continuous phase separations and other mechanisms to generate nanoscale structural and chemical non-uniformities in the parent phase and to study their effects on subsequent ferroic phase transitions and ferroic nanodomain formation. The responses of these ferroic nanodomains to temperature and external fields will be documented. Drastically different properties from those of their microdomain counterparts are expected, in particular ultra-low-modulus quasi-linear pseudoelasticity, low hysteresis, high susceptibility such as giant piezoelectricity, giant magnetostriction and giant non-hysteretic strain response, and strong fatigue resistance. The educational outreach of the project is designed to have a significant influence on encouraging high school students who are members of underrepresented groups to enter science and engineering disciplines.