CAREER: Multiferroic Materials - Predictive Modeling, Multiscale Analysis, and Optimal Design

职业：多铁性材料 - 预测建模、多尺度分析和优化设计

• 批准号: 1351561
• 负责人: Liping Liu
• 金额: $ 41.17万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1351561&HistoricalAwards=false
• 关键词: CAREER; Multiferroic; Materials; Predictive; Modeling

The research objective of this Faculty Early Career Development (CAREER) Program award is to establish a fundamental understanding of the mechanics and mathematics that dictates the physical behaviors of multiferroic crystals and composites, to predict and optimize the performance of existing and new multiferroic devices, and to validate the theoretical predictions and designs by experiments. By the method of Gamma convergence and homogenization analysis, the theoretical approach starts from the fundamental principles of thermodynamics, electrodynamics, frame indifference and material symmetries toward a hierarchy of self-consistent nonlinear theories for multiferroic bodies in a variety of physical and geometric limits. Based on the finite element method and multi-level-set gradient method, the numerical approach furnishes computational models and algorithms for predicting and optimizing desired properties of multiferroic materials. Through a collaborative program, the experimental approach provides validation of the predicted properties and optimal designs of multiferroic composites. Multiferroic materials can be stimulated by and respond to external magnetic, electric and elastic fields, serve multiple functions, and are broadly used in multi-actuating and multi-sensing systems. The integrated theoretical, numerical and experimental strategy will facilitate the engineering of multiferroic structures and composites with improved functionalities and stimulate the discovery of novel multiferroic materials. These progresses will offer new opportunities in areas of smart materials and intelligent systems. Collaborations with industrial partners will ensure the potential technology transfer. Broader social impact will be achieved by educational and outreach efforts that are closely tied to the research, including research opportunities for under-represented groups, high-school visits, a textbook on elasticity with modern applications in biomechanics and nanomaterials, an interactive visualization demonstrations project on multifunctional materials and optimal designs to enhance students' interest and learning experience, and dissemination of research findings in conferences and public seminars.

本学院早期职业发展计划的研究目标是建立对多铁性晶体和复合材料物理行为的力学和数学的基本理解，预测和优化现有和新的多铁性器件的性能，并通过实验验证理论预测和设计。通过伽玛收敛和均匀化分析的方法，理论方法从热力学、电动力学、框架无关性和材料对称性的基本原理出发，向各种物理和几何极限下的多铁体的自洽非线性理论层次发展。在有限元法和多水平集梯度法的基础上，提出了预测和优化多铁性材料期望性能的计算模型和算法。通过协作程序，实验方法为预测的多铁复合材料性能和优化设计提供了验证。多铁性材料可以受到外部磁场、电场和弹性场的刺激并作出响应，具有多种功能，广泛应用于多致动和多传感系统中。综合理论，数值和实验策略将促进多铁性结构和复合材料的工程改进功能和刺激发现新的多铁性材料。这些进展将为智能材料和智能系统领域提供新的机会。与工业伙伴的合作将确保潜在的技术转让。更广泛的社会影响将通过与研究密切相关的教育和推广工作来实现，包括为代表性不足的群体提供研究机会，高中访问，一本关于弹性与生物力学和纳米材料现代应用的教科书，一个关于多功能材料的交互式可视化演示项目和优化设计，以提高学生的兴趣和学习经验。以及在会议和公开研讨会上传播研究成果。