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.

这项教师早期职业发展（职业）计划奖的研究目标是建立对机械和数学的基本理解，该机制和数学决定了多种方法晶体和复合材料的身体行为，以预测和优化现有和新的多体型设备的性能，并通过实验验证实验和设计。通过伽马收敛和均质化分析的方法，理论方法始于热力学，电动力学，框架的冷漠和材料对称性的基本原理，朝着各种物理和几何限制的多效体的自持非线性理论的层次结构。基于有限元方法和多级梯度方法，数值方法提供了计算模型和算法，以预测和优化多效材料的所需属性。通过协作计划，实验方法提供了对多效复合材料的预测属性和最佳设计的验证。 可以通过外部磁性，电场和弹性场来刺激多种材料，并响应多种功能，并广泛用于多种作用和多感应系统。综合的理论，数值和实验策略将促进具有改进功能的多铁结构和复合材料的工程，并刺激发现新型多效材料的发现。这些进步将为智能材料和智能系统的领域提供新的机会。与工业合作伙伴的合作将确保潜在的技术转移。与研究密切相关的教育和外展工作将实现更广泛的社会影响，包括代表性不足的群体的研究机会，高中访问，一本关于现代应用在生物力学和纳米材料中的弹性的教科书，互动式的互动式可视化示范了在多功能材料材料和最佳设计方面的启示，以增强了对始终的研究和学习的研究和学习的研究和研究和学习的经验，并促进了研究和学习的经验。