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Mathematics of Self-Assembled Materials

自组装材料数学

基本信息

批准号：
1908968
负责人：
Karl Glasner
金额：
$ 23.4万
依托单位：
University of Arizona
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-08-01 至 2024-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1908968&HistoricalAwards=false
关键词：
Mathematics Self Assembled Materials

项目摘要

The ability of systems to assemble and organize without direct control or intervention is fundamental to biological and non-biological systems. Materials such as complex polymers may self-assemble into a wide variety of forms, and have many nanotechnology and biomedical applications. This project studies models of material self-assembly to develop theoretical insight and predictive capabilities. Formulas are developed that connect microscopic molecular properties to mechanical and morphological behaviors at larger scales. Computations are employed for predicting novel behaviors and custom-tailoring inputs for engineered nanostructures. The award provides research and educational opportunities for both graduate and undergraduate students.This project broadly investigates polymer, amphiphilic, and particle-based systems, and processes fundamental to the creation of nanoscale materials. Models describing formation of nanoparticles and amphiphilic structures in heterogeneous polymer systems are examined using a mixture of analytical and computational approaches that quantify equilibria, morphology, and dynamics. In conjunction with these models, algorithms for inverse problems will be developed for purposes of parameter identification and engineering design. Self-assembled systems involving a large number of interacting particles are studied within the same framework, leading to predictions of pattern formation and collective behavior. Byproducts of the research include the development of numerical and inverse problem algorithms.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

系统在没有直接控制或干预的情况下组装和组织的能力是生物和非生物系统的基础。复杂聚合物等材料可以自组装成多种形式，并具有许多纳米技术和生物医学应用。该项目研究材料自组装模型，以发展理论洞察力和预测能力。开发的公式将微观分子特性与更大规模的机械和形态行为联系起来。计算用于预测工程纳米结构的新颖行为和定制输入。该奖项为研究生和本科生提供研究和教育机会。该项目广泛研究聚合物、两亲性和基于粒子的系统，以及创建纳米级材料的基础工艺。使用量化平衡、形态和动力学的分析和计算方法的混合来检查描述异质聚合物系统中纳米颗粒和两亲结构的形成的模型。结合这些模型，将开发反问题算法，用于参数识别和工程设计。在同一框架内研究涉及大量相互作用粒子的自组装系统，从而预测模式形成和集体行为。该研究的副产品包括数值和反问题算法的开发。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。