CAREER: Multiscale Mechanics of Carbon Nanotube-Polymer Composites

职业：碳纳米管-聚合物复合材料的多尺度力学

基本信息

批准号：
2046332
负责人：
Hessam Yazdani
金额：
$ 56.26万
依托单位：
Howard University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-01 至 2023-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2046332&HistoricalAwards=false
关键词：
CAREER Multiscale Mechanics Carbon Nanotube

项目摘要

This Faculty Early Career Development (CAREER) grant will support research on understanding the fracture mechanisms and predicting the mechanical properties of carbon nanotube-filled polymer composites. These materials have the potential to play a growing role in the prosperity, security, and global competitiveness of the United States and propelling the economic performance of major industrial sectors such as aerospace, manufacturing, biomedical, and civil infrastructure. Polymer composites are tunable materials whereby changes to their constituents, processing conditions, and microstructure one can achieve products with distinct functions. Understanding the processing-structure-property relations and failure mechanisms of these materials, however, is complicated because they feature a wide range of compositions, phenomena, and interactions across several scales of time, length, complexity, and uncertainty. This research aims to unravel these relations and mechanisms and in turn supplant the traditional trial-and-error approach to the design of polymer composites by an efficient, machine learning-assisted, experiment-informed, multiscale computational approach that will accelerate the discovery of novel polymer composites with improved manufacturability, reliability, and performance, ultimately benefiting the economy and society. The educational and outreach components of this project will contribute to enhancing diversity in STEM multidisciplinary education and include developing courses in advanced materials and forming sustainable collaborations between the PI’s research group and industry partners and professional organizations. Among the scientific and technological challenges remaining in the field of carbon nanotube-filled polymer composites, one of the least-understood areas is the deformation and failure of these materials and a poor understanding of load transfer in them at the filler-matrix interface. This project will further elucidate the phenomena and mechanisms that underlie the mechanical response of these materials at the nano- and microscales and quantify their processing-structure-property relationships by developing a probabilistic framework comprising laboratory tests, microscopic characterizations, image processing, multiscale modeling and simulations, and machine learning. The uncertainties involved will be quantified, and a probabilistic multiscale modeling and simulation hierarchy will be developed to study high-fidelity models of polymer composites. Machine learning will be used to perform sensitivity analyses and develop probabilistic predictive models for the properties of polymer composites. The study outcome will offer a new route to design heterogeneous, high-performance, and multifunctional composite materials.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.

这项教师早期职业发展（职业）赠款将支持了解理解断裂机制的研究，并预测碳纳米管填充的聚合物公司的机械性能。这些材料有可能在美国的繁荣，安全和全球竞争力中发挥越来越多的作用，并推动航空航天，制造业，生物医学和民用基础设施等主要工业部门的经济绩效。聚合物复合材料是可调的材料，可以改变其结构，加工条件和微观结构，可以实现具有不同功能的产品。然而，了解这些材料的处理结构 - 培训关系和失败机制是复杂的，因为它们在几个时间尺度，长度，复杂性和不确定性上具有广泛的组成，现象和相互作用。这项研究旨在阐明这些关系和机制，然后通过一种有效的，机器学习，实验性的，多尺度的计算方法来取代传统的试验方法，以设计聚合物公司，从而加速新型聚合物公司的新型聚合物公司，从而改善了生产，可靠性，绩效，绩效，最终受益于经济和社会。该项目的教育和外展成分将有助于增强STEM多学科教育的多样性，包括开发高级材料的课程，并在PI的研究小组与行业合作伙伴和专业组织之间建立可持续的合作。在碳纳米管填充的聚合物公司的领域中，科学和技术挑战仍然存在，最不理解的领域之一是这些材料的变形和失败以及对填充物垫子界面上负载转移的不良理解。该项目将进一步阐明这些材料在纳米和显微镜下的机械响应的现象和机制，并通过开发概率框架，包括实验室测试，显微镜特征，图像处理，多台阶模型以及模拟以及模拟和机器学习，从而量化其处理结构 - 培训关系。涉及的不确定性将进行量化，并将开发概率的多尺度建模和模拟层次结构来研究聚合物公司的高保真模型。机器学习将用于执行灵敏度分析并为聚合物公司的性质开发概率预测模型。该研究结果将为设计异质，高性能和多功能复合材料提供新的途径。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响评估标准，被认为是珍贵的支持。