Collaborative Research: Mechanics of Hybrid Random Fiber Networks

合作研究：混合随机光纤网络的机制

• 批准号: 2022471
• 负责人: Ioannis Chasiotis
• 金额: $ 35.14万
• 依托单位: University of Illinois at Urbana-Champaign
• 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: 2021-06-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2022471&HistoricalAwards=false
• 关键词: Collaborative; Research; Mechanics; Hybrid; Random

This grant will support research and education on the mechanics of random networks of polymeric filaments, which are reinforced with hard particles. Fiber networks are the main structural component of many synthetic and natural materials: polymeric or biological fibers and nanofibers with rigid inclusions are omnipresent in biological tissues, tissue scaffolds, biomedical implants, electrospun air filtration systems, cellulose products, etc. Most of these fibrous systems form composites with embedded non-fibrous entities. While continuum matrix composites have been studied extensively, the mechanics of hybrid networks with a discrete matrix has received no attention to date, despite the plethora of applications. The results of this research will influence the design of a wide range of applications of fibrous networks, such as non-wovens, gels, rubber, tissue scaffolds, cellulose products, etc. as well as our understanding of the mechanical behavior of a wealth of biological systems which are comprised of heterogeneous random networks. On the educational front, a program geared towards high school, undergraduate and graduate students with computational activities and hands on laboratory experiments will include several aspects of this research.This research will (i) establish structure-property relations of hybrid fiber networks, (ii) extend the theory of composites with continuum matrices to composites in which the matrix is a discrete fiber network, (iii) establish new methods to experimentally investigate fibrous materials and their composites. The theory of continuum matrix composites will be extended to hybrid materials in which the matrix is a fiber network reinforced with particles or fibers of different properties from those of the main network (matrix). Thereby, effective ways will be identified to reinforce networks with small volume fractions of fillers, and concomitantly improve dramatically on the composite stiffness and strength. First, experiments and computational modeling will evaluate the perturbation introduced by an isolated filler to the deformation fields of stochastic networks in order to establish an equivalent Eshelby solution for networks. Then, the effect of filler concentration on the small and large strain mechanical response and network strength will be explored to establish effective homogenization methods for hybrid networks. Data from controlled experiments performed with the aforementioned systems will be used to validate the numerical models, which will be then used to broadly explore the design space defined by the network and filler parameters.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.

这笔赠款将支持研究和教育的随机网络的聚合物长丝，这是加强与硬颗粒的力学。纤维网络是许多合成和天然材料的主要结构组分：具有刚性内含物的聚合物或生物纤维和纳米纤维在生物组织、组织支架、生物医学植入物、静电纺丝空气过滤系统、纤维素产品等中无处不在。虽然连续基体复合材料已被广泛研究，混杂网络与离散矩阵的力学尚未得到关注，尽管有大量的应用。这项研究的结果将影响纤维网络的广泛应用，如非织造布，凝胶，橡胶，组织支架，纤维素产品等的设计，以及我们对由异质随机网络组成的大量生物系统的力学行为的理解。在教育方面，一个面向高中生、本科生和研究生的程序，包括计算活动和实验室实验，将包括本研究的几个方面，本研究将（i）建立混杂纤维网络的结构-性能关系，（ii）将连续基体复合材料理论扩展到基体为离散纤维网络的复合材料，（iii）建立新的方法来实验研究纤维材料及其复合材料。连续体基体复合材料的理论将扩展到混杂材料，其中基体是由与主网络（基体）不同性质的颗粒或纤维增强的纤维网络。因此，有效的方法将被确定，以加强网络与小体积分数的填料，并伴随着显着提高复合材料的刚度和强度。首先，实验和计算建模将评估由孤立的填充物引入随机网络的变形场的扰动，以建立网络的等效Eshelby解。然后，将探讨填料浓度对小应变和大应变力学响应以及网络强度的影响，以建立有效的混合网络均匀化方法。上述系统的受控实验数据将用于验证数值模型，然后将用于广泛探索网络和填料参数定义的设计空间。该奖项反映了NSF的法定使命，并被认为值得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。

项目成果

Rate dependent adhesion of nanoscale polymer contacts

• DOI: 10.1016/j.jmps.2021.104597
• 发表时间: 2021-09-06
• 期刊: JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS
• 影响因子: 5.3
• 作者: Das, Debashish;Chasiotis, Ioannis
• 通讯作者: Chasiotis, Ioannis