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Collaborative Research: Visualizing statistical force networks in colloidal materials far-from-equilibrium

合作研究：可视化远离平衡状态的胶体材料中的统计力网络

基本信息

批准号：
2104726
负责人：
Lilian Hsiao
金额：
$ 41.81万
依托单位：
North Carolina State University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-08-15 至 2024-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2104726&HistoricalAwards=false
关键词：
Collaborative Research Visualizing statistical force

项目摘要

Non-technical AbstractSuspensions of particles in liquids are found everywhere around us in foods, consumer products, natural settings, biological systems, and construction materials. The physical and mechanical properties of these materials, their shelf life, and their function are heavily influenced by how the particles interact with each other. Better design of materials requires an understanding of how particle interactions give rise to certain types of mechanical behavior. The particles in these systems come in all shapes and sizes, and often possess rough edges as opposed to being completely smooth and spherical. Understanding how to handle and process such types of colloidal materials provides significant economic and technological advantages to our nation. When colloids are forced to flow in highly concentrated slurries, the particles aggregate and collectively resist motion, leading to large increases in pressure and catastrophic failure in equipment. This project uses advanced network science concepts, experiments, and simulations in concert to study such types of jammed suspensions in a series of flow scenarios. The insight gained from this work will benefit a wide range of academic researchers and industrial practitioners that utilize dense particulate systems. Basic concepts related to soft matter physics will be disseminated broadly to K-12 students and the general public through summer camps and citizen science on social media. Moreover, state-of-the-art results generated from this project will be incorporated into undergraduate and graduate curriculum, and in workshops designed to engage minority and underrepresented scientists.Technical AbstractDense particulate materials are ubiquitous in many manufacturing fields, such as pharmaceuticals, consumer and food products, and the energy industry. Understanding the multiscale nature of flowing dense suspensions will advance the bottom-up design of novel and superior materials. This project provides foundational understanding in the physics of dense suspensions, by generating a statistical description of the force networks that are responsible for stress propagation from particle-level to macroscopic scale. The central hypothesis is that the spatiotemporal signatures in load-bearing networks can be tuned using particle friction and dynamics. The PIs will combine experiments and simulations to investigate the nature of network morphology and relaxation in colloidal suspensions undergoing flow hysteresis, creep, and rapid cessation of flow. Experiments involve the use of confocal rheometry, which is a high-resolution and high-speed technique that measures flow stresses while directly imaging the movement of individual colloids. The experimental observations will be combined with computer simulations that incorporate detailed fluid physics between roughened surfaces. These techniques enable the analysis of clusters at the network level, including how they evolve and change in flowing systems. In dense flowing suspensions, giant networks are thought to persist and control the mechanics of the entire system. This project will study particle networks when non-ideal particles are separated by thin layers of fluid, validate granular models that connect mesoscale cooperativity lengths to flow rheology, and utilize colloidal properties to deliberately change the network patterns responsible for unexpected flow properties.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.

非技术摘要液体中的颗粒悬浮物在我们周围的食物、消费品、自然环境、生物系统和建筑材料中随处可见。这些材料的物理和机械性能、它们的保质期和它们的功能很大程度上受到粒子相互作用的影响。更好的材料设计需要了解粒子相互作用如何导致某些类型的力学行为。这些系统中的粒子具有各种形状和大小，并且通常具有粗糙的边缘，而不是完全平滑和球形。了解如何处理和加工这种类型的胶体材料为我们国家提供了显著的经济和技术优势。当胶体被迫在高度浓缩的泥浆中流动时，颗粒会聚集在一起，共同抵抗运动，导致压力大幅增加，设备发生灾难性故障。该项目使用先进的网络科学概念、实验和模拟相结合来研究一系列流动场景中的这种类型的拥堵悬浮。从这项工作中获得的洞察力将使利用密集颗粒系统的广泛的学术研究人员和工业从业者受益。与软物质物理有关的基本概念将通过夏令营和社交媒体上的公民科学向K-12学生和普通公众广泛传播。此外，该项目产生的最新成果将被纳入本科生和研究生课程，以及旨在吸引少数族裔和代表性不足的科学家的研讨会中。技术摘要密度颗粒材料在许多制造领域普遍存在，如制药、消费品和食品以及能源行业。了解流动的致密悬浮液的多尺度特性将推动新材料和优质材料的自下而上设计。该项目通过生成负责从粒子水平到宏观尺度的应力传播的力网络的统计描述，提供了对稠密悬浮物的物理学的基础理解。中心假设是，承载网络中的时空特征可以利用粒子摩擦和动力学进行调整。PI将结合实验和模拟来研究经历流动滞后、蠕变和快速停止流动的胶体悬浮液中网络形态和松弛的本质。实验涉及共聚焦流变仪的使用，这是一种高分辨率和高速的技术，在测量流动应力的同时直接成像单个胶体的运动。实验观察将与计算机模拟相结合，计算机模拟包括粗糙表面之间的详细流体物理。这些技术能够在网络级别分析集群，包括它们在流动系统中如何演变和变化。在密集流动的悬浮物中，巨大的网络被认为持续存在并控制着整个系统的机械结构。该项目将研究非理想颗粒被薄层流体分离时的颗粒网络，验证将中尺度合作长度与流动流变学联系起来的颗粒模型，并利用胶体特性故意改变导致意外流动特性的网络模式。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。