Development of a thermodynamically consistent rheological constitutive equation for thixotropic suspensions connecting particle properties to thermodynamics and rheology

许多材料在其加工和/或使用期间必须具有固体状和流体状性质。 例子包括建筑材料，如水泥和沥青，生物流体，如血液，消费品，包括牙膏和护手霜，天然存在的泥浆，粘土和沉积物，以及用于3D打印的聚合物和糊剂。 为了实现所需的流动行为，产品配方设计师改变颗粒特性，如尺寸、形状和表面涂层，添加流动改性剂和胶凝剂，并改变加工条件。 然而，没有准确的方法来预测流动行为。这限制了许多产品的开发，并指出我们对这些重要材料的科学理解存在差距。 这项研究将开发一个新的理论框架，通过创新的实验进行验证，以帮助这一奋进。 这项工作既可以提高我们对这些复杂材料的科学认识，又可以为工业界提供改善加工工艺的工程指导。 此外，高中生，本科生和研究生将在这个多学科的研究工作进行培训。从技术上讲，这项研究解决了触变性，这是一个普遍存在的，往往令人烦恼的，含有颗粒的复杂流体，糊状物和软物质的特性，其特征是一个复杂的，时间依赖性的流变学，由于流动微观结构耦合。微观力学方法本质上局限于小尺度的长度和时间，而在更大的规模的重要性，工程应用和处理，只有唯象模型存在。这些通常限于剪切流，并包含内部参数与不明确的物理意义。 主要研究人员计划通过开发一个基本的、严格的、多尺度的理论框架来解决这个问题，并利用这个框架来开发真正的预测性本构方程，这些方程将在定义明确的模型触变系统的高级实验中得到验证。他们将开发一种新的基于张量、多尺度微观结构的框架，该框架在理论上是一致的，并且普遍适用于所有流（即，以客观的方式来表达）。该理论基于最现代的非平衡态热力学（NET）形式主义（GENERIC）;特拉华州大学的研究人员是这种方法的先驱。基于屈服应力悬浮液的颗粒特性并与连续介质模型匹配的新导出的总体平衡模型的粗粒化将固定NET理论中的中尺度参数，并产生预测性本构模型，该模型可以根据精确的分析结果以及瞬态和振荡剪切流和非连续介质中模型浓缩悬浮液的国际公认数据进行严格测试和验证。粘度流量，并直接对微观结构数据获得的RHEO光学&RHEO-SANS，利用研究支持的NIST。拟议的NET多尺度建模同时强调流变学和材料的微观结构，结合与杠杆实验程序的紧密协调，使这项工作有别于以前的努力。 该研究将导致在复杂的触变系统的建模和理解的新能力，可以显着推进合理的配方和许多工业和国家重要性的材料的处理。这个奖项反映了NSF的法定使命，并已被认为是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的支持。

Many materials must have both solid-like and fluid-like properties during their processing and/or use. Examples include construction materials such as cement and asphalt, biological fluids such as blood, consumer products including toothpaste and hand-creams, naturally occurring muds, clays, and sediments, and polymers and pastes used in 3-D printing. To achieve the desired flow behavior, product formulators vary particle properties, such as size, shape, and surface coatings, add flow modifiers and gelling agents, and vary the processing conditions. However, there is no accurate method of predicting the flow behavior. This limits the development of many products and points to a gap in our scientific understanding of these important materials. This research will develop a new theoretical framework, to be validated by innovative experiments, to aid in this endeavor. The work should both improve our scientific understanding of these complex materials and provide engineering guidance for industry on improving processing. In addition, high school students, undergraduates and graduate students will be trained in this multidisciplinary research effort.More technically, this research addresses thixotropy, which is a ubiquitous, and often vexing, property of particle-containing complex fluids, pastes, and soft matter characterized by a complex, time-dependent rheology due to flow-microstructure coupling. Micromechanical approaches are inherently restricted to small scales of length and time, while at the larger scales of importance to engineering applications and processing, only phenomenological models exist. These are often restricted to shear flows, and contain internal parameters with ill-defined physical meaning. The principal investigators plan to remedy this by developing a fundamental and rigorous, multiscale theoretical framework and use this to develop truly predictive constitutive equations, which will be validated against advanced experiments on well-defined, model thixotropic systems. They will develop a new tensorial, multiscale microstructure-based framework that is thermodynamically consistent and generally applicable for all flows (i.e., cast in materially objective fashion). The theory is based on the most modern nonequilibrium thermodynamic (NET) formalism (GENERIC); the investigators at the University of Delaware are among the pioneers of this approach. Coarse graining of a newly derived population balance model based on particle properties for suspensions with yield stress and matching with the continuum model will fix the mesoscale parameters in the NET theory and result in a predictive constitutive model that can be rigorously tested and validated against exact analytical results as well as internationally recognized data on model concentrated suspensions in transient and oscillatory shear flows and non-viscometric flows, and directly against microstructure data obtained using RHEO-optical & RHEO-SANS, leveraging research supported by NIST. The proposed NET multiscale modeling with a simultaneous emphasis on both the rheology and the material's microstructure, combined with tight coordination with the leveraged experimental program sets this work apart from previous efforts. The research will lead to a new capability in the modeling and understanding of complex thixotropic systems that can significantly advance the rational formulation and processing of many materials of industrial and national importance.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.