US-South Africa DDEP: Efficient Processing of Polydisperse Particulate Mixtures

智力优势：微粒或颗粒状材料在我们的日常生活中随处可见，从我们吃的食物到我们行驶的道路，再到我们服用的药物。很难找到一种商业产品，在混合并转化为最终形式之前，它在某个时候不是不同的、独特的颗粒的集合。然而，尽管颗粒材料普遍存在，但与其流体对应物相比，其处理单元的操作水平很低。因此，颗粒处理厂效率低下，频繁停机和浪费过多，所有这些都导致产品成本上升。通常，经验法则被用来限制这些问题，但这些并不能可靠地预测和防止处理问题的发生。更理想的方法是能够从基本原理、材料特性和小规模实验室测试中定量预测流动行为和分离率，然后相应地设计工艺以限制对性能和产品均匀性的不利影响。一个多学科的研究团队是至关重要的，首先表征颗粒材料的基本性质，然后将这些知识扩展到工业规模的有效操作。罗格斯大学的Benjamin Glasser教授和Matthew Metzger先生与南非威特沃特斯兰德大学（WITS）的Diane Hildebrandt教授的研究小组的合作将独特地将颗粒材料的基础知识与设计大规模高效颗粒操作的能力联系起来。这些问题的核心是缺乏对颗粒在受到驱动力时如何表现的基本理解，这大大阻碍了复制和扩大颗粒过程的尝试。拟议的博士论文增强项目将侧重于发展为什么粒状材料往往分离，或去混合的基本理解。在常见的颗粒系统中，不同粗糙度的多分散颗粒的流动调查将有助于建立各种颗粒混合物的分离潜力的智能决策的基础。随后的分析将确定操作制度，以尽量减少工业操作过程中的颗粒分离。更广泛的影响：这项合作将建立一个沟通渠道，促进两个领先的研究小组在各自领域的持续和未来交流。罗格斯大学的Glasser教授小组因其基础性工作而受到国际认可，这些工作揭示了颗粒材料分离的趋势与由尺寸，密度和表面性质差异引起的不稳定性之间的联系。希尔德布兰特教授在WITS大学的一个小组提供了从系统的角度将基本知识纳入有效流程设计的补充专业知识。总的来说，这项合作将连接国际知名的科学家和专业知识，而不是在一个单一的大学。拟议的研究将开发一个框架，以确定颗粒单元操作的最佳操作条件，以减少颗粒处理操作过程中经常遇到的产品故障和效率低下的发生。

Intellectual Merit: Particulate, or granular, materials are encountered throughout our daily lives, ranging from the food we eat, to the roads we drive on, to the medicines we take. It is challenging to find a commercial product that at some point was not a collection of differing, distinct particles before it was mixed and transformed into its final form. Yet, despite the prevalence of particulate materials, their processing units operate at meager levels compared to their fluid counterparts. As a result, particulate processing plants suffer from poor efficiency, frequent shutdowns and excess waste, all contributing to higher product cost. Often, rules-of-thumb have been used to limit these problems, but these have not reliably predicted and prevented processing problems from occurring. A more desirable approach is the ability to quantitatively predict flow behavior and segregation rates from fundamental principles, material properties and small-scale laboratory tests, and then to engineer processes accordingly to limit detrimental effects on performance and product uniformity. A multidisciplinary research team is critical to first characterize the fundamental nature of granular materials and then extend that knowledge to efficient operation at industrial scale. Collaboration among Professor Benjamin Glasser and Mr. Matthew Metzger at Rutgers University with the research group of Professor Diane Hildebrandt at the University of the Witwatersrand (WITS) in South Africa will uniquely connect the basic knowledge of granular materials with ability to design efficient granular operations at scale. At the core of these issues is the lack of a fundamental understanding of how particles behave when subject to a driving force, which significantly hampers attempts to reproduce and scale-up particulate processes. The proposed Doctoral Dissertation Enhancement Project will focus on developing a fundamental understanding of why granular materials tend to segregate, or de-mix. Investigations of the flow of polydisperse particles of varying degrees of roughness in commonly encountered granular systems will assist in building the foundation for intelligent decision making about the segregation potential of a variety of particulate mixtures. Subsequent analysis will determine operation regimes to minimize particulate segregation during industrial operation. Broader Impact: The collaboration will nurture a conduit of communication that will facilitate on-going and future exchanges between the two leading research groups in their respective fields. Prof. Glasser's group at Rutgers University is internationally recognized for foundational works exposing links between the tendency of granular materials to segregate and instabilities caused by differences in size, density and surface properties. Prof. Hildebrandt?s group at WITS University offers complementary expertise in incorporating elementary knowledge into the design of efficient processes from a systems perspective. Collectively, the collaboration will connect internationally-renowned scientists and expertise not found at a single university. The proposed studies will develop a framework to determine optimal operation conditions for granular unit operations to decrease the occurrence of product failures and inefficiencies frequently encountered during particulate processing operations.This award has been funded by NSF's Office of International Science and Engineering.