Collaborative Research CDI-Type II: Hierarchical Stochastic Algorithms for Materials Engineering.

非主导提案ID: CMMI - 0835548 PI: Vlachos， Dionisios G.（特拉华大学）非主导提案ID: CMMI - 0835673 PI: Katsoulakis， Markos a .（马萨诸塞大学阿默斯特分校）拟议研究的中心主题是开发一种数学和计算框架，使材料形成的合理控制和设计通过自组装过程。自组装的自发特性为方便和廉价的商业用途的设备放大提供了巨大的希望。然而，如何可重复地控制和设计这样的系统一直困扰着研究人员，这一困难源于它们固有的随机性和突发性行为。所提出的框架基于新颖的数学和计算工具，这些工具首次能够在实际长度和时间尺度上以足够的精度对随机过程进行建模，并系统地推导用于模拟和自组装控制的粗粒度近似。研究任务将汇集数学家和化学工程师的专业知识，在跨学科和多机构的虚拟环境中使用信息技术进行有效的数据共享，参与小组之间的通信和研究任务的协调。我们的工作有可能为实验人员提供一种系统的方法来开发合理的方案，首次实现基于计算思维的纳米材料的制造，这种纳米材料是通过分层自组装形成的，具有成本效益。提出的框架跨越了高经济利益的多个科学和工程领域，从材料合成到生物系统再到能源生产。在关键技术和社会影响领域出现的新问题要求教育哲学的范式转变。拟议的研究通过应用数学家和化学工程师之间的知识交流提供了这样一个机会。学院将积极招收来自代表性不足群体的本科生和研究生。

Non- Lead Proposal ID: CMMI - 0835548 PI: Vlachos, Dionisios G. (University of Delaware)Non- Lead Proposal ID: CMMI - 0835673 PI: Katsoulakis, Markos A. (University of Massachusetts Amherst)The central theme of the proposed research is development of a mathematical and computational framework that enables rational control and design of materials forming by self-assembly processes. The spontaneous character of self-assembly gives great promise for easy and cheap scale-up of devices for commercial use. However, it has eluded researchers how to reproducibly control and design such systems, a difficulty stemming from their inherent stochasticity and emergent behavior. The proposed framework is based on novel mathematical and computational tools that enable, for the first time, modeling of stochastic processes with sufficient accuracy over realistic length and time scales and systematic derivation of coarse-grained approximations used in simulations and control of self-assembly. The research tasks will bring together expertise of mathematicians and chemical engineers in an interdisciplinary and multi-institutional virtual environment using information technology for efficient data sharing, communication between participating groups and coordination of research tasks.Our work has the potential to provide a systematic approach to the development of rational protocols for experimentalists, enabling for the first time computational thinking-based fabrication of nanomaterials formed via hierarchical self-assembly in a cost-effective manner. The proposed framework crosses among multiple sciences and engineering fields of high economical interest, ranging from materials synthesis to biological systems to energy production. Emerging problems in areas of critical technological and societal impact demand a paradigm shift in education philosophy. The proposed research offers such an opportunity through the exchange of knowledge between applied mathematicians and chemical engineers. The PIs will actively pursue the recruitment of students from under-represented groups, both at the undergraduate and graduate levels.