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

非铅提案ID：CMMI - 0835548 PI：Vlachos，Dionisios G.（特拉华州大学）非牵头提案ID：CMMI - 0835673 PI：Katsoulakis，Markos A.（马萨诸塞州阿默斯特大学）拟议研究的中心主题是发展一个数学和计算框架，使合理的控制和设计的材料形成的自组装过程。 自组装的自发特性为商业用途的设备的简单和廉价的规模化提供了巨大的希望。 然而，它一直困扰着研究人员如何可重复地控制和设计这样的系统，一个困难源于他们固有的随机性和紧急行为。所提出的框架是基于新的数学和计算工具，使，第一次，建模的随机过程具有足够的准确性，在现实的长度和时间尺度和系统推导的粗粒度近似用于模拟和控制自组装。 研究任务将汇集数学家和化学工程师的专业知识，在一个跨学科和多机构的虚拟环境中，利用信息技术进行有效的数据共享，参与小组之间的沟通和研究任务的协调。我们的工作有可能为实验人员提供一个系统的方法来制定合理的协议，第一次以具有成本效益的方式通过分级自组装形成的纳米材料的基于计算思维的制造成为可能。所提出的框架跨越了具有高度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问题要求教育理念的范式转变。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。PI将积极寻求从代表性不足的群体中招募学生，无论是在本科生还是研究生阶段。

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.