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.(马萨诸塞大学阿姆赫斯特分校)拟议研究的中心主题是开发一种数学和计算框架，使通过自组装过程形成的材料能够进行合理控制和设计。自组装的自发特性为商业设备的轻松和廉价扩展提供了巨大的希望。然而，研究人员一直回避如何可重复地控制和设计这样的系统，这一困难源于它们固有的随机性和紧急行为。提出的框架基于新的数学和计算工具，首次能够在真实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控制自组装的粗粒度近似。研究任务将把数学家和化学工程师的专业知识汇聚在一个跨学科和多机构的虚拟环境中，利用信息技术实现有效的数据共享、参与小组之间的交流和研究任务的协调。我们的工作有可能为实验者提供一种系统的方法来开发合理的协议，首次能够以经济高效的方式基于计算思维制造通过分级自组装形成的纳米材料。拟议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。在具有重大技术和社会影响的领域出现的新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。督导主任会积极从学生人数偏低的组别招收学生，包括本科生和研究生。

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.