Multiscale Modeling, Optimization, and Control of Microstructural Evolution

PI：Talid R. Sinno和Warren Seider机构：宾夕法尼亚大学提案编号：0730971标题：自适应多尺度建模，优化和微观结构演化的控制越来越强大的计算资源和新算法扩展了多尺度建模的应用范围，其中原子尺度现象与宏观加工条件相关联。这个项目的目的是开发一个分层的，多尺度的建模框架，适用于重复执行的环境，如过程优化和反馈控制。这一目标正变得越来越相关，因为在先进材料的加工过程中，相对于原子种类的空间分布中的波动的容限变得更紧。本计画将探讨两类微结构演化：（1）块状结晶半导体材料中的原子聚集，包括硅、锗和硅锗;（2）多层金属合金中的物种再分布/偏析和相分离，例如铜镍合金，这是磁储存媒体的模型系统。几个当代多尺度建模的挑战将得到解决，以构建一个高度自适应，粗粒度的晶格动力学蒙特卡罗模拟框架。第一个目标将是开发新的晶格动力学蒙特卡罗（LKMC）模拟，隐式占复杂的非晶格重排在真实的系统，特别是在高温下常见的半导体和金属加工。这将通过与大规模平衡和非平衡分子动力学模拟产生的数据进行系统比较来实现。由此产生的“MD匹配”LKMC模拟，然后将在最近推出的粗粒化策略，允许系统的订单减少与控制误差内实施。这项工作的一个关键成果将是战略应用这种粗粒度的框架LKMC模拟与多个物种之间的复杂相互作用。粗粒化将在一个完全自适应的框架内实现，其中粗粒化的程度在空间和时间上动态地调整，这取决于系统不断发展的微观结构以及整个控制/优化环境的分辨率需求。研究中的许多现象已经过实验研究，就硅而言，目前正在与工业界合作，提供与热化学加工环境有关的聚集体形态的详细微观数据。在这个项目中考虑的材料系统和微观结构演变现象本身就具有根本的意义，但也是广泛的类的问题。原子团簇的成核和生长以及空间异质环境中的扩散是与先进器件和材料的制造相关的大量过程中的基础现象。该项目将汇集多尺度建模的几个方面，并将它们集成到一个控制环境中，目的是开发一个多尺度优化和控制的原型框架。模型开发将适用于各种各样的工艺和材料。例如，自适应粗粒度LKMC方法是一种非常强大的通用方法，它是多尺度的，而不是高度系统特定的。该项目将汇集两个传统上不同的研究领域的元素，并将它们紧密结合在一起。大规模的分子动力学和基本的动力学蒙特卡罗代码已经到位，使研究生工作在这个项目上专注于新的方面，如自适应粗粒化和集成的优化和控制组件与多尺度模型。该项目的基本思想将用于开发与宾夕法尼亚大学化学和生物分子工程（CBE）高级设计课程相关的教育材料。到目前为止，PI开发的超越传统化学品加工的新设计项目已经非常成功。例如，最近的项目已经涉及使用有限元建模的化学气相沉积工艺的设计，但是还没有尝试包括原子尺度建模。这项工作应该提供了一个基础，创建设计模块的基础上优化微观目标函数，并将代表CBE顶点课程的演变又一个重要的一步。

PI: Talid R. Sinno and Warren SeiderInstitution: University of Pennsylvania Proposal Number: 0730971Title: Adaptive Multiscale Modeling, Optimization, and Control of Microstructural EvolutionIncreasingly powerful computational resources and new algorithms have extended the application horizon of multiscale modeling, in which atomic scale phenomena are linked to macroscopic processing conditions. The aim of this project is to develop a hierarchical, multiscale-modeling framework suitable for use in repeated execution environments, such as process optimization and feedback control. This objective is becoming increasingly relevant as tolerances with respect to fluctuations in the spatial distribution of atomic species become tighter during the processing of advanced materials. Two classes of microstructural evolution will be considered in this project: (1) atomic aggregation in bulk crystalline semiconductor materials, including silicon, germanium, and silicon-germanium, and (2) species redistribution/segregation and phase separation in multilayered metallic alloys, such as copper-nickel, which are model systems for magnetic storage media.Intellectual Merit: The project has both synthetic and integrative elements. Several contemporary multiscale modeling challenges will be addressed in order to construct a highly adaptive, coarse-grained lattice kinetic Monte Carlo simulation framework. The first aim will be to develop novel lattice kinetic Monte Carlo (LKMC) simulations that implicitly account for complex off-lattice rearrangements in real systems, particularly at the elevated temperatures common in semiconductor and metals processing. This will be accomplished by systematic comparison to data generated by large-scale equilibrium and non-equilibrium molecular dynamics simulations. The resulting "MD matched" LKMC simulations will then be implemented within recently introduced coarse-graining strategies that allow for systematic order-reduction with controlled error. A key outcome of this work will be strategies for applying this coarse-graining framework to LKMC simulations with complex interactions between multiple species. The coarse-graining will be implemented within a fully adaptive framework in which the degree of coarse-graining is adjusted dynamically in space and time as dictated by the evolving microstructure of the system as well as the resolution needs of the overall control/optimization environment. Many of the phenomena under consideration have been studied experimentally, and in the case of silicon, an ongoing collaboration with industry provides access to detailed microscopic data related to aggregate morphology as a function of thermochemical processing environment.Broader Impacts: The material systems and microstructural evolution phenomena considered in this project are of fundamental interest in their own right but also are prototypical examples of a broad class of problems. Nucleation and growth of atomic clusters, and diffusion in spatially heterogeneous environments are cornerstone phenomena in a large number of processes related to the fabrication of advanced devices and materials. The project will bring together several aspects of multiscale modeling and integrate them into a control environment with the aim of developing a prototypical framework for multiscale optimization and control. The model developments will be applicable to a wide variety of processes and materials. For example, the adaptive coarse-grained LKMC method is an extremely powerful general approach that is multiscale without being highly system specific. The project will bring together elements from two traditionally different research areas and couple them closely. Large-scale molecular dynamics and basic kinetic Monte Carlo codes are already in place, allowing the graduate student working on this project to focus on novel aspects such as adaptive coarse-graining and integration of the optimization and control components with the multiscale models. The basic ideas of the project will be used to develop educational materials related to the Chemical and Biomolecular Engineering (CBE) senior design course at Penn. The development of new design projects that go beyond traditional chemicals processing into this course by the PI has been highly successful thus far. For example, recent projects have involved the design of chemical vapor deposition processes using finite element modeling, but no attempt has yet been made to include atomic-scale modeling. This work should provide a basis for creating design modules based on the optimization of microscopic objective functions and would represent yet another significant step in the evolution of the CBE capstone course.