Accurate and Efficient Atomic-Scale Simulation of Structural Evolution in Materials: Metal Thin-Film Growth

材料结构演化的准确高效的原子尺度模拟：金属薄膜生长

• 批准号: 9617122
• 负责人: Kristen Fichthorn
• 金额: $ 19.8万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-04-15 至 2000-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9617122&HistoricalAwards=false
• 关键词: Accurate; Efficient; Atomic; Scale; Simulation

9617122 Fichthorn This theoretical research will advance the current capabilities for long-time, atomic-scale, dynamical simulations of materials by developing a family of new dynamical methods, based on Smart Monte Carlo. These methods are applicable to systems whose evolution is governed by rare-event dynamics. The inherent advantages of these methods are their accuracy, which is comparable to molecular dynamics simulations, and computational efficiency, which allows for simulation of long time scales on the order of minutes to hours. The new and extended capabilities of Smart Monte Carlo could have applications in the design and processing of many different kinds of materials, in catalysis, and in separations, where atomic- scale kinetics dictate macroscopic structure and function. These methods will be used to probe the relationship between kinetics and morphology in metal thin film epitaxy. Specifically, we will study cluster diffusion and its role in submonolayer metal thin film epitaxy for three model systems: Rh/Rh(001), Rh/Rh(111), and Pt/Rh(111). Recent studies indicate that complicated, many-atom mechanisms may mediate cluster diffusion in these systems and lead to unexpectedly high mobilities for large clusters. These findings have ramifications for thin film morphology, as well as for the development of theories for cluster diffusion and island growth, since current theories do not account for multiple-atom diffusion mechnaisms and large cluster mobilities. %%% This research is comprised of both the development of new computational techniques and the application of these techniques to the study of the deposition and movement of metal atoms on metal surfaces. These simulations, and associated theory, will help us understand how material films grow and form particular structures. The results of this work will advance computational methods and provide an important design tool for understanding the growth of materials. ***

9617122 Fichthorn这项理论研究将通过开发一系列基于智能蒙特卡罗的新动力学方法来提高目前长时间，原子尺度，材料动力学模拟的能力。 这些方法适用于系统的演变是由稀有事件动力学。 这些方法的固有优点是它们的准确性，这是可比的分子动力学模拟，和计算效率，这允许模拟长时间尺度上的几分钟到几小时的顺序。 智能蒙特卡罗的新的和扩展的能力可以在许多不同种类的材料的设计和处理中，在催化和分离中，原子尺度动力学决定宏观结构和功能。 这些方法将用于探索金属薄膜外延生长过程中动力学与形貌之间的关系。 具体来说，我们将研究团簇扩散及其在亚单层金属薄膜外延三个模型系统：Rh/Rh（001），Rh/Rh（111），Pt/Rh（111）的作用。 最近的研究表明，复杂的，多原子的机制可能介导的集群扩散在这些系统中，并导致意外的高迁移率的大集群。 这些发现有分歧的薄膜形态，以及集群扩散和岛屿生长的理论的发展，因为目前的理论不占多原子扩散mechanisms和大集群迁移率。 这项研究包括新的计算技术的发展和这些技术在金属表面上的沉积和金属原子运动的研究中的应用。 这些模拟和相关的理论将帮助我们理解材料薄膜是如何生长和形成特定结构的。 这项工作的结果将推进计算方法，并为理解材料的生长提供重要的设计工具。 ***