Simulating Nonequilibrium Processes over Extended Time- and Length-scales using Parallel Accelerated Dynamics

该奖项支持对凝聚相系统理解的一个长期障碍的计算和理论研究和教育：许多重要过程发生在传统方法不易获得的时间尺度上。为了解决这一差距，各种加速动力学技术，包括超动力学，并行副本动力学，温度加速动力学已被提出。特别是，温度加速动力学已经相当成功地扩展了模拟的时间尺度，因为它允许在长达数秒甚至数小时的时间尺度上逼真地模拟低温过程。然而，由于串行温度加速动力学所需的计算工作与原子数N的立方成比例，这种技术只能应用于非常小的系统。为了解决这个问题，PI最近开发了一种用于并行温度加速动力学模拟或“paradigm”的方法，该方法基于空间分解与PI的同步子晶格算法相结合，该算法按log（N）缩放。利用这种方法，PI研究了Cu/Cu（100）的低温生长，以解释最近观察到的空位形成和压缩应变，PI的目标是利用paramount对扩展时间和长度尺度上的各种非平衡过程进行并行的温度加速动力学模拟。此外，PI计划开发新的方法，使温度加速动力学方法能够研究更高温度下的过程以及研究3D系统和具有远程相互作用的系统。这些措施包括开发一种方法，以本地适应高温参数，控制在每个处理器中的加速动态模拟的“升压”，以优化给定配置的效率，以及处理“低势垒”问题。为了扩展可以通过模拟处理的事件的可能大小，并进一步提高paradigm模拟的效率，PI还旨在开发一种混合的paradigm方法，其中空间分解与中等规模的并行分子动力学模拟和局部鞍点搜索相结合。使用这些方法，PI将进行并行加速动力学模拟，以了解无法使用基于晶格的方法轻松研究的重要非平衡过程，包括：（1）低温半导体生长中的晶体到非晶转变（2）SiO2衬底上非晶Si生长的早期阶段（3）亚单层和多层Fe/Cu（100）、Cu/Ni（100）和Co/Cu（111）生长中的有序、混合和缺陷形成（4）MgO中的辐射损伤和缺陷迁移率这项工作将为广泛的国家、国际、和社会影响。从这个项目中开发的一些方法和结果也将被纳入由PI在托莱多大学教授的计算物理学联合本科生-研究生课程中，同时沿着薄膜和表面物理学研究生课程，学生将学习新的理论进展和最先进的实施和经验评估技术。该奖项支持计算研究和教育，以开发和应用算法和软件来模拟时间尺度上的过程，这些过程对基础科学很重要，但超出了传统模拟方法的范围。例如，分子动力学通常限于纳秒，因为运动方程的积分所需的时间步长很小。然而，重要的罕见事件通常发生在微秒、秒甚至小时的时间尺度上。例子包括晶体或薄膜生长过程中表面形态的演变，固体中点缺陷的扩散，以及塑性应变过程中晶界的迁移。PI的目标是在之前NSF资助下进行的研究的基础上开发新的模拟工具，这些工具可以访问更长的时间尺度，更高的温度和更大的系统。 随着PI的现有和增强的工具，他将解决具体的材料问题，包括半导体材料如何生长和新层的形态，生长的材料层如何与它们生长的材料混合，以及表面附近原子排列的缺陷如何移动及其对生长过程的影响。PI还将新方法应用于材料生长和辐照后材料的动力学。这些研究将与具体的实验密切相关，并将增强我们对材料生长的理解。这项工作将为具有广泛的国家、国际和社会影响的教育和外联活动提供机会。从这个项目中开发的一些方法和结果也将被纳入由PI在托莱多大学教授的计算物理学联合本科生-研究生课程中，同时沿着薄膜和表面物理学研究生课程，学生将学习新的理论进展和最先进的实施和经验评估技术。开发的新算法有助于更广泛的材料研究社区的网络基础设施。

TECHNICAL SUMMARYThis award supports computational and theoretical research and education on a long-standing obstacle to the understanding of condensed-phase systems: many important processes occur on a time-scale that is not easily accessible with conventional methods. In order to address this gap, a variety of accelerated dynamics techniques including hyperdynamics, parallel replica dynamics, and temperature-accelerated dynamics have been proposed. In particular, temperature-accelerated dynamics has been quite successful in extending the time-scales for simulations since it allows realistic simulations of low temperature processes over timescales as long as seconds and even hours. However, due to the fact that the computational work required for serial temperature-accelerated dynamics scales as the number of atoms, N, cubed, this technique can only be applied to extremely small systems. In order to address this problem, the PI has recently developed a method for parallel temperature-accelerated dynamics simulations or "parTAD," which is based on spatial decomposition combined with the PI's synchronous sublattice algorithm, which scales as log(N). Using this method, the PI has studied the low-temperature growth of Cu/Cu (100) over extended length-scales in order to explain recent observations of vacancy formation and compressive strain.The PI aims to use parTAD to carry out parallel temperature-accelerated dynamics simulations of a variety of non-equilibrium processes over extended time- and length-scales. In addition, the PI plans to develop mew methods which will enable the temperature-accelerated dynamics method to study processes at higher temperatures as well as to study 3D systems and systems with long-range interactions. These include the development of a method to locally adapt the high temperature parameter which controls the "boost" in the accelerated-dynamics simulations in each processor to optimize the efficiency for a given configuration, as well as to deal with the "low-barrier" problem. To extend the possible size of events that can be handled by simulations and also further enhance the efficiency of parTAD simulations, the PI also aims to develop a hybrid approach to parTAD in which spatial decomposition is coupled with medium scale parallel molecular dynamics simulations and localized saddle-point searches. Using these methods the PI will carry out parallel accelerated dynamics simulations to understand important non-equilibrium processes which cannot be easily studied with lattice-based methods, including:(1) Crystalline-to-amorphous transition in low-temperature semiconductor growth(2) Early stages of growth of amorphous Si on SiO2 substrates(3) Ordering, intermixing and defect formation in submonolayer and multilayer Fe/Cu(100), Cu/Ni(100), and Co/Cu(111) growth(4) Radiation damage and defect mobility in MgOThe work will provide opportunities for educational and outreach activities with broad national, international, and societal impact. Some of the methods and results developed from this project will also be incorporated in a joint undergraduate-graduate course on Computational Physics taught by the PI at the University of Toledo along with a graduate course on Thin-Films and Surface Physics in which students will learn about new theoretical advances and state-of-the-art implementation and empirical evaluation techniques. New algorithms that are developed contribute to the cyberinfrastructure of the broader materials research community.NON-TECHNICAL SUMMARYThis award supports computational research and education to develop and apply algorithms and software to simulate processes on time scales that are important to the underlying science but out of the range of conventional simulation methods. For example, molecular dynamics is generally limited to nanoseconds because of the small time-step required for the integration of the equations of motion. However, important infrequent events often take place on a time scale of microseconds, seconds, or even hours. Examples include the evolution of the surface morphology during crystal or film growth, the diffusion of point defects in solids, and the migration of grain boundaries during plastic strain. The PI aims to build on research performed under previous NSF funding to develop new simulation tools that can access longer time scales, higher temperatures, and larger systems. With the PI's existing and enhanced tools he will tackle specific materials problems involving how semiconductor materials grow and the morphology of new layers, how growing materials layers can intermix with the material upon which they are grown, and how imperfections in the arrangement of atoms near surfaces move and their affect on the growth process. The PI will also apply the new methods to materials growth and the dynamics of materials after irradiation. These studies will be carried out in close connection with specific experiments and will enhance our understanding of materials growth. The work will provide opportunities for educational and outreach activities with broad national, international, and societal impact. Some of the methods and results developed from this project will also be incorporated in a joint undergraduate-graduate course on Computational Physics taught by the PI at the University of Toledo along with a graduate course on Thin-Films and Surface Physics in which students will learn about new theoretical advances and state-of-the-art implementation and empirical evaluation techniques. New algorithms that are developed contribute to the cyberinfrastructure of the broader materials research community.