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SI2-SSE: Infrastructure Enabling Broad Adoption of New Methods That Yield Orders-of-Magnitude Speedup of Molecular Simulation Averaging

SI2-SSE：基础设施支持广泛采用新方法，使分子模拟平均速度提高几个数量级

基本信息

批准号：
1739145
负责人：
David Kofke
金额：
$ 49.97万
依托单位：
SUNY at Buffalo
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-10-01 至 2021-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1739145&HistoricalAwards=false
关键词：
SI2 SSE Infrastructure Enabling Broad

项目摘要

There is, today, a strong expectation that future materials will be studied in huge numbers first on the computer, and the best candidates for synthesis in the laboratory will be identified computationally. In this way engineers can efficiently formulate new materials that are lighter, stronger, or otherwise more functionally effective. Such advances are needed across all fields of technology, from energy to medicine to transportation to manufacturing. Recent advances from the molecular modeling community toward quantifying atomic interactions are rapidly eliminating a key obstacle to realization of this vision. Yet, an important obstacle remains: the thermal properties of materials -- those that are important at all but the lowest temperatures -- are needed to predict crystal structures and properties at conditions of practical interest. These properties are too expensive to compute for many materials at once, as needed for a computation-based screening effort. The project team has developed an algorithm that significantly accelerates these calculations without any loss of accuracy, and therefore goes a long way toward removing this obstacle. The aim of this project is to make this breakthrough available to researchers who are using molecular simulation to understand and develop new materials. To this end, this project will refine and extend these methods, and then add computer code to widely-used molecular simulation packages so that they can perform calculations using these new techniques. The team is additionally making efforts to promote awareness and ensure ease-of-use of the methods and their implementation."Mapped averaging" is a recently published scheme for the reformulation of ensemble averages. The framework uses approximate results from statistical mechanical theory to derive new ensemble averages (mapped averages) that represent exactly the error in the theory. Well-conceived mapped averages can be computed by molecular simulation with remarkable precision and efficiency; in favorable cases the computational savings are many orders of magnitude. For crystalline systems, a harmonic approximation provides a suitable starting point, allowing simulation to compute precisely the anharmonic contribution to the properties. The result is a technique for computing crystalline properties with unprecedented, transformative efficiency. The aim of this project is to implement these methods on well-established and widely used software packages for simulation of crystalline systems, and to develop mapped averages for new applications of interest to the users of these systems. The theoretical basis for this project appeared in the literature very recently (2015), so the proposed work is completely novel. The techniques are not trivial to understand and are tedious implement, hence adoption by the larger community will require this targeted infrastructure development to make them more accessible to casual users. The full development team includes the computational scientists and software engineers who coded, maintain and distribute the packages where these elements will be introduced. This group assists the project investigators to interface with the simulation packages while ensuring that the new codes are written to the highest standards. The full development team works together also to ensure that the software elements are thoroughly validated for correctness and usability. In addition to the implementation, the project also aims to expand the scope of the mapped-averaging method to encompass properties and substances to which it was not previously applied. This project enables mapped averaging methods to be employed on several widely-used molecular simulation packages: viz, LAMMPS, HOOMD, Cassandra, and VASP, which altogether have a base encompassing thousands of users. Software elements implemented in this project are in many cases completely transparent to the users of these packages, and can be employed by them with no added complication, to speed up their calculations by orders of magnitude. Thus the efforts made in this project will produce an enabling technology, giving scientists and engineers new capabilities to formulate materials for practical applications. Development tools and scripts are constructed in this project, which will facilitate the extension of mapped-averaging methods by other developers to even more molecular simulation packages, material properties, and molecular model systems. Software developed for this project is distributed open-source. Knowledge developed in this project is consolidated to form course materials made available on the web, and used as part of a large component of a graduate molecular simulation course taught by the PI. Training of 1 PhD student and numerous MS and undergraduates occurs across the project period. A strong dissemination effort involving papers, documentation, presentations, and workshops ensure that these methods and tools are understood and adopted by the community. Finally, instructional, graphically-oriented molecular simulation modules are developed and made available on the web to convey concepts related to harmonic and anharmonic components of crystalline behavior, with unique capabilities made possible by the mapped averaging framework.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

今天，人们强烈期望未来的材料将首先在计算机上进行大量研究，并通过计算确定实验室合成的最佳候选者。通过这种方式，工程师可以有效地配制更轻，更强或功能更有效的新材料。从能源到医药、运输到制造业，所有技术领域都需要这种进步。分子建模界在量化原子相互作用方面的最新进展正在迅速消除实现这一愿景的关键障碍。然而，一个重要的障碍仍然存在：材料的热性能-除了最低温度之外的所有重要性能-都需要预测实际感兴趣条件下的晶体结构和性能。这些属性太昂贵了，无法一次计算许多材料，因为需要基于计算的筛选工作。项目团队已经开发出一种算法，可以在不损失准确性的情况下显著加快这些计算，因此在消除这一障碍方面还有很长的路要走。该项目的目的是使这一突破提供给那些使用分子模拟来理解和开发新材料的研究人员。为此，该项目将改进和扩展这些方法，然后将计算机代码添加到广泛使用的分子模拟软件包中，以便它们可以使用这些新技术进行计算。该小组还在努力提高认识，确保这些方法易于使用和实施。“映射平均”是最近出版的一个重新表述系综平均的方案。该框架使用统计力学理论的近似结果来推导新的系综平均值（映射平均值），这些平均值恰好代表理论中的误差。精心构思的映射平均值可以通过分子模拟计算出显着的精度和效率，在有利的情况下，计算节省了许多数量级。对于晶体系统，谐波近似提供了一个合适的起点，允许模拟精确计算非谐波对性质的贡献。其结果是一种计算晶体性质的技术，具有前所未有的变革性效率。该项目的目的是在成熟和广泛使用的软件包上实现这些方法，用于模拟晶体系统，并为这些系统的用户感兴趣的新应用开发映射平均值。该项目的理论基础最近（2015年）出现在文献中，因此所提出的工作是完全新颖的。这些技术并不容易理解，而且实现起来也很繁琐，因此更大社区的采用将需要这种有针对性的基础设施开发，以使它们更容易被临时用户访问。完整的开发团队包括计算科学家和软件工程师，他们编码，维护和分发将引入这些元素的软件包。该小组协助项目调查人员与模拟软件包进行接口，同时确保新代码的编写符合最高标准。整个开发团队也会共同努力，以确保软件元素的正确性和可用性得到彻底验证。除了实施之外，该项目还旨在扩大映射平均法的范围，以涵盖以前未适用的特性和物质。该项目使映射平均方法可以在几个广泛使用的分子模拟软件包上使用：即LAMMPS，HOOMD，Cassandra和VASP，这些软件包共有数千个用户。在这个项目中实现的软件元素在许多情况下对这些软件包的用户是完全透明的，并且可以由他们使用而不增加复杂性，以加速他们的计算数量级。因此，在该项目中所做的努力将产生一种使能技术，使科学家和工程师能够为实际应用配制材料。开发工具和脚本构建在这个项目中，这将有助于其他开发人员的映射平均方法的扩展，甚至更多的分子模拟包，材料性能和分子模型系统。为该项目开发的软件是分布式开源的。在这个项目中开发的知识是巩固，形成课程材料提供在网络上，并作为一个大的组成部分，研究生分子模拟课程教授的PI。1名博士生和许多MS和本科生的培训发生在整个项目期间。一个强大的传播工作，包括论文，文件，演示文稿和研讨会，确保这些方法和工具被社区理解和采用。最后，开发了教学性的、面向图形的分子模拟模块，并在网络上提供，以传达与晶体行为的谐波和非谐波成分相关的概念，其独特的能力通过映射平均框架成为可能。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。