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.

如今，人们强烈期望将未来的材料首先在计算机上进行大量研究，而在实验室中合成的最佳候选者将在计算中确定。这样，工程师就可以有效地制定更轻，更强或更有效的新材料。从能源到医学再到运输再到制造业的所有技术领域，都需要此类进步。分子建模群落对量化原子相互作用的最新进展正在迅速消除实现这一愿景的关键障碍。然而，仍然存在一个重要的障碍：材料的热性能（除了最低温度以外的最重要的材料）以预测在实际利益的条件下的晶体结构和特性。这些特性太昂贵了，无法一次计算许多材料，以便基于计算的筛选工作。项目团队已经开发了一种算法，该算法可以显着加速这些计算，而不会损失任何准确性，因此在消除这一障碍方面大有帮助。该项目的目的是使使用分子模拟来理解和开发新材料的研究人员可以实现这一突破。为此，该项目将完善并扩展这些方法，然后将计算机代码添加到广泛使用的分子模拟软件包中，以便他们可以使用这些新技术执行计算。该团队还在努力促进意识并确保方法易于使用及其实施。“映射平均”是一个最近发布的整体平均值的计划。该框架使用统计机械理论的近似结果来得出新的集合平均值（映射的平均值），该集合平均代表了理论中的误差。构图良好的平均值可以通过具有明显的精度和效率的分子模拟来计算。在有利的情况下，计算节省是许多数量级。对于晶体系统，谐波近似提供了合适的起点，从而使模拟可以精确地计算对属性的非谐贡献。结果是一种用于以前所未有的变革效率计算结晶特性的技术。该项目的目的是在建立良好的且广泛使用的软件包上实施这些方法，以模拟结晶系统，并为这些系统的用户开发用于新的感兴趣的新应用的映射平均值。该项目的理论基础最近出现在文献中（2015年），因此拟议的工作是完全新颖的。这些技术并不是很容易理解和乏味的实施，因此，较大的社区采用将需要这种有针对性的基础架构开发，以使其更容易受到临时用户的访问。完整的开发团队包括编码，维护和分发这些要素的包装的计算科学家和软件工程师。该小组协助项目调查人员与仿真软件包进行交互，同时确保将新代码写入最高标准。完整的开发团队还共同努力，以确保软件元素得到正确的验证，以确保正确性和可用性。除了实施外，该项目还旨在扩大映射平均方法的范围，以包含以前未应用的属性和物质。该项目使映射的平均方法可用于几个广泛使用的分子模拟软件包：VIZ，LAMMPS，HOOMD，CASSANDRA和VASP，这些方法总共具有成千上万的用户。在许多情况下，在此项目中实现的软件元素对这些软件包的用户完全透明，并且可以通过它们添加并发症来使用，以通过数量级加快其计算。因此，该项目所做的努力将产生一种有利的技术，从而为科学家和工程师提供新的功能，以制定用于实际应用的材料。开发工具和脚本是在此项目中构建的，这将促进其他开发人员将映射平均方法扩展到更具分子仿真软件包，材料属性和分子模型系统。为该项目开发的软件是开源的。该项目中开发的知识是合并的，以形成网络上提供的课程材料，并用作PI教授的研究生分子模拟课程的大部分组成部分的一部分。在整个项目期间，对1位学生以及众多MS和本科生进行了培训。涉及论文，文档，演讲和讲习班的强烈传播努力确保了社区理解和采用这些方法和工具。 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.