Data CI Pilot: CI-Based Collaborative Development of Data-Driven Interatomic Potentials for Predictive Molecular Simulations

数据 CI 试点：基于 CI 的数据驱动原子间势的协作开发，用于预测分子模拟

基本信息

批准号：
2039575
负责人：
Ellad Tadmor
金额：
$ 112.8万
依托单位：
University of Minnesota-Twin Cities
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-10-01 至 2024-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2039575&HistoricalAwards=false
关键词：
Data CI Pilot Based Collaborative

项目摘要

The project addresses a pressing need of the molecular simulation community by providing materials researchers with a powerful new ability to efficiently synthesize all available data and knowledge related to their particular problem of study. It convenes a consortium of materials researchers around the common goal of increasing interoperability of existing and emerging materials cyberinfrastructures supported by NSF and others. The PIs will develop a new computational framework that enables researchers to rapidly develop and deploy data-driven interatomic potentials for complex material systems, by connecting existing cyberinfrastructure resources of first-principles calculations and experimental data. This will provide qualitative insights into material behavior, as well as predictive capability necessary to design new materials and nanostructures.This project aims to accelerate the adoption of data-driven interatomic potential (DDIP) technology by removing existing barriers faced by materials researchers. Few groups in academia, government and industry have the capacity to develop DDIPs as this requires simultaneous expertise in the physics of the material being modeled, in “first principles” (FP) calculations, and in machine learning techniques, as well as access to extensive computational resources needed to construct the extremely large and diverse training sets required to fit high-quality DDIPs. To address this, a computational infrastructure called “ColabFit” is being developed that will enable researchers to collaborate on DDIP development by pooling their knowledge and data. Researchers will be able to train state-of-the-art DDIPs using a supported fitting code of choice, seamlessly access training data from existing cyberinfrastructure (CI) resources of FP data, and exchange DDIPs in a standard format through the Open Knowledgebase of Interatomic Models (OpenKIM) project so that they can build on each other’s work. This effort fills a pressing need in the materials simulation community, as evidenced by the large consortium of leading DDIP developers, CI projects, and materials standards organization that has been assembled to support it. To keep development of the ColabFit framework focused on real-world materials research needs, it will be organized around a target application of DDIP development for phase transformations in 2D transition metal dichalcogenides.This project is jointly supported by the Office of Advanced Cyberinfrastructure in the Computer and Information Sciences Directorate, and the Division of Materials Research in the Mathematical and Physical Sciences Directorate.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.

该项目通过为材料研究人员提供有效综合与其特定研究问题有关的所有可用数据和知识的新能力来解决分子模拟社区的紧迫需求。它召集了一个材料研究人员的联盟，围绕着增加NSF和其他人支持的现有和新兴材料网络基础设施的互操作性的共同目标。 PI将开发一个新的计算框架，使研究人员能够通过连接第一原理计算的现有网络基础设施资源和实验数据来快速开发和部署复杂材料系统的数据驱动的原子间潜力。这将为设计新材料和纳米结构所需的质量行为以及预测能力提供定性的见解。该项目旨在通过消除材料研究人员面临的现有障碍来加速采用数据驱动的原子体潜能（DDIP）技术。在学术界，政府和行业中，很少有群体能够开发DDIP，因为这需要在“第一原理”（FP）计算以及机器学习技术中进行建模的物理学的简单专业知识，并获得了建造非常大型和多样化的训练集所需的广泛计算资源，以构建极为大型的培训集，以实现高素质高素质DDIP。为了解决这个问题，正在开发一种称为“ ColabFit”的计算基础架构，该基础架构将使研究人员能够通过汇总知识和数据来协作DDIP开发。研究人员将能够使用支持的合适守则，从现有的Cyberinfrastructure（CI）资源中无缝访问FP数据的资源来训练最先进的DDIP，并通过原子质模型（OpenKIM）项目以标准的知识基础以标准的格式交换DDIP，以便它们可以在彼此的工作上构建。这项工作满足了材料模拟社区的紧迫需求，这是由领先的DDIP开发人员，CI项目和材料标准组织组成的大型财团所证明的，该组织已组装以支持它。为了保持关注现实世界材料研究需求的ColabFit框架的开发，它将围绕DDIP开发的目标应用于2D过渡金属二核代元素中的相位转换。该项目由高级Cyberinfrasture在计算机和信息科学领域的高级网络基础设施办公室共同支持，并在计算机和信息科学的材料范围内的材料范围内的材料统计范围，并构成了数学和自动统计局局长和数学阶段的秘书，并构成了数学和秘书级别的构图。使用基金会的智力优点和更广泛的影响标准，被认为是珍贵的支持。