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Collaborative Research: CDS&E: ReaxFF2: Efficient and Scalable Methods for Long-time Reactive Molecular Dynamics Simulations

Collaborative Research: CDS&E: ReaxFF2: Efficient and Scalable Methods for Long-time Reactive Molecular Dynamics Simulations
合作研究:CDS
批准号:
1807740
负责人:
Adri van Duin
金额:
$20.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-09-01 至 2022-08-31

项目摘要

项目成果

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中文摘要
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英文摘要
This project aims to enable long-time simulations of reactive molecular systems through efficientand scalable techniques. Long-time reactive simulations are critical for several scientific problemssuch as catalysis, battery interfaces, biological simulations involving water, and emergingareas like surface oxidation and chemical vapor deposition (CVD) growth. However, progress onthese fronts is limited because long-time simulations of large-scale systems are very difficult, ifnot impossible, to perform using existing methods. The Reactive Force Field (ReaxFF) method is in principle ideally suited for this purpose. However, the short time steps required in current ReaxFF simulations and the computationally expensive force field formulation limit ReaxFF's temporal capabilities to narrow simulation time ranges. This project aims to overcome such limitations by creating ReaxFF2,which will extend time scales by one to two orders of magnitude - thus making large-scale, long-time RMD simulations accessible to a wide community. Codes developed will be made publicly available and results from this project will be highlighted on a dedicated website, and they will also be incorporated into workshops by the PIs.In creating ReaxFF2, the PIs will enhance the Reax force field formulation significantly, and develop innovative algorithms and software implementations for scalable simulations. More specifically, alternative ReaxFF interactions will be formulated to eliminate sharp derivatives in energy terms and enhance ReaxFF time step lengths by at least a factor of four. To accelerate the dynamic charge distribution models needed in RMD, scalable parallel preconditioning techniques for the iterative solvers will be developed. A task parallel approach to compute interactions, hierarchical problem decomposition, vectorization of the key kernels, and use of mixed precision arithmetics constitutethe main techniques that will be utilized to fully leverage the performance capabilities of largecomputer clusters. Finally, capabilities of accelerated RMD concepts in the proposed ReaxFF2 formulation will be evaluated and inlined trajectory analysis tools for RMD will be developed to facilitate the study of long-time RMD simulations. This project will significantly enhance the PIs' software development, community building, and sustenance efforts for the RMD community. Codes, functional forms, and parameter sets developed will be made publicly available, enabling fast and accurate modeling of diverse reactive systems beyond the scope of this project. For community outreach, results from this project will be highlighted on a dedicated website, and they will also be incorporated into workshops by the PIs.This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Division of Materials Research and the Division of Chemistry within the NSF Directorate for Mathematical and Physical Sciences.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.
期刊论文(7)
专著(0)
科研奖励(0)
会议论文
Multiply Accelerated ReaxFF Molecular Dynamics: Coupling Parallel Replica Dynamics with Collective Variable Hyper Dynamics
乘法加速 ReaxFF 分子动力学:将并行复制动力学与集体变量超动力学耦合
DOI: 10.1080/08927022.2019.1646911
发表时间: 2019
期刊: Molecular simulation
影响因子: 2.1
作者: [Ganeshan, Karthik Hossain]
通讯作者: Ganeshan, Karthik Hossain
DOI: 10.1021/acs.jctc.9b00769
发表时间: 2019-12-01
期刊: JOURNAL OF CHEMICAL THEORY AND COMPUTATION
影响因子: 5.5
作者: [Shchygol, Ganna, Yakovlev, Alexei, Verstraelen, Toon]
通讯作者: Verstraelen, Toon
EAGER: Collaborative Research: MATDAT18 Type-I: Development of a machine learning framework to optimize ReaxFF force field parameters.
Collaborative Research: SI2-SSI: Development of an Integrated Molecular Design Environment for Lubrication Systems (iMoDELS)
Collaborative Research: Experimental and theoretical study on the structure and catalytic activity of metal cluster/metal oxide interfaces
国内基金
海外基金
Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    SATOSHI NAWATA
  • 依托单位:
Cell Research
Cell Research
Cell Research (细胞研究)