Beyond harmonic transition state theory for accelerating molecular dynamics
超越调和过渡态理论加速分子动力学
基本信息
- 批准号:1152342
- 负责人:
- 金额:$ 49.18万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2012
- 资助国家:美国
- 起止时间:2012-08-15 至 2016-07-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Graeme Henkelman from the University of Texas at Austin is supported by the Chemical Theory, Models and Computational Methods (CTMC) Program and the Office of Cyber Infrastructure (OCI) in developing algorithms for accelerating molecular dynamics simulations. For rare event systems, such as diffusion in solids and reactions at surfaces, transition state theory (TST) allows for a separation of time scales between that of molecular vibrations and the reactive events of interest. When reactive mechanisms are not known, an adaptive version of the kinetic Monte Carlo (KMC) method is used to find saddle points and rates are evaluated with harmonic TST. To reduce the computational cost, a database is employed to store kinetic events and to make them available for later use in separate calculations with similar chemistry. When the reaction mechanisms for a class of system are known, the computational cost is low because all events are drawn from the database. To further accelerate the simulations, groups of states connected by fast rates are escaped using an analytic solution to the master equation. Storing the local connectivity of these states is essential for efficiency. Accuracy will be improved with a set of methods ranging from harmonic TST to the (classically) exact full TST plus dynamical corrections. The challenge of TST is finding a dividing surface that separates reactants from any product state. A support vector machine is being developed to provide an analytic classification function based upon learned data. Sampled points around the decision surface will be used to train the machine so that it can provide an accurate transition state without prior knowledge of reaction mechanisms.This work is directed at alleviating the ultralong computational times needed for simulation of realistic chemical or material processes, e.g., catalysis, protein folding, molecular diffusion and so on. The characteristic times for basic molecular motion are many, many times faster than the time scales we measure in the laboratory, and so acceleration algorithms must be developed. EON2 is being developed as a distributed open-source program developed by the PI and collaborators to calculate long-timescale molecular dynamics in systems, for example, undergoing catalys and clustering on metal substrates. It will use advanced database techniques and machine learning, and will be usable in conjunction with other software through customized interfaces. A discussion forum is hosted by the PI for anyone with questions about the algorithms, software or science. The project has been opened up so that computers on campus, supercomputers with idle time, and anyone from the public can contribute computational resources to accelerate dynamics simulations at the atomic scale. This aspect of the outreach program gives the public direct access to the research being done as part of this project.
来自德克萨斯大学奥斯汀分校的Graeme Henkelman得到了化学理论,模型和计算方法(CTMC)计划和网络基础设施办公室(OCI)的支持,以开发加速分子动力学模拟的算法。对于稀有事件系统,如固体中的扩散和表面反应,过渡态理论(TST)允许分离分子振动和感兴趣的反应事件之间的时间尺度。当反应机制是未知的,自适应版本的动力学蒙特卡罗(KMC)方法被用来找到鞍点和率进行评估与谐波TST。 为了降低计算成本,采用数据库来存储动力学事件,并使它们可用于稍后在具有类似化学的单独计算中使用。当一类系统的反应机理已知时,由于所有事件都是从数据库中提取的,因此计算成本很低。为了进一步加速模拟,通过快速速率连接的状态组使用主方程的解析解来逃逸。存储这些状态的本地连接性对于效率至关重要。 精度将提高一套方法,从谐波TST的(经典)准确的全TST加上动态校正。TST的挑战是找到一个将反应物与任何产物状态分开的分界面。目前正在开发一种支持向量机,以便根据学习到的数据提供分析分类功能。 决策表面周围的采样点将用于训练机器,以便它可以提供准确的过渡态,而无需预先知道反应机理。这项工作旨在减轻模拟现实化学或材料过程所需的超长计算时间,例如,催化、蛋白质折叠、分子扩散等等。基本分子运动的特征时间比我们在实验室测量的时间尺度快很多很多倍,因此必须开发加速算法。 EON2是由PI和合作者开发的分布式开源程序,用于计算系统中的长时间尺度分子动力学,例如,在金属基底上进行催化剂和聚类。 它将使用先进的数据库技术和机器学习,并将通过定制界面与其他软件结合使用。 PI为任何对算法、软件或科学有疑问的人主办了一个讨论论坛。 该项目已经开放,以便校园内的计算机,空闲时间的超级计算机以及任何公众都可以贡献计算资源,以加速原子尺度的动力学模拟。外联方案的这一方面使公众能够直接获得作为该项目一部分正在进行的研究。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Graeme Henkelman其他文献
Iterative redox activation promotes interfacial synergy in an Ag/Cusubx/subO catalyst for oxygen reduction
迭代氧化还原活化促进了用于氧还原的 Ag/CuₓO 催化剂中的界面协同作用
- DOI:
10.1016/j.cej.2022.136966 - 发表时间:
2022-10-15 - 期刊:
- 影响因子:13.200
- 作者:
Youngtae Park;Kihyun Shin;Changsoo Lee;Sang-Yeon Lee;Yong-Kul Lee;Chang-Hee Kim;Hyun-Seok Cho;Graeme Henkelman;Hyuck Mo Lee - 通讯作者:
Hyuck Mo Lee
CO<sub>2</sub>-mediated porphyrin catalysis in reversible Li-CO<sub>2</sub> cells
- DOI:
10.1016/j.cej.2023.147141 - 发表时间:
2023-12-01 - 期刊:
- 影响因子:
- 作者:
Boran Kim;Kihyun Shin;Graeme Henkelman;Won-Hee Ryu - 通讯作者:
Won-Hee Ryu
COsub2/sub-mediated porphyrin catalysis in reversible Li-COsub2/sub cells
二氧化碳介导的卟啉催化在可逆锂二氧化碳电池中
- DOI:
10.1016/j.cej.2023.147141 - 发表时间:
2023-12-01 - 期刊:
- 影响因子:13.200
- 作者:
Boran Kim;Kihyun Shin;Graeme Henkelman;Won-Hee Ryu - 通讯作者:
Won-Hee Ryu
Simple construction and reversible sequential evolution mechanism of nitrogen-doped mesoporous carbon/SnSsub2/sub nanosheets in lithium-ion batteries
锂离子电池中氮掺杂介孔碳/SnS₂纳米片的简单结构和可逆顺序演化机制
- DOI:
10.1016/j.apsusc.2023.156673 - 发表时间:
2023-05-01 - 期刊:
- 影响因子:6.900
- 作者:
Kun Liu;Jia-ao Wang;Chenjie Lou;Ziru Zhou;Ning Zhang;Yingtao Yu;Qingxiao Zhang;Graeme Henkelman;Mingxue Tang;Juncai Sun - 通讯作者:
Juncai Sun
Calculations of selective Si epitaxial growth
- DOI:
10.1016/j.apsusc.2020.145888 - 发表时间:
2020-06-01 - 期刊:
- 影响因子:
- 作者:
Wenrui Chai;Muthukumar Kaliappan;Michael Haverty;David Thompson;Graeme Henkelman - 通讯作者:
Graeme Henkelman
Graeme Henkelman的其他文献
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{{ truncateString('Graeme Henkelman', 18)}}的其他基金
Computational Methods for Modeling Reaction Dynamics in Batteries and Catalysts
电池和催化剂反应动力学建模的计算方法
- 批准号:
2102317 - 财政年份:2021
- 资助金额:
$ 49.18万 - 项目类别:
Standard Grant
Computational methodology to determine rare event chemical reaction dynamics and networks
确定罕见事件化学反应动力学和网络的计算方法
- 批准号:
1764230 - 财政年份:2018
- 资助金额:
$ 49.18万 - 项目类别:
Standard Grant
DMREF: Collaborative Research: Toolkit to Characterize and Design Bi-functional Nanoparticle Catalysts
DMREF:协作研究:表征和设计双功能纳米粒子催化剂的工具包
- 批准号:
1534177 - 财政年份:2015
- 资助金额:
$ 49.18万 - 项目类别:
Standard Grant
Collaborative Research: CDS&E: Experimentally verified nano-oxidation simulations of Cu surfaces
合作研究:CDS
- 批准号:
1410335 - 财政年份:2014
- 资助金额:
$ 49.18万 - 项目类别:
Continuing Grant
CAREER: Methods for Calculating Molecular Dynamics over Long Time Scales
职业:长时间尺度内分子动力学的计算方法
- 批准号:
0645497 - 财政年份:2007
- 资助金额:
$ 49.18万 - 项目类别:
Continuing Grant
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