Ab initio molecular dynamics of hydrogen dissociation on metal surfaces using neural networks and novelty sampling

从头算 势能面 分子动力学 统计物理学 密度泛函理论 势能 半经典物理学 从头算量子化学方法 人工神经网络 离解(化学) 计算化学 化学 计算机科学 物理 量子力学 量子 分子 物理化学 人工智能
作者
Jeffery Ludwig,Dionisios G. Vlachos
出处
期刊:Journal of Chemical Physics [American Institute of Physics]
卷期号:127 (15) 被引量:80
标识
DOI:10.1063/1.2794338
摘要

We outline a hybrid multiscale approach for the construction of ab initio potential energy surfaces (PESs) useful for performing six-dimensional (6D) classical or quantum mechanical molecular dynamics (MD) simulations of diatomic molecules reacting at single crystal surfaces. The algorithm implements concepts from the corrugation reduction procedure, which reduces energetic variation in the PES, and uses neural networks for interpolation of smoothed ab initio data. A novelty sampling scheme is implemented and used to identify configurations that are most likely to be predicted inaccurately by the neural network. This hybrid multiscale approach, which couples PES construction at the electronic structure level to MD simulations at the atomistic scale, reduces the number of density functional theory (DFT) calculations needed to specify an accurate PES. Due to the iterative nature of the novelty sampling algorithm, it is possible to obtain a quantitative measure of the convergence of the PES with respect to the number of ab initio calculations used to train the neural network. We demonstrate the algorithm by first applying it to two analytic potentials, which model the H2∕Pt(111) and H2∕Cu(111) systems. These potentials are of the corrugated London-Eyring-Polanyi-Sato form, which are based on DFT calculations, but are not globally accurate. After demonstrating the convergence of the PES using these simple potentials, we use DFT calculations directly and obtain converged semiclassical trajectories for the H2∕Pt(111) system at the PW91/generalized gradient approximation level. We obtain a converged PES for a 6D hydrogen-surface dissociation reaction using novelty sampling coupled directly to DFT. These results, in excellent agreement with experiments and previous theoretical work, are compared to previous simulations in order to explore the sensitivity of the PES (and therefore MD) to the choice of exchange and correlation functional. Despite having a lower energetic corrugation in our PES, we obtain a broader reaction probability curve than previous simulations, which is attributed to increased geometric corrugation in the PES and the effect of nonparallel dissociation pathways.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
据说明天有雨完成签到,获得积分10
1秒前
大香樟树完成签到,获得积分10
1秒前
JamesPei应助爱吃香菜采纳,获得10
2秒前
缥缈的慕青完成签到,获得积分10
2秒前
123发布了新的文献求助10
3秒前
杜富豪完成签到 ,获得积分10
4秒前
qq完成签到 ,获得积分10
4秒前
lasu发布了新的文献求助10
5秒前
SHANDIAN完成签到,获得积分10
5秒前
5秒前
虚心海露完成签到,获得积分10
5秒前
6秒前
6秒前
火星上初翠应助pyh采纳,获得10
7秒前
去码头整点薯条完成签到,获得积分10
7秒前
8秒前
8秒前
小蘑菇应助加菲丰丰采纳,获得10
8秒前
科研通AI2S应助Yuu采纳,获得10
10秒前
Amonologue完成签到,获得积分10
11秒前
11秒前
11秒前
毛豆应助GY916采纳,获得10
12秒前
xxxx发布了新的文献求助10
12秒前
13秒前
13秒前
13秒前
yaaaaaa完成签到,获得积分10
14秒前
14秒前
sundayslyu发布了新的文献求助10
14秒前
脑洞疼应助bjb采纳,获得10
14秒前
隐形曼青应助小何尖尖角采纳,获得10
15秒前
17秒前
万能图书馆应助斯文山蝶采纳,获得10
17秒前
NSS完成签到,获得积分10
17秒前
wcy完成签到 ,获得积分10
17秒前
马秀玲完成签到,获得积分10
17秒前
生物小白完成签到,获得积分10
18秒前
123完成签到,获得积分10
19秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Molecular Mechanisms of Photosynthesis, 4th Edition 1000
Organic Reactions, Volume 116 1000
Current concepts in cutaneous toxicity : proceedings of the Fourth Conference on Cutaneous Toxicity, Washington, D.C., May 9-11, 1979 1000
The recovery-stress questionnaires : user manual 800
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7258843
求助须知:如何正确求助?哪些是违规求助? 8880808
关于积分的说明 18764245
捐赠科研通 6939299
什么是DOI,文献DOI怎么找? 3201445
关于科研通互助平台的介绍 2375349
邀请新用户注册赠送积分活动 2177240