A Machine Learning Model to Classify Dynamic Processes in Liquid Water**
文献类型：期刊论文
| 作者 | Huang, Jie; Huang, Gang1; Li, Shiben |
| 刊名 | CHEMPHYSCHEM
 |
| 出版日期 | 2022 |
| 关键词 | JUMP MECHANISM CLUSTERS EXCHANGE SPECTROSCOPY DIFFUSION NETWORKS CELL |
| ISSN号 | 1439-4235 |
| DOI | 10.1002/cphc.202100599 |
| 英文摘要 | The dynamics of water molecules plays a vital role in understanding water. We combined computer simulation and deep learning to study the dynamics of H-bonds between water molecules. Based on ab initio molecular dynamics simulations and a newly defined directed Hydrogen (H-) bond population operator, we studied a typical dynamic process in bulk water: interchange, in which the H-bond donor reverses roles with the acceptor. By designing a recurrent neural network-based model, we have successfully classified the interchange and breakage processes in water. We have found that the ratio between them is approximately 1 : 4, and it hardly depends on temperatures from 280 to 360 K. This work implies that deep learning has the great potential to help distinguish complex dynamic processes containing H-bonds in other systems. |
| 学科主题 | Chemistry ; Physics |
| 语种 | 英语 |
| 源URL | [http://ir.itp.ac.cn/handle/311006/27909]  |
| 专题 | 理论物理研究所_理论物理所1978-2010年知识产出 |
| 作者单位 | 1.Wenzhou Univ, Dept Phys, Wenzhou 325035, Zhejiang, Peoples R China 2.Chinese Acad Sci, Inst Theoret Phys, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Huang, Jie,Huang, Gang,Li, Shiben. A Machine Learning Model to Classify Dynamic Processes in Liquid Water**[J]. CHEMPHYSCHEM,2022. |
| APA | Huang, Jie,Huang, Gang,&Li, Shiben.(2022).A Machine Learning Model to Classify Dynamic Processes in Liquid Water**.CHEMPHYSCHEM. |
| MLA | Huang, Jie,et al."A Machine Learning Model to Classify Dynamic Processes in Liquid Water**".CHEMPHYSCHEM (2022). |
入库方式： OAI收割
来源：理论物理研究所
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