| Machine learning coarse grained models of dissolutive wetting: a droplet on soluble surfaces | |
Miao Q(苗青); Yuan QZ(袁泉子)
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| Source Publication | PHYSICAL CHEMISTRY CHEMICAL PHYSICS
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| 2023-03-08 | |
| Volume | 25Issue:10Pages:7487-7495 |
| ISSN | 1463-9076 |
| Abstract | Dissolutive wetting is not only a key problem in application fields such as energy, medicine, micro devices and etc., but also a frontier issue of academic research. As an important tool for exploring the micro mechanisms of dissolutive wetting, molecular dynamics simulations are limited by simulation scale and force field parameters. Thus, artificial intelligence is introduced into the multi scale simulation framework to tackle such challenges. By combining density functional theory, molecular dynamics simulations and experiments, we obtain a coarse grained model of the glucose water dissolution pair. Furthermore, the structure of the solid molecules and the hydration shell near the solute particles are calculated by quantum mechanics/molecular mechanics to verify the accuracy of the model. Finally, the applicability of the coarse grained model in dissolutive wetting is proven by experimental results. We believe our machine learning method not only lays a foundation for exploring the micro mechanisms of dissolutive wetting, but also provides a general approach for obtaining the force field parameters of different systems. |
| DOI | 10.1039/d3cp00112a |
| Indexed By | SCI ; EI |
| Language | 英语 |
| WOS ID | WOS:000940541100001 |
| WOS Research Area | Chemistry, Physical ; Physics, Atomic, Molecular & Chemical |
| WOS Subject | Chemistry ; Physics |
| Funding Organization | National Natural Science Foundation of China (NSFC) [12072346, 12032019] |
| Classification | 二类/Q1 |
| Ranking | 1 |
| Contributor | Yuan, QZ (corresponding author), Chinese Acad Sci, Inst Mech, State Key Lab Nonlinear Mech, Beijing 100190, Peoples R China. ; Yuan, QZ (corresponding author), Univ Chinese Acad Sci, Sch Engn Sci, Beijing 100049, Peoples R China. |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://dspace.imech.ac.cn/handle/311007/91867 |
| Collection | 非线性力学国家重点实验室 |
| Affiliation | 1.Chinese Acad Sci, Inst Mech, State Key Lab Nonlinear Mech, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Engn Sci, Beijing 100049, Peoples R China 3.Hyperveloc Aerodynam Inst CARDC, Mianyang 621000, Peoples R China |
| Recommended Citation GB/T 7714 | Miao Q,Yuan QZ. Machine learning coarse grained models of dissolutive wetting: a droplet on soluble surfaces[J]. PHYSICAL CHEMISTRY CHEMICAL PHYSICS,2023,25,10,:7487-7495.Rp_Au:Yuan, QZ (corresponding author), Chinese Acad Sci, Inst Mech, State Key Lab Nonlinear Mech, Beijing 100190, Peoples R China., Yuan, QZ (corresponding author), Univ Chinese Acad Sci, Sch Engn Sci, Beijing 100049, Peoples R China. |
| APA | 苗青,&袁泉子.(2023).Machine learning coarse grained models of dissolutive wetting: a droplet on soluble surfaces.PHYSICAL CHEMISTRY CHEMICAL PHYSICS,25(10),7487-7495. |
| MLA | 苗青,et al."Machine learning coarse grained models of dissolutive wetting: a droplet on soluble surfaces".PHYSICAL CHEMISTRY CHEMICAL PHYSICS 25.10(2023):7487-7495. |
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| Jp2023Fa299.pdf（4266KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Download | |
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