Towards fully ab initio simulation of atmospheric aerosol nucleation
文献类型：期刊论文
| 作者 | Jiang, Shuai2; Liu, Yi-Rong2 ; Huang, Teng1; Feng, Ya-Juan2; Wang, Chun-Yu2; Wang, Zhong-Quan1; Ge, Bin-Jing2; Liu, Quan-Sheng2; Guang, Wei-Ran2; Huang, Wei1,2,3
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| 刊名 | NATURE COMMUNICATIONS
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| 出版日期 | 2022-10-14 |
| 卷号 | 13 |
| DOI | 10.1038/s41467-022-33783-y |
| 通讯作者 | Jiang, Shuai(shuaijiang@ustc.edu.cn) |
| 英文摘要 | Atmospheric aerosol nucleation contributes to approximately half of the worldwide cloud condensation nuclei. Despite the importance of climate, detailed nucleation mechanisms are still poorly understood. Understanding aerosol nucleation dynamics is hindered by the nonreactivity of force fields (FFs) and high computational costs due to the rare event nature of aerosol nucleation. Developing reactive FFs for nucleation systems is even more challenging than developing covalently bonded materials because of the wide size range and high dimensional characteristics of noncovalent hydrogen bonding bridging clusters. Here, we propose a general workflow that is also applicable to other systems to train an accurate reactive FF based on a deep neural network (DNN) and further bridge DNN-FF-based molecular dynamics (MD) with a cluster kinetics model based on Poisson distributions of reactive events to overcome the high computational costs of direct MD. We found that previously reported acid-base formation rates tend to be significantly underestimated, especially in polluted environments, emphasizing that acid-base nucleation observed in multiple environments should be revisited. Atmosphere aerosol nucleation contributes to climate change, air pollution, and human health, however the mechanisms are complex and elusive. Here the authors propose a general workflow based on deep neural network-based force field, paving the way towards fully ab initio simulation of atmospheric aerosol nucleation. |
| WOS关键词 | SULFURIC-ACID ; PARTICLE FORMATION ; CHEMISTRY ; GROWTH |
| 资助项目 | MCC Lab of Information Science and Technology Institution, USTC ; National Natural Science Foundation of China[41877305] |
| WOS研究方向 | Science & Technology - Other Topics |
| 语种 | 英语 |
| WOS记录号 | WOS:000874078500021 |
| 出版者 | NATURE PORTFOLIO |
| 资助机构 | MCC Lab of Information Science and Technology Institution, USTC ; National Natural Science Foundation of China |
| 源URL | [http://ir.hfcas.ac.cn:8080/handle/334002/130009]  |
| 专题 | 中国科学院合肥物质科学研究院 |
| 通讯作者 | Jiang, Shuai |
| 作者单位 | 1.Chinese Acad Sci, Anhui Inst Opt & Fine Mech, Lab Atmospher Phys Chem, Hefei 230031, Anhui, Peoples R China 2.Univ Sci & Technol China, Sch Informat Sci & Technol, Hefei 230026, Anhui, Peoples R China 3.Chinese Acad Sci, Ctr Excellent Urban Atmospher Environm, Inst Urban Environm, Xiamen 361021, Fujian, Peoples R China |
| 推荐引用方式 GB/T 7714 | Jiang, Shuai,Liu, Yi-Rong,Huang, Teng,et al. Towards fully ab initio simulation of atmospheric aerosol nucleation[J]. NATURE COMMUNICATIONS,2022,13. |
| APA | Jiang, Shuai.,Liu, Yi-Rong.,Huang, Teng.,Feng, Ya-Juan.,Wang, Chun-Yu.,...&Huang, Wei.(2022).Towards fully ab initio simulation of atmospheric aerosol nucleation.NATURE COMMUNICATIONS,13. |
| MLA | Jiang, Shuai,et al."Towards fully ab initio simulation of atmospheric aerosol nucleation".NATURE COMMUNICATIONS 13(2022). |
入库方式： OAI收割
来源：合肥物质科学研究院
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