Knowledge Management System Of Institute of process engineering,CAS
| Revisiting the structure, interaction, and dynamical property of ionic liquid from the deep learning force field | |
| Ling, Yulong1,2; Li, Kun2; Wang, Mi2; Lu, Junfeng2; Wang, Chenlu2; Wang, Yanlei2,3; He, Hongyan1,2,4 | |
| 2023-01-30 | |
| Source Publication | JOURNAL OF POWER SOURCES
 |
| ISSN | 0378-7753 |
| Volume | 555Pages:8 |
| Abstract | Rational understanding of interaction and structure of ionic liquids (ILs) is vital for their application in super -capacitors. The force field trained by machine learning has aroused considerable interest in the molecular design of ILs, which can effectively balance the competition between computational accuracy and efficiency. In this work, a new deep learning force field (DPFF) for 10 different ILs was obtained, where the dataset for atomic energy and force was prepared via the ab initio molecular dynamics (MD) simulation. Using the trained DPFF, the ns-long MD simulations for various ILs were performed successfully. Combining the error analysis on atomic energy, distribution of bonds and angles, and potential energy, one can prove that the MD simulation with DPFF can describe the force and energy of ILs with ab initio precision. Meanwhile, the analysis of the vibrational spectrum and hydrogen bond suggests that the DPFF can also predict the coupling nature between coulombic and hydrogen bonding interactions within ILs reasonably. Furthermore, the DPFF for ILs is trained to extend to the bulk system. Hence, DPFF, possessing high accuracy and low computational cost, can serve as an effective tool for the molecular design of new ILs-based electrolytes for high-performance energy storage devices. |
| Keyword | Ionic liquids Molecular dynamics simulations Force field Hydrogen bond Machine learning |
| DOI | 10.1016/j.jpowsour.2022.232350 |
| Language | 英语 |
| WOS Keyword | MOLECULAR-DYNAMICS ; SIMULATION ; SEPARATION ; MECHANISM ; GAS |
| Funding Project | National Key R&D Program of China[2021YFB3802600] ; National Natural Science Foundation of China[21922813] ; National Natural Science Foundation of China[22078322] ; Youth Innovation Promotion Association of CAS[2021046] ; Youth Innovation Promotion Association of CAS[Y2021022] ; Innovation Academy for Green Manufacture, Chinese Academy of Sciences[IAGM2020C16] |
| WOS Research Area | Chemistry ; Electrochemistry ; Energy & Fuels ; Materials Science |
| WOS Subject | Chemistry, Physical ; Electrochemistry ; Energy & Fuels ; Materials Science, Multidisciplinary |
| Funding Organization | National Key R&D Program of China ; National Natural Science Foundation of China ; Youth Innovation Promotion Association of CAS ; Innovation Academy for Green Manufacture, Chinese Academy of Sciences |
| WOS ID | WOS:000891784100004 |
| Publisher | ELSEVIER |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ipe.ac.cn/handle/122111/56078 |
| Collection | 中国科学院过程工程研究所 |
| Corresponding Author | Wang, Yanlei; He, Hongyan |
| Affiliation | 1.Zhengzhou Univ, Henan Inst Adv Technol, Zhengzhou 450003, Peoples R China 2.Chinese Acad Sci, Beijing Key Lab Ion Liquids Clean Proc, State Key Lab Multiphase Complex Syst, CAS Key Lab Green Proc & Engn,Inst Proc Engn, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.Chinese Acad Sci, Innovat Acad Green Manufacture, Beijing 100190, Peoples R China |
| First Author Affilication | Center of lonic Liquids and Green Engineering |
| Corresponding Author Affilication | Center of lonic Liquids and Green Engineering |
| Recommended Citation GB/T 7714 | Ling, Yulong,Li, Kun,Wang, Mi,et al. Revisiting the structure, interaction, and dynamical property of ionic liquid from the deep learning force field[J]. JOURNAL OF POWER SOURCES,2023,555:8. |
| APA | Ling, Yulong.,Li, Kun.,Wang, Mi.,Lu, Junfeng.,Wang, Chenlu.,...&He, Hongyan.(2023).Revisiting the structure, interaction, and dynamical property of ionic liquid from the deep learning force field.JOURNAL OF POWER SOURCES,555,8. |
| MLA | Ling, Yulong,et al."Revisiting the structure, interaction, and dynamical property of ionic liquid from the deep learning force field".JOURNAL OF POWER SOURCES 555(2023):8. |
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