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Special Issue:
SPECIAL TOPIC — Smart design of materials and design of smart materials
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| SPECIAL TOPIC—Smart design of materials and design of smart materials |
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Reconstruction and stability of Fe3O4(001) surface: An investigation based on particle swarm optimization and machine learning |
| Hongsheng Liu(柳洪盛), Yuanyuan Zhao(赵圆圆), Shi Qiu(邱实), Jijun Zhao(赵纪军), and Junfeng Gao(高峻峰)† |
| Key Laboratory of Materials Modification by Laser, Ion and Electron Beams(Dalian University of Technology), Ministry of Education, Dalian 116024, China |
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Abstract Magnetite nanoparticles show promising applications in drug delivery, catalysis, and spintronics. The surface of magnetite plays an important role in these applications. Therefore, it is critical to understand the surface structure of Fe3O4 at atomic scale. Here, using a combination of first-principles calculations, particle swarm optimization (PSO) method and machine learning, we investigate the possible reconstruction and stability of Fe3O4(001) surface. The results show that besides the subsurface cation vacancy (SCV) reconstruction, an A layer with Fe vacancy (A-layer-VFe) reconstruction of the (001) surface also shows very low surface energy especially at oxygen poor condition. Molecular dynamics simulation based on the iron-oxygen interaction potential function fitted by machine learning further confirms the thermodynamic stability of the A-layer-VFe reconstruction. Our results are also instructive for the study of surface reconstruction of other metal oxides.
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Received: 15 January 2023
Revised: 02 February 2023
Accepted manuscript online: 08 February 2023
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PACS:
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68.35.-p
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(Solid surfaces and solid-solid interfaces: structure and energetics)
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68.35.B-
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(Structure of clean surfaces (and surface reconstruction))
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| Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 12004064, 12074053, and 91961204), the Fundamental Research Funds for the Central Universities (Grant No. DUT22LK11) and XingLiaoYingCai Project of Liaoning Province, China (Grant No. XLYC1907163). The calculations were performed on Tianjin Supercomputing Platform, Shanghai Supercomputing Platform. |
Corresponding Authors:
Junfeng Gao
E-mail: gaojf@dlut.edu.cn
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Cite this article:
Hongsheng Liu(柳洪盛), Yuanyuan Zhao(赵圆圆), Shi Qiu(邱实), Jijun Zhao(赵纪军), and Junfeng Gao(高峻峰) Reconstruction and stability of Fe3O4(001) surface: An investigation based on particle swarm optimization and machine learning 2023 Chin. Phys. B 32 056802
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