Investigation on Chemical Behavior of Ni and Fe Impurities in LBE by Deep Potential Molecular Dynamics Simulation
The compatibility of liquid lead-bismuth eutectic (LBE) with structural materials is one of the problems in its application in advanced nuclear reactors. At present, the understanding of impurity atoms diffusion in liquid LBE is still limited. It is particularly difficult to study the chemical behav...
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| Format: | Article |
| Language: | English |
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Editorial Board of Atomic Energy Science and Technology
2023-12-01
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| Series: | Yuanzineng kexue jishu |
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| _version_ | 1797366810747600896 |
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| author | LIANG Ruting1,2;BO Tao2,*;NIE Changming1;ZHANG Lei2;CHAI Zhifang2;SHI Weiqun3,* |
| author_facet | LIANG Ruting1,2;BO Tao2,*;NIE Changming1;ZHANG Lei2;CHAI Zhifang2;SHI Weiqun3,* |
| author_sort | LIANG Ruting1,2;BO Tao2,*;NIE Changming1;ZHANG Lei2;CHAI Zhifang2;SHI Weiqun3,* |
| collection | DOAJ |
| description | The compatibility of liquid lead-bismuth eutectic (LBE) with structural materials is one of the problems in its application in advanced nuclear reactors. At present, the understanding of impurity atoms diffusion in liquid LBE is still limited. It is particularly difficult to study the chemical behaviors such as diffusion properties of impurity atoms in LBE by experimental methods. However, traditional theoretical calculations such as density functional theory (DFT) and classical molecular dynamics (MD) methods have dilemmas in simulation scale and simulation accuracy. To address those issues, a scheme based on DFT calculation, deep neural networks, and machine learning was introduced. By training on high-quality data sets generated by DFT calculations, three deep potential (DP) models of LBE, LBE-Ni, and LBE-Fe were constructed to describe the interaction between atoms. The results of AIMD calculation of radial distribution function (RDF) can be repeated by DPMD. By performing MD simulations with DP models, the microstructures of Ni, Fe impurities in LBE and the thermal physical properties of LBE were investigated. Meanwhile, the estimated thermophysical properties were discussed, including density, specific heat capacity, shear viscosity, and self-diffusion coefficient of Ni and Fe atoms. The higher RDF peaks of Bi-Ni and Bi-Fe reveal that both impurity atoms interact more strongly with Bi atoms. The predicted thermophysical properties are in good agreement with the experimental results, and have better accuracy than the results of the classical MD that based on the embedded atom method (EAM). In conclusion, a thorough understanding of the microstructure of impurities in LBE is provided and the data of the thermophysical properties of LBE are enriched. |
| first_indexed | 2024-03-08T17:09:02Z |
| format | Article |
| id | doaj.art-97fb2eb3e02249198b2f88a6750c4a7f |
| institution | Directory Open Access Journal |
| issn | 1000-6931 |
| language | English |
| last_indexed | 2024-03-08T17:09:02Z |
| publishDate | 2023-12-01 |
| publisher | Editorial Board of Atomic Energy Science and Technology |
| record_format | Article |
| series | Yuanzineng kexue jishu |
| spelling | doaj.art-97fb2eb3e02249198b2f88a6750c4a7f2024-01-04T01:46:47ZengEditorial Board of Atomic Energy Science and TechnologyYuanzineng kexue jishu1000-69312023-12-0157122376238710.7538/yzk.2023.youxian.0053Investigation on Chemical Behavior of Ni and Fe Impurities in LBE by Deep Potential Molecular Dynamics SimulationLIANG Ruting1,2;BO Tao2,*;NIE Changming1;ZHANG Lei2;CHAI Zhifang2;SHI Weiqun3,*01.School of Chemistry and Chemical Engineering, University of South China, Hengyang 421001, China;2.Engineering Laboratory of Advanced Energy Materials, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, China;3.Laboratory of Nuclear Energy Chemistry, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, ChinaThe compatibility of liquid lead-bismuth eutectic (LBE) with structural materials is one of the problems in its application in advanced nuclear reactors. At present, the understanding of impurity atoms diffusion in liquid LBE is still limited. It is particularly difficult to study the chemical behaviors such as diffusion properties of impurity atoms in LBE by experimental methods. However, traditional theoretical calculations such as density functional theory (DFT) and classical molecular dynamics (MD) methods have dilemmas in simulation scale and simulation accuracy. To address those issues, a scheme based on DFT calculation, deep neural networks, and machine learning was introduced. By training on high-quality data sets generated by DFT calculations, three deep potential (DP) models of LBE, LBE-Ni, and LBE-Fe were constructed to describe the interaction between atoms. The results of AIMD calculation of radial distribution function (RDF) can be repeated by DPMD. By performing MD simulations with DP models, the microstructures of Ni, Fe impurities in LBE and the thermal physical properties of LBE were investigated. Meanwhile, the estimated thermophysical properties were discussed, including density, specific heat capacity, shear viscosity, and self-diffusion coefficient of Ni and Fe atoms. The higher RDF peaks of Bi-Ni and Bi-Fe reveal that both impurity atoms interact more strongly with Bi atoms. The predicted thermophysical properties are in good agreement with the experimental results, and have better accuracy than the results of the classical MD that based on the embedded atom method (EAM). In conclusion, a thorough understanding of the microstructure of impurities in LBE is provided and the data of the thermophysical properties of LBE are enriched.lbethermophysical propertydiffusion coefficientfirst-principlemolecular dynamicsmachine learning |
| spellingShingle | LIANG Ruting1,2;BO Tao2,*;NIE Changming1;ZHANG Lei2;CHAI Zhifang2;SHI Weiqun3,* Investigation on Chemical Behavior of Ni and Fe Impurities in LBE by Deep Potential Molecular Dynamics Simulation Yuanzineng kexue jishu lbe thermophysical property diffusion coefficient first-principle molecular dynamics machine learning |
| title | Investigation on Chemical Behavior of Ni and Fe Impurities in LBE by Deep Potential Molecular Dynamics Simulation |
| title_full | Investigation on Chemical Behavior of Ni and Fe Impurities in LBE by Deep Potential Molecular Dynamics Simulation |
| title_fullStr | Investigation on Chemical Behavior of Ni and Fe Impurities in LBE by Deep Potential Molecular Dynamics Simulation |
| title_full_unstemmed | Investigation on Chemical Behavior of Ni and Fe Impurities in LBE by Deep Potential Molecular Dynamics Simulation |
| title_short | Investigation on Chemical Behavior of Ni and Fe Impurities in LBE by Deep Potential Molecular Dynamics Simulation |
| title_sort | investigation on chemical behavior of ni and fe impurities in lbe by deep potential molecular dynamics simulation |
| topic | lbe thermophysical property diffusion coefficient first-principle molecular dynamics machine learning |
| work_keys_str_mv | AT liangruting12botao2niechangming1zhanglei2chaizhifang2shiweiqun3 investigationonchemicalbehaviorofniandfeimpuritiesinlbebydeeppotentialmoleculardynamicssimulation |