Startseite Molecular dynamics study of the dissolution of crystalline and amorphous nickel nanoparticles in aluminium
Artikel
Lizenziert
Nicht lizenziert Erfordert eine Authentifizierung

Molecular dynamics study of the dissolution of crystalline and amorphous nickel nanoparticles in aluminium

  • Gennady M. Poletaev ORCID logo EMAIL logo , Roman Y. Rakitin ORCID logo und Irina V. Zorya ORCID logo
Veröffentlicht/Copyright: 4. Februar 2025
Veröffentlichen auch Sie bei De Gruyter Brill

Abstract

The dissolution of a nickel nanoparticle in aluminium under the conditions of the crystalline and amorphous state of aluminium and nickel, which can be achieved, in particular, with severe plastic deformation of the powders of the initial mixture (mechanoactivation), was studied by means of molecular dynamics. It is shown that the state of the aluminium structure (crystalline or amorphous) has a relatively small effect on the intensity of mutual diffusion of Ni and Al up to the melting temperature of aluminium. This is due to the formation of a crystalline aluminium layer around the crystalline particle, which repeats the Ni lattice. In the case of the amorphous state of the nickel particle and the aluminium matrix, dissolution occurred much faster than in the crystalline state of nickel. That is, mutual diffusion occurs significantly more strongly in the case of the amorphous state of nickel compared to the case of amorphous aluminium at the same constant temperature. The diameter of the nickel nanoparticle in the considered range from 4 to 12 nm did not affect the temperature at which the mutual diffusion of Ni and Al sharply accelerated with varying temperature. This was due to the fact that the melting point of aluminium did not change when simulating particles of different sizes.


Corresponding author: Gennady M. Poletaev, Polzunov Altai State Technical University, Lenina Ave. 46, 656038 Barnaul, Russia, E-mail:

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

1. Miracle, D. B. Acta Metall. Mater. 1993, 41, 649; https://doi.org/10.1016/0956-7151(93)90001-9.Suche in Google Scholar

2. Tresa, P.; Sammy, T. J. Propul. Power 2006, 22, 361; https://doi.org/10.2514/1.18239.Suche in Google Scholar

3. Reeves, R. V.; Mukasyan, A. S.; Son, S. F. J. Phys. Chem. 2010, 114, 14772; https://doi.org/10.1021/jp104686z.Suche in Google Scholar

4. Rogachev, A. S. Russ. Chem. Rev. 2008, 77, 21; https://doi.org/10.1070/RC2008v077n01ABEH003748.Suche in Google Scholar

5. Morris, M. A.; Leboeuf, M. Mater. Sci. Eng.: A 1997, 224, 1; https://doi.org/10.1016/S0921-5093(96)10532-3.Suche in Google Scholar

6. Bohn, R.; Klassen, T.; Bormann, R. Intermetallics 2001, 9, 559; https://doi.org/10.1016/S0966-9795(01)00039-5.Suche in Google Scholar

7. Kambara, M.; Uenishi, K.; Kobayashi, K. F. J. Mater. Sci. 2000, 35, 2897; https://doi.org/10.1023/A:1004771808047.10.1023/A:1004771808047Suche in Google Scholar

8. Kimura, H. Phil. Mag. A 1996, 73, 723; https://doi.org/10.1080/01418619608242993.Suche in Google Scholar

9. Boldyrev, V. V.; Tkacova, K. J. Mater. Synth. Process. 2000, 8, 121; https://doi.org/10.1023/A:1011347706721.10.1023/A:1011347706721Suche in Google Scholar

10. Filimonov, V. Y.; Loginova, M. V.; Ivanov, S. G.; Sitnikov, A. A.; Yakovlev, V. I.; Sobachkin, A. V.; Negodyaev, A. Z.; Myasnikov, A. Y. Combust. Sci. Technol. 2020, 192, 457; https://doi.org/10.1080/00102202.2019.1571053.Suche in Google Scholar

11. Loginova, M. V.; Yakovlev, V. I.; Filimonov, V. Yu.; Sitnikov, A. A.; Sobachkin, A. V.; Ivanov, S. G.; Gradoboev, A. V. Lett. Mater. 2018, 8, 129; https://doi.org/10.22226/2410-3535-2018-2-129-134.Suche in Google Scholar

12. Fourmont, A.; Politano, O.; Le Gallet, S.; Desgranges, C.; Baras, F. J. Appl. Phys. 2021, 129, 065301. https://doi.org/10.1063/5.0037397.Suche in Google Scholar

13. Baras, F.; Bizot, Q.; Fourmont, A.; Le Gallet, S.; Politano, O. Appl. Phys. A 2021, 127, 555; https://doi.org/10.1007/s00339-021-04700-9.Suche in Google Scholar

14. Purja Pun, G. P.; Mishin, Y. Philos. Mag. 2009, 89, 3245; https://doi.org/10.1080/14786430903258184.Suche in Google Scholar

15. Levchenko, E. V.; Ahmed, T.; Evteev, A. V. Acta Mater. 2017, 136, 74; https://doi.org/10.1016/j.actamat.2017.06.056.Suche in Google Scholar

16. Poletaev, G. M.; Rakitin, R. Y. Mater. Physi. Mech. 2022, 48, 452; https://doi.org/10.18149/MPM.4832022_15.Suche in Google Scholar

17. Chen, C.; Zhang, F.; Xu, H.; Yang, Z.; Poletaev, G. M. J. Mater. Sci. 2022, 57, 1833; https://doi.org/10.1007/s10853-021-06837-7.Suche in Google Scholar

18. Poletaev, G. M. Molecular Dynamics Research (MDR). In Certificate Of State Registration of a Computer Program No. 2015661912 Dated; Rospatent: Moscow, 2015.Suche in Google Scholar

19. Levchenko, E. V.; Evteev, A. V.; Lorscheider, T.; Belova, I. V.; Murch, G. E. Comput. Mater. Sci. 2013, 79, 316; https://doi.org/10.1016/j.commatsci.2013.06.005.Suche in Google Scholar

20. Cherukara, M. J.; Weihs, T. P.; Strachan, A. Acta Mater. 2015, 96, 1; https://doi.org/10.1016/j.actamat.2015.06.008.Suche in Google Scholar

21. Poletaev, G. M.; Bebikhov, Y.V.; Semenov, A. S.; Sitnikov, A. A. J. Exp. Theor. Phys. 2023, 136, 477; https://doi.org/10.1134/S1063776123040118.Suche in Google Scholar

22. Phillpot, S. R.; Lutsko, J. F.; Wolf, D.; Yip, S. Phys. Rev. B 1989, 40, 2831; https://doi.org/10.1103/PhysRevB.40.2831.Suche in Google Scholar

23. Wejrzanowski, T.; Lewandowska, M.; Sikorski, K.; Kurzydlowski, K. J. J. Appl. Phys. 2014, 116, 164302; https://doi.org/10.1063/1.4899240.Suche in Google Scholar

24. Noori, Z.; Panjepour, M.; Ahmadian, M. J. Mater. Res. 2015, 30, 1648; https://doi.org/10.1557/jmr.2015.109.Suche in Google Scholar

25. Qi, Y.; Cagin, Т.; Johnson, W. L.; Goddard, W. A.III.. J. Chem. Phys. 2001, 115, 385; https://doi.org/10.1063/1.1373664.Suche in Google Scholar

26. Poletaev, G. M.; Gafner, Y. Y.; Gafner, S. L. Lett. Mater. 2023, 13, 298; https://doi.org/10.22226/2410-3535-2023-4-298-303.Suche in Google Scholar

27. Xiong, S.; Qi, W.; Cheng, Y.; Huang, B.; Wang, M.; Li, Y. Phys. Chem. Chem. Phys. 2011, 13, 10652; https://doi.org/10.1039/C0CP90161J.Suche in Google Scholar

28. Hamilton, J. C.; Foiles, S. M. Phys. Rev. Lett. 1995, 75, 882; https://doi.org/10.1103/PhysRevLett.75.882.Suche in Google Scholar PubMed

29. Wang, Y.; Ruterana, P.; Kret, S.; Chen, J.; El Kazzi, S.; Desplanque, L.; Wallart, X. Appl. Phys. Lett. 2012, 100, 262110; https://doi.org/10.1063/1.4731787.Suche in Google Scholar

Received: 2023-06-05
Accepted: 2024-10-08
Published Online: 2025-02-04
Published in Print: 2025-02-25

© 2025 Walter de Gruyter GmbH, Berlin/Boston

Heruntergeladen am 15.11.2025 von https://www.degruyterbrill.com/document/doi/10.1515/ijmr-2023-0187/pdf
Button zum nach oben scrollen