Skip to main content
Log in

Revisiting the breakdown of Stokes-Einstein relation in glass-forming liquids with machine learning

  • Article
  • Published:
Science China Physics, Mechanics & Astronomy Aims and scope Submit manuscript

Abstract

The Stokes-Einstein (SE) relation has been considered as one of the hallmarks of dynamics in liquids. It describes that the diffusion constant D is proportional to (τ/T)−1, where τ is the structural relaxation time and T is the temperature. In many glass-forming liquids, the breakdown of SE relation often occurred when the dynamics of the liquids becomes glassy, and its origin is still debated among many scientists. Using molecular dynamics simulations and support-vector machine method, it is found that the scaling between diffusion and relaxation fails when the total population of solid-like clusters shrinks at the maximal rate with decreasing temperature, which implies a dramatic unification of clusters into an extensive dominant one occurs at the time of breakdown of the SE relation. Our data leads to an interpretation that the SE violation in metallic glass-forming liquids can be attributed to a specific change in the atomic structures.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. P. G. Debenedetti, and F. H. Stillinger, Nature 410, 259 (2001).

    Article  ADS  Google Scholar 

  2. W. H. Wang, Prog. Mater. Sci. 106, 100561 (2019).

    Article  Google Scholar 

  3. J. C. Qiao, Q. Wang, J. M. Pelletier, H. Kato, R. Casalini, D. Crespo, E. Pineda, Y. Yao, and Y. Ysang, Prog. Mater. Sci. 104, 250 (2019).

    Article  Google Scholar 

  4. Z. W. Wu, W. Kob, W. H. Wang, and L. Xu, Nat. Commun. 9, 5334 (2018), arXiv: 1808.04084.

    Article  ADS  Google Scholar 

  5. P. Luo, Y. Z. Li, H. Y. Bai, P. Wen, and W. H. Wang, Phys. Rev. Lett. 116, 175901 (2016).

    Article  ADS  Google Scholar 

  6. T. Scopigno, G. Ruocco, F. Sette, and G. Monaco, Science 302, 849 (2003), arXiv: cond-mat/0311305.

    Article  ADS  Google Scholar 

  7. L. Wang, A. Ninarello, P. Guan, L. Berthier, G. Szamel, and E. Flenner, Nat. Commun. 10, 26 (2019), arXiv: 1804.08765.

    Article  ADS  Google Scholar 

  8. T. Kawasaki, and K. Kim, Sci. Adv. 3, e1700399 (2017), arXiv: 1701.06028.

    Article  ADS  Google Scholar 

  9. Y. C. Hu, F. X. Li, M. Z. Li, H. Y. Bai, and W. H. Wang, J. Appl. Phys. 119, 205108 (2016).

    Article  ADS  Google Scholar 

  10. R. Soklaski, V. Tran, Z. Nussinov, K. F. Kelton, and L. Yang, Philos. Mag. 96, 1212 (2016), arXiv: 1502.01739.

    Article  ADS  Google Scholar 

  11. L. Xu, F. Mallamace, Z. Yan, F. W. Starr, S. V. Buldyrev, and H. Eugene Stanley, Nat. Phys. 5, 565 (2009).

    Article  Google Scholar 

  12. S. Sastry, and C. Austen Angell, Nat. Mater. 2, 739 (2003).

    Article  ADS  Google Scholar 

  13. F. H. Stillinger, and J. A. Hodgdon, Phys. Rev. E 50, 2064 (1994).

    Article  ADS  Google Scholar 

  14. G. Tarjus, and D. Kivelson, J. Chem. Phys. 103, 3071 (1995).

    Article  ADS  Google Scholar 

  15. S. R. Becker, P. H. Poole, and F. W. Starr, Phys. Rev. Lett. 97, 055901 (2006), arXiv: cond-mat/0605170.

    Article  ADS  Google Scholar 

  16. S. Pan, Z. W. Wu, W. H. Wang, M. Z. Li, and L. Xu, Sci. Rep. 7, 39938 (2017).

    Article  ADS  Google Scholar 

  17. S. S. Schoenholz, E. D. Cubuk, D. M. Sussman, E. Kaxiras, and A. J. Liu, Nat. Phys. 12, 469 (2016).

    Article  Google Scholar 

  18. Y. T. Sun, H. Y. Bai, M. Z. Li, and W. H. Wang, J. Phys. Chem. Lett. 8, 3434 (2017).

    Article  Google Scholar 

  19. S. Plimpton, J. Comput. Phys. 117, 1 (1995).

    Article  ADS  Google Scholar 

  20. M. I. Mendelev, D. J. Sordelet, and M. J. Kramer, J. Appl. Phys. 102, 043501 (2007).

    Article  ADS  Google Scholar 

  21. W. Kob, and H. C. Andersen, Phys. Rev. E 52, 4134 (1995), arXiv: cond-mat/9505118.

    Article  ADS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to ZhenWei Wu.

Electronic supplementary material

11433_2020_1539_MOESM1_ESM.pdf

Supplementary Information for “Revisiting the structural signature of breakdown of Stokes-Einstein relation in a glass-forming liquid with machine learning”

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wu, Z., Li, R. Revisiting the breakdown of Stokes-Einstein relation in glass-forming liquids with machine learning. Sci. China Phys. Mech. Astron. 63, 276111 (2020). https://doi.org/10.1007/s11433-020-1539-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11433-020-1539-4

Keywords

Navigation