Physics of the Solid State

, Volume 61, Issue 11, pp 2083–2089 | Cite as

The Mechanism of Influence of Disperse Nanoparticles on Parameters of the Martensitic Transitions in Alloys with the Shape Memory Effect

  • G. A. MalyginEmail author


Within the diffuse martensitic transition theory based on the thermodynamic and kinetic equations and relations, the mechanism of influence of disperse nanoparticles on the parameters of martensitic transitions in alloys with the shape memory effect (SME) is analyzed. The objects of the analysis are the TiNi alloy with the varied sizes of Ti3Ni4 particle at their constant volume concentration, and the NiMnGaTb alloy with Tb precipitate particles with constant sizes and variation of volume concentration of the precipitates. Information about these alloys is available in the literature. The analysis has shown that, due to the coherent coupling of the Ti3Ni4 particles with the substrate, the temperature width of the transition RB19' depends on the particle sizes, which confirms the earlier established regularity of the local interior strain influence on this parameter. Concerning the NiMnGaTb alloy, the analysis has shown that, due to the presence of interior local strains associated with the Tb particles, the temperature width of the martensitic transformations increases linearly alongside the growth of the particle concentration in the alloy. The existence of the critical value of the particle concentration, above which the temperature width of the transition becomes indefinitely large, and the martensitic transformation in the alloy is blocked, is shown.


SME alloys martensitic transitions disperse nanoparticles phase transformation dislocations 



  1. 1.
    Y. Wu, J. Wang, C. Jiang, and H. Xu, Intermetallics 97, 42 (2018).CrossRefGoogle Scholar
  2. 2.
    X. Wang, S. Kustov, R. Li, D. Schryvers, B. Verlinden, and J. van Humbeeck, Acta Mater. 82, 224 (2015).CrossRefGoogle Scholar
  3. 3.
    E. Yu. Panchenko, Yu. I. Chumlyakov, I. V. Kireeva, A. V. Ovsyanikov, Kh. Sekhitoglu, I. Karaman, and G. Maier, Phys. Met. Metallogr. 106, 577 (2008).ADSCrossRefGoogle Scholar
  4. 4.
    W. Cai, J. Zhang, Z. Y. Gao, and J. H. Sui, Appl. Phys. Lett. 92, 252502 (2008).ADSCrossRefGoogle Scholar
  5. 5.
    X. Yi, X. Meng, W. Cai, and L. Zhao, Scr. Mater. 151, 90 (2018).CrossRefGoogle Scholar
  6. 6.
    G. A. Malygin, V. I. Nikolaev, V. M. Krymov, S. A. Pul’nev and S. I. Stepanov, Tech. Phys. 64, 819 (2019).CrossRefGoogle Scholar
  7. 7.
    G. A. Malygin, Phys. Usp. 44, 173 (2001).ADSCrossRefGoogle Scholar
  8. 8.
    G. A. Malygin, Phys. Solid State 61, 149 (2019).ADSCrossRefGoogle Scholar
  9. 9.
    G. A. Malygin, Phys. Solid State 61, 1251 (2019).ADSCrossRefGoogle Scholar
  10. 10.
    K. Otsuka and X. Ren, Prog. Mater. Sci. 50, 511 (2005).CrossRefGoogle Scholar
  11. 11.
    J. Eshelby, Continuous Theory of Dislocations, Collection of Articles (Inostr. Liter., Moscow, 1963).Google Scholar
  12. 12.
    D. Y. Li and L. Q. Chen, Acta Mater. 45, 471 (1997).CrossRefGoogle Scholar
  13. 13.
    G. A. Malygin, Phys. Solid State 45, 1566 (2003).ADSCrossRefGoogle Scholar
  14. 14.
    T. Honma, in Shape Memory Alloy-86, Ed. by Ch. Yoyi, T. Y. Hsu, and T. Ko (China Academic, Guilin, 1986), p. 47.Google Scholar
  15. 15.
    R. X. Wang, Y. Zohar, and M. Wong, J. Micromech. Microeng. 11, 686 (2001).ADSCrossRefGoogle Scholar

Copyright information

© Pleiades Publishing, Ltd. 2019

Authors and Affiliations

  1. 1.Ioffe InstituteSt. PetersburgRussia

Personalised recommendations