Calculation of isothermal compressibility of potassium halide melts and in binary mixtures KI–KX (X = F, Cl, Br) by the classical molecular dynamics

封面

如何引用文章

全文:

开放存取 开放存取
受限制的访问 ##reader.subscriptionAccessGranted##
受限制的访问 订阅存取

详细

Calculations of the isothermal compressibility (ᵡT) of individual potassium halides and some binary mixtures, namely KI–KX (X = F, Cl, Br), by using the classical molecular dynamics were carried out. Simulations of potassium halide melts using the Born-Mayer-Huggins pair potential showed good agreement between the calculated isothermal compressibility values and experimental data. A systematic underestimation of the calculated ᵡT values for individual melts was discovered, with the maximum difference between the calculated and experimental values being 24% for potassium chloride. For binary mixtures KI–KX (X = F, Cl, Br), the experimental concentration dependences of ᵡT during the transition from bromide ion to fluoride ion are characterized by an increasing deviation from additivity. It is shown, that even now for the binary mixture KI–KBr, the calculated concentration dependence ᵡT has a pronounced nonlinear dependence. At the same time, the maximum differences between the calculated and experimental values of ᵡT are observed for the KI–KF binary mixture of equimolar composition and are about 34%.

全文:

受限制的访问

作者简介

M. Kobelev

Institute of high-temperature electrochemistry Ural branch of RAS

编辑信件的主要联系方式.
Email: m.kobelev@ihte.ru
俄罗斯联邦, Yekaterinburg

参考

  1. Porter T., Vaka M., Steenblik P., Corte D. Computational methods to simulate molten salt thermophysical properties // Commun. Chem. 2022, 5. P. 69.
  2. Yang H., Gallagher R., Chartrand P., Gheribi A.E. // Sol. Energy. 2023. 256. P. 158–178. https://doi.org/10.1016/j.solener.2023.04.009
  3. Galashev A.Y., Abramova K.A., Vorob’ev A.S. et al. // Electrochemical Materials and Technologies. 2023. 2. № 3. P. 20232017. https://doi.org/10.15826/elmattech.2023.2.017
  4. Shishido H., Yusa N., Hashizume H. et al. Thermal design investigation for a FLiNaBe blanket system // Fusion Sci. Tech. 2017. 72. № 3. P. 382–388.
  5. Sooby E., Baty A., Benes O., McIntyre P., Pogue N., Salanne M., Sattarov A. // J. Nucl. Mater. 2013. 440. № 1-3. P. 298–303. https://doi.org/10.1016/j.jnucmat.2013.04.004
  6. Минченко В.И., Степанов В.П. Ионные расплавы: упругие и калорические свойства. Екатеринбург: УрО РАН, 2008.
  7. Fumi F.G., Tosi M.P. // J. Phys. Chem. Solids. 1964. 25. P. 31–43. https://doi.org/10.1016/0022-3697(64)90159-3
  8. Ribeiro M.C.C. // J. Phys. Chem. B. 2003. 107. P. 4392–4402. https://doi.org/10.1021/jp027261a
  9. Wang J., Sun Z., Lu G., Yu J. // J. Phys. Chem. B 2014. 118. № 34. P. 10196–10206. https://doi.org/10.1021/jp5050332
  10. Frenkel D and Smit B Understanding molecular simulation: From algorithms to applications. Academic Press, 2002.
  11. Sangster M., Dixon M. // Adv. Phys. 1976. 25. P. 247–342. https://doi.org/10.1080/00018737600101392
  12. Larsen B., Forland T., Singer K. // Mol. Phys. 1973. 26. № 6. P. 1521–1532. https://doi.org/10.1080/00268977300102671
  13. Mayer J.E. // J. Chem. Phys. 1933. 1. № 4. P. 270–279. https://doi.org/10.1063/1.1749283
  14. Allen M., Tildesley D. Computer simulations of liquids. New York: Oxford University Press, 1987.
  15. Smirnov M.V., Stepanov V.P. // Electr. Acta. 1982. 27. № 11. P. 1551–1563. https://doi.org/10.1016/0013-4686(82)80082-0
  16. Nosé S. // Prog. Theor. Phys. Supp. 1991. 103. P. 1–46. https://doi.org/10.1143/PTPS.103.1
  17. Refson K. // Comp. Phys. Commun. 2000. № 3. P. 310–329. https://doi.org/10.1016/S0010-4655(99)00496-8
  18. Bockris J.O.M., Richards N.E. // Proc. Roy. Soc. A. 1957. 241. № 1224. P. 44–66. https://doi.org/10.1098/rspa.1957.0112

补充文件

附件文件
动作
1. JATS XML
下载
2. Fig.1

下载 (34KB)
索引源数据
3. 2a

下载 (37KB)
索引源数据
4. 2b

下载 (38KB)
索引源数据
5. Fig.2

下载 (38KB)
索引源数据

版权所有 © Russian Academy of Sciences, 2024

##common.cookie##