Stability of the magnetic subsystem of 2D magnets from the method of the crystal orbital hamilton population

Capa

Citar

Texto integral

Acesso aberto Acesso aberto
Acesso é fechado Acesso está concedido
Acesso é fechado Somente assinantes

Resumo

The densities of electronic states in quasi-two-dimensional vanadium nitrides have been studied using density functional theory and the method of the crystal orbital Hamilton population. The contribution of various orbital pairs and their influence on the stability of the magnetic subsystem of these compounds has been analyzed using the crystal orbital Hamilton population (COHP) algorithm. The calculation results and their analysis suggest that the formation of long-range magnetic order plays a role in the structural stabilization of magnetic quasi-two-dimensional transition metal nitrides. Comparing –COHP curves for different vanadium nitrides shows that the nitrogen stoichiometry in VxNy compounds affects the electronic properties and the nature of the chemical bond during the transition to the ferromagnetic state. Calculation data and total energies prove the structure-stabilizing effect of long-range magnetic ordering in quasi-two-dimensional vanadium-nitrogen compounds.

Sobre autores

L. Kushchuk

Bauman Moscow State Technical University

Email: karec1@gmail.com
Rússia, Moscow

D. Veretimus

Bauman Moscow State Technical University

Email: karec1@gmail.com
Rússia, Moscow

P. Lega

Bauman Moscow State Technical University; Kotelnikov Institute of Radio Engineering and Electronics RAS; RUDN University

Email: karec1@gmail.com
Rússia, Moscow; Moscow; Moscow

A. Antonenkova

RUDN University

Email: karec1@gmail.com
Rússia, Moscow

A. Kartsev

Computing Center Far Eastern Branch RAS; Kotelnikov Institute of Radio Engineering and Electronics RAS; RUDN University

Autor responsável pela correspondência
Email: karec1@gmail.com
Rússia, Khabarovsk; Moscow; Moscow

Bibliografia

  1. Mahapatra P.L., Tromer R., Pandey P. et al. // Small. 2022. V. 18. № 27. P. 2201667. https://doi.org/10.1002/smll.202201667
  2. Ghosh S.K., Mandal D. // 2D Nanomaterials for Energy Applications: Graphene and Beyond. Elsevier, 2020. P. 1. https://doi.org/10.1016/C2018-0-00152-8
  3. Cortie D.L., Causer G.L., Rule K.C. et al. // AdV. Funct. Mater. 2020. V. 30. № 18. P. 1901414. https://doi.org/10.1002/adfm.201901414
  4. Coronado E. // Nat. Rev. Mater. 2020. V. 5. P. 87. https://doi.org/10.1038/s41578-019-0146-8
  5. Pramanik A., Kumbhakar P., Negedu S.D., Tiwary C.S. // Opt. Lett. 2022. V. 47. № 19.P. 4965. https://opg.optica.org/ol/abstract.cfm?URI=ol-47- 19-4965
  6. Moradi Z., Vaezzadeh M., Saeidi M. // Phys. Chem. C. 2023. V. 127. № 25. P. 12243. https://doi.org/10.1021/acs.jpcc.3c01954
  7. Park J.G. // J. Phys.: Condens. Matter. 2016. V. 28. № 30. P. 301001. https://doi.org/10.1088/0953-8984/28/30/301001
  8. Negedu S.D., Karstev A., Palit M., Pandey P., Emmanuel O.F., Roy A.K., Das G.P., Ajayan M.P. Kumbhakar P., Tiwary C.S.// J. Phys. Chem. C. 2022. V. 126. № 30. P. 12545. https://doi.org/10.1021/acs.jpcc.2c02102
  9. Mazaev P.V., Koledov V.V., Shavrov V.G. et al. // J. Commun. Technol. Electron. 2016. V. 61. P. 630. https://doi.org/10.1134/S1064226916060176
  10. Lega P., Kuchin D.S., Koledov V.V., Sampath V., Zhikharev A.M., Shavrov V.G. // Mater. Sci. Forum. 2016. V. 845. P. 142. http://dx.doi.org/10.4028/www.scientific.net/MSF.845.142
  11. Giannozzi P., Andreussi O., Brumme T. et al. // J. Phys.: Condens. Matter. 2017. V. 29. № 46. P. 465901. https://doi.org/10.1088/1361-648X/aa8f79
  12. Sihi A., Pandey S.K. // Eur. Phys. J. B. 2020. V. 93. P. 9. https://doi.org/10.1140/epjb/e2019-100500-8
  13. Şaşıoğlu E., Friedrich C., Blügel S. // Phys. Rev. B. 2011. V. 83. № 12. P. 121101(R). https://doi.org/10.1103/PhysRevB.83.121101
  14. Kartsev A., Feya O.D., Bondarenko N., Kvashnin A.G. // Phys. Chem. Chem. Phys. 2019. V. 21. № 9. P. 5262. https://doi.org/10.1039/C8CP07165A
  15. Kartsev A., Malkovsky S., Chibisov A. // Nanomaterials. 2021. V. 11. № 11. P. 2967. https://doi.org/10.3390/nano11112967
  16. Prandini G., Marrazzo A., Castelli I.E., Mounet N., Marzari N. // npj Comput. Mater. 2018. V. 4. № 1. P. 72. https://doi.org/10.1038/s41524-018-0127-2
  17. Grimme S., Antony J., Ehrlich S., Krieg H. // J. Chem. Phys. 2010. V. 132. № 15. P. 154104. https://doi.org/10.1063/1.3382344
  18. Maintz S., Deringer V.L., Tchougréeff A.L., Dronskowski R. // J. Comput. Chem. 2016. V. 37. № 11. P. 1030. https://doi.org/10.1002/jcc.24300
  19. Landrum G.A., Dronskowski R. // Ang. Chem. Int. Ed. 2000. V. 39. № 9. P. 1560. https://doi.org/10.1002/(SICI)1521-3773 (20000502)39:9%3C1560::AID-ANIE1560%3E3.0. CO;2-T
  20. Сорокин А.А., Макогонов С.В., Королев С.П. // Научно-техническая информация. Сер. 1. Организация и методика информационной работы. 2017. № 12. С. 14.

Arquivos suplementares

Arquivos suplementares
Ação
1. JATS XML

Declaração de direitos autorais © Russian Academy of Sciences, 2024