B. Balbashio1, A.A. Skrylev2, D.V. Shestakov3, L.M. Vinogradova4, I.S. Belokon5, A.V. Nezhdanov6, A.I. Mashin7

1–7 Nizhny Novgorod State University named after N.I. Lobachevsky (Nizhny Novgorod, Russia)
1 bbalbasi@gmail.com, 2 skrylev.lexa@mail.ru, 3 danil.shestakov@unn.ru, 4 lidiya.vinogradova@unn.ru, 5belocon.11.do@gmail.com, 6 nezhdanov@phys.unn.ru, 7 mashin@unn.ru

In this work, the structural and electronic properties of ZnSnN2 were investigated using density functional theory (DFT). The electronic structure calculations were performed with the Quantum ESPRESSO package. The optimized lattice parameters are in good agreement with the available literature data. The band structure and projected density of states (PDOS) were analyzed using the PBE functional, while the electronic structure was further refined using wave functions obtained from the PBE functional, followed by an HSE-style correction. With this correction, a direct band gap of 1.60 eV was obtained, which is in good agreement with experimental results. The results indicate that ZnSnN2 is a direct band gap semiconductor with an energy gap located near the visible range.

Balbashio B., Skrylev A.A., Shestakov D.V., Vinogradova L.M., Belokon I.S., Nezhdanov A.V., Mashin A.I. Study of the electronic properties of the ternary compound ZnSnN2 using density functional theory // Nonlinear World. 2026. V. 24. № 3. P. 29–40. DOI: https:// doi.org/10.18127/ j20700970-202603-04

1. Parr R.G., Yang W. Density-Functional Theory of Atoms and Molecules. Oxford University Press, 1989.
2. Thomas L.H. The calculation of atomic fields. Math. Proc. Cambridge Philos. Soc. 1927. V. 23(5). P. 542–548.
3. Hohenberg P., Kohn W. Inhomogeneous Electron Gas. Phys. Rev. 1964. V. 136(3B). P. B864–B871.
4. Kohn W., Sham L.J. Self-Consistent Equations Including Exchange and Correlation Effects. Phys. Rev. 1965. V. 140(4A). P. A1133–A1138.
5. Giannozzi P. et al. QUANTUM ESPRESSO: a modular and open-source software project for quantum simulations of materials . J. Phys.: Condens. Matter. 2009. V. 21(39). 395502. DOI: 10.1088/0953-8984/21/39/395502.
6. Giannozzi P. et al. Advanced capabilities for materials modelling with Quantum ESPRESSO. J. Phys.: Condens. Matter. 2017. V. 29(46). 465901. DOI: 10.1088/1361-648X/aa8f79.
7. Soler J.M. et al. The SIESTA method for ab initio order-N materials simulation. J. Phys.: Condens. Matter. 2002. V. 14(11). P. 2745–2779.
8. Perdew J.P. et al. Generalized Gradient Approximation Made Simple. Phys. Rev. Lett. 1996. V. 77(18). P. 3865–3868.
9. Dirac P.A.M. Quantum Mechanics of Many-Electron Systems. Proc. Roy. Soc. A. 1929. V. 123(792). P. 714–733.
10. de Broglie L. Recherches sur la théorie des quanta. Doctoral Thesis. Université de Paris, 1924.
11. Schrödinger E. Quantisierung als Eigenwertproblem. Ann. Phys. 1926. V. 79(4). P. 361–376.
12. Sze S.M., Ng K.K. Physics of Semiconductor Devices, 3rd ed., Wiley, 2007.
13. Yu P.Y., Cardona M. Fundamentals of Semiconductors: Physics and Materials Properties, 4th ed., Springer, 2010.
14. Ashcroft N.W., Mermin N.D. Solid State Physics. Harcourt. Brace & World, 1976.
15. Falkovsky L.A. (2022). Features of interband absorption in narrow-gap semiconductors // arXiv:0802.2007. 2008.
16. Dal Corso A. Pseudopotentials periodic table: From H to Pu. Comput. Mater. Sci. 2014. V. 95. P. 337–350. DOI: 10.1016/j.commatsci.2014.07.043.
17. Martin R.M. Electronic Structure: Basic Theory and Practical Methods. Cambridge University Press. 2004.
18. Payne M.C. et al. Iterative minimization techniques for ab initio total-energy calculations: molecular dynamics and conjugate gradients. Rev. Mod. Phys. 1992. V. 64(4). P. 1045–1097.
19. Hamann D.R., Schlüter M., Chiang C. Norm-Conserving Pseudopotentials. Phys. Rev. Lett. 1979. V. 43(20). P. 1494–1497.
20. Blöchl P.E. Projector Augmented-Wave Method. Phys. Rev. B. 1994. V. 50. P. 17953.
21. Wang T., Ni C., Janotti A. Band alignment and p-type doping of ZnSnN2. Phys. Rev. B. 2017. V. 95. 205205. DOI: 10.1103/PhysRevB.95.205205.
22. Materials Project. Materials Data on ZnSnN₂. OSTI Dataset. 2020. DOI: 10.17188/1750980.
23. Senabulya N. et al. Stabilization of orthorhombic phase in single-crystal ZnSnN2 films. AIP Adv. 2016. V. 6(7). 075019. DOI:10.1063/1.4960109.
24. Quayle P.C. et al. Synthesis, lattice structure, and band gap of ZnSnN2. MRS Commun. 2013. V. 3(3). P. 135–138. DOI: 10.1557/mrc.2013.19.
25. Fioretti A.N. et al. Combinatorial insights into doping control and transport properties of zinc tin nitride // arXiv:1504.01819, 2015.
26. Skrylev A.A. et al. Electrophysical properties of cation-disordered ZnSnN2 films: temperature dependences and thermal annealing. Physica B. 2025. V. 721. 418058.
27. Skrylev A.A. et al. Raman spectroscopy study of disorder in cation sublattice of nonstoichiometric and annealed ZnSnN2. Opt. Mater. 2024. V. 156. 116035.
28. Nezhdanov A.V. et al. Mixed phase ZnSnN₂ thin films for solar energy applications: Insight into optical and electrical properties.  Opt. Mater. 2023. V. 144. 114335.
29. BURAI 1.3. A GUI of Quantum ESPRESSO. URL: https://www.burai.org (data obrashchenija: 01.01.2025).
30. Momma K., Izumi F. VESTA 3 for visualization of crystal, volumetric and morphology data. URL: https://jp-minerals.org/vesta/en/ (data obrashchenija: 01.01.2025).
31. Materials Project. Materials Data on ZnSnN2 (mp‑1029469). Dataset. United States: Department of Energy, 2020. DOI: 10.17188/1750980. URL: https://www.osti.gov/dataexplorer/biblio/dataset/1750980 (data obrashchenija: 24.10.2025).
32. Murnaghan F.D. The Compressibility of Media under Extreme Pressures. Proc. Natl. Acad. Sci. 1944. V. 30(9). P. 244–247. DOI: 10.1073/pnas.30.9.244.
33. Punya A., Lambrecht W.R.L., van Schilfgaarde M. Quasiparticle band structure of Zn-IV-N2 compounds. Phys. Rev. B. 2011. V. 84. 165204.
34. Python Software Foundation. Python Language Reference. URL: https://www.python.org (data obrashchenija: 01.01.2025).
35. Deng F. et al. Determination of the Basic Optical Parameters of ZnSnN₂. Opt. Lett. 2015. V. 40(7). P. 1282–1285. DOI: 10.1364/OL.40.001282.
36. Balbashio B. i dr. Analiz kristallicheskoj struktury ZnSnN₂ metodami rentgenovskoj difrakcii. Nanotekhnologii: razrabotka, primenenie – XXI vek. 2025. T. 17. № 3. S. 26–33 (In Russian).
37. Ong S.P. et al. Python Materials Genomics (pymatgen): A robust, open-source Python library for materials analysis. Comput. Mater. Sci. 2013. V. 68. P. 314–319. DOI: 10.1016/j.commatsci.2012.10.028.