Skip to main content
SpringerLink
Log in

Synthesis, Investigation and Neural Network Modeling of the Properties of Sol-Gel ITO/ZnO and ITO/ZnO:Mg Structures

  • Published:
Journal of Contemporary Physics (Armenian Academy of Sciences) Aims and scope

Abstract

The ITO/ZnO and ITO/ZnO:Mg bilayer structures were fabricated by the sol-gel method and their structural and photoelectric properties were experimentally studied. It is shown that, compared with ZnO and ZnO:Mg films without an ITO sublayer, the morphology changes noticeably and the band gap decreases. The I–V characteristics of obtained structures were analyzed in the dark and under the influence of optical radiation of different wavelengths. Using artificial neural networks, their spectral photosensitivity was modeled.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.
Fig. 7.
Fig. 8.

REFERENCES

  1. Gultepe, O. and Atay, F., J. Mater. Sci: Mater. Electron., 2022, vol. 33, p. 15039.

    Google Scholar 

  2. Ayvazyan, G.Y., Katkov, M.V. Lebedev, M.S., Shayapov, V.R., Afonin, M.Yu., Petukhova, D.E., Yushina, I.V., Maksimovskii, E.A., and Aghabekyan, A.V., J. Contemp. Phys. (Armenian Acad. Sci.), 2021, vol. 56, p. 240.

  3. Cao, J., Wu, B., Chen, R., Wu, Y., Hui, Y., Mao, B.W., and Zheng, N., Adv. Mater., 2018, vol. 30, p. 1705596.

    Article  Google Scholar 

  4. Ayvazyan, G.Y., Kovalenko, D.L., Lebedev, M.S., Matevosyan, L.A., and Semchenko, A.V., J. Contemp. Phys. (Armenian Acad. Sci.), 2022, vol. 57, p. 274.

    Google Scholar 

  5. Xu, Q., Cheng, L., Meng, L., Wang, Z., Bai, S., Tian, X., Jia, X., and Qin, Y., ACS Appl. Mater. Interfaces, 2019, vol. 11, p. 26127.

    Article  Google Scholar 

  6. Kang, Y., Yu, F., Zhang, L., Wang, W., Chen, L., and Li, Y., Solid State Ionics, 2021, vol. 360, p. 115544.

    Article  Google Scholar 

  7. Hou, Y., Mei, Z., Liu, Z., Liang, H., Gu, C., and Du, X., Thin Solid Films, 2017, vol. 634, p. 165.

    Article  ADS  Google Scholar 

  8. He, W., Feng, Y., Hu, Z-D., Balmakou, A., Khakhomov, S., and Deng, Q., J. Wang, IEEE Sensors J., 2020, vol. 20, p. 1801.

    Article  ADS  Google Scholar 

  9. Park, G.C., Hwang, S.M., Lim, J.H., and Joo, J., Nanoscale, 2014, vol. 6, p. 1840.

    Article  ADS  Google Scholar 

  10. Sridhar, P., Sakthivel, K., and Sankaranarayana, R.K., Appl. Surf. Sci. Adv., 2023, vol. 13, p. 100382.

    Article  Google Scholar 

  11. Zheng, G., Song, J., Zhang, J., Li, J., Han, B., Meng, X., Yang, F., Zhao, Y., and Wang, Y., Mater. Sci. Semicond. Process., 2020, vol. 112. P. 105016.

    Article  Google Scholar 

  12. Othman, Z.J. and Matoussi, A., J. Alloys Comp., 2016, vol. 671, p. 366.

    Article  Google Scholar 

  13. Huang, K., Tang, Z., Zhang, L., Yu, J., Lv, J., and Liu, X., Appl. Surf. Sci., 2012, vol. 258, p. 3710.

    Article  ADS  Google Scholar 

  14. Guo, D., Sato, K., Hibino, S., Takeuchi, T., Bessho, H., and Kato, K., J. Mater. Sci., 2014, vol. 49, p. 4722.

    Article  ADS  Google Scholar 

  15. Rouchdi, M., Salmani, E., Fares, B., Hassanain, N., and Mzerd, A., Results in Phys., 2017, vol. 7, p. 620.

    Article  ADS  Google Scholar 

  16. Kek, R., Ong, G.L., Yap, S.L., Lim, L.K., Koh, S.F., Nee, C.H., Tou, T.Y., and Yap, S.S., Mater. Sci. Semicond. Process., 2022, vol. 145, p. 106636.

    Article  Google Scholar 

  17. Makhlouf, H., Karam, C., Lamouchi, A., Tingry, S., Miele, P., Habchi, R., Chtourou, R., and Bechelany, M., Appl. Surf. Sci., 2018, vol. 444, p. 253.

    Article  ADS  Google Scholar 

  18. Rosa, A.M., da Silva, E.P., Amorim, E., Chaves, M., Catto, C., Lisboa-Filho, P.N., Bortoleto, J.R.R., J. Phys. Conf. Ser., 2012, vol. 370, p. 012020.

    Article  Google Scholar 

  19. Sidsky, V.V., Malyutina-Bronskaya, V.V., Soroka, S.A., Danilchenko, K.D., Semchenko, A.V., and Pilipenko, V.A., Lecture Notes in Networks and Syst., 2022, vol. 422, p. 227.

    Article  Google Scholar 

  20. Malik, G., Mourya, S., Jaiswal, J., and Chandra, R., Mater. Sci. Semicond. Process., 2019, vol. 100, p. 200.

    Article  Google Scholar 

  21. Yang, W., Liu, J., Guan, Z., Liu, Z., Chen, B., Zhao, L., Li, Y., Cao, X., He, X., Zhang, C., Zeng, Q., and Fu, Y., Ceramics Internat., 2020, vol. 46, p. 6605.

    Article  Google Scholar 

  22. Ţălu, Ş., Boudour, S., Bouchama, I., Astinchap, B., Ghanbaripour, H., Akhtar, M.S., and Zahra, S., Microscopy Research and Techn., 2022, vol. 85, p. 1213.

    Article  Google Scholar 

  23. Bhari, B.Z., Rahman, K.S., Chelvanathan, P., and Ibrahim, M.A., Mater. Let., 2022, vol. 339, p. 134097.

    Article  Google Scholar 

  24. Young, S.-L., Kao, M.-C., Chen, H.-Z., Shih, N.-F., Kung, C.-Y., and Chen, C.-H., J. Nanomater., 2015, vol. 2015, p. 1.

    Article  ADS  Google Scholar 

  25. Dobrozhan, O., Diachenko, O., Kolesnyk, M., Stepanenko, A., Vorobiov, S., Baláž, P., Plotnikov, S., and Opanasyuk, A., Mater. Sci. Semicond. Process., 2019, vol. 102, p. 104595.

    Article  Google Scholar 

  26. Vaseashta, A., Ayvazyan, G., Khudaverdyan, S., and Matevosyan, L., Phys. Status Solidi RRL, 2023, vol. 17, p. 2200482.

    Article  Google Scholar 

  27. Kawajiri, K., Tahara, K., and Uemiya, S., Resour. Environ. Sustain., 2022, vol. 7, p. 100047.

    Google Scholar 

  28. Nagpal, S., Rahul, S.V., and Bhatnagar, P.K., Eng. Res. Express, 2020, vol. 2, p. 025007.

    Article  ADS  Google Scholar 

  29. Madhi, I., Bouzid, B., Saadoun, M., and Bessaïs, B., Ceramics Internat., 2015, vol. 41, p. 6552.

    Article  Google Scholar 

  30. Ayvazyan, G., Vaseashta, A., Gasparyan, F., and Khudaverdyan, S., J. Mater Sci: Mater. Electron., 2022, vol. 33, p. 17001.

    Google Scholar 

  31. Vijayalakshmin, K., Renitta, A., and Karthick, K., Ceramics Internat., 2014, vol. 40, p. 6171.

    Article  Google Scholar 

  32. Asriyan, H.V., Shatveryan, A.A., Aroutiounian, V.M., Gasparyan, F.V., Melkonyan, S.V., and Mkhitharian, Z.H., Proc. SPIE, 2005, vol. 5846, p. 192.

    Article  ADS  Google Scholar 

  33. Chollet, F., Deep Learning with Python. New York, Manning Publications Co., 2021.

    Google Scholar 

Download references

Funding

The study was financially supported by the Science Committee of the Republic of Armenia (Project No. 21AG-2B011) and the Belarusian Republic Foundation for Fundamental Research (Projects T21ARMG-004 and T22UZB-074).

Author information

Authors and Affiliations

  1. National Polytechnic University of Armenia, Yerevan, Armenia

    G. Y. Ayvazyan

  2. Francisk Skorina Gomel State University, Gomel, Belarus

    K. D. Danilchenko, D. L. Kovalenko, A. A. Maevsky, Yu. V. Nikityuk, V. A. Prokhorenko, A. V. Semchenko, V. V. Sidsky & S. A. Khakhomov

  3. SSPA “Optics, Optoelectronics, and Laser Technology”, Minsk, Belarus

    V. V. Malyutina-Bronskaya & A. V. Nesterenok

Authors
  1. G. Y. Ayvazyan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. K. D. Danilchenko
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. D. L. Kovalenko
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. A. A. Maevsky
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yu. V. Nikityuk
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. V. A. Prokhorenko
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. A. V. Semchenko
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. V. V. Sidsky
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. S. A. Khakhomov
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. V. V. Malyutina-Bronskaya
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. A. V. Nesterenok
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to G. Y. Ayvazyan.

Ethics declarations

The authors of this work declare that they have no conflicts of interest.

Additional information

Translated by V. Musakhanyan

Publisher’s Note.

Pleiades Publishing remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ayvazyan, G.Y., Danilchenko, K.D., Kovalenko, D.L. et al. Synthesis, Investigation and Neural Network Modeling of the Properties of Sol-Gel ITO/ZnO and ITO/ZnO:Mg Structures. J. Contemp. Phys. 58, 266–273 (2023). https://doi.org/10.1134/S1068337223030064

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S1068337223030064

Keywords:

Search

Navigation