Skip to main content
Log in

A computational study on the potential application of yne-BN monolayer for selective detection of NO and CO gases

  • Original Paper
  • Published:
Monatshefte für Chemie - Chemical Monthly Aims and scope Submit manuscript

Abstract

We computationally investigated the reactivity and sensitivity of a graphyne-like boron nitride nanosheet (yne-BN) toward the CO and NO gases. Our calculations showed that the CO and NO gases mainly adsorb on the boron atom of –B=N– linkages, releasing energies of 51.8 and 39.7 kJ/mol, respectively. The yne-BN electronic properties did not sensibly change by the CO gas adsorption, but the NO gas largely stabilized its LUMO level and significantly increased the electrical conductivity. This is explained based on the different electronic structure of the CO and NO molecules. Also, by the NO adsorption, the work function (Φ) of yne-BN was considerably reduced from 5.59 to 4.70 eV, changing the field emission electron current which can help to detect this gas. A short recovery time about 0.9 μs was predicted for the NO desorption. By increasing the NO concentration, the HOMO–LUMO gap of yne-BN more decreases, more increasing the electrical conductivity. We concluded that the yne-BN sheet is a promising electronic or Φ-type sensor for the selective detection of NO gas at the presence of CO gas.

Graphic abstract

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

Access this article

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

Instant access to the full article PDF.

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

Similar content being viewed by others

References

  1. Lee D-D, Lee D-S (2001) IEEE Sens J 1:214

    CAS  Google Scholar 

  2. Yamazoe N, Miura N (1994) Sens Actuators B Chem 20:95

    CAS  Google Scholar 

  3. Yamaura H, Tamaki J, Moriya K, Miura N, Yamazoe N (1997) J Electrochem Soc 144:L158

    CAS  Google Scholar 

  4. Zhi M, Koneru A, Yang F, Manivannan A, Li J, Wu N (2012) Nanotechnology 23:305501

    PubMed  Google Scholar 

  5. Yan H, Liu C-C (1994) Sens Actuators B Chem 17:165

    CAS  Google Scholar 

  6. Babanezhad E, Beheshti A (2018) Chem Rev Lett 1:82

    Google Scholar 

  7. Rostamoghli R, Vakili M, Banaei A, Pourbashir E, Jalalierad K (2018) Chem Rev Lett 1:31

    Google Scholar 

  8. Hartmann G, Lee M, Hwang GS (2019) Inorg Chem Commun 106:135

    CAS  Google Scholar 

  9. Baei MT, Ahmadi Peyghan A, Moghimi M (2012) Monatsh Chem 143:1463

    CAS  Google Scholar 

  10. Peyghan AA, Aslanzadeh SA, Samiei A (2014) Monatsh Chem 145:1083

    CAS  Google Scholar 

  11. Kaewruksa B, Wanbayor R, Ruangpornvisuti V (2012) J Mol Struct 1012:50

    CAS  Google Scholar 

  12. Dutta A, Pradhan AK, Qi F, Mondal P (2020) Monatsh Chem 151:159

    CAS  Google Scholar 

  13. Hellgren N, Berlind T, Gueorguiev GK, Johansson MP, Stafström S, Hultman L (2004) Mater Sci Eng B 113:242

    Google Scholar 

  14. Li D, Kaner RB (2008) Science 320:1170

    CAS  PubMed  Google Scholar 

  15. Khaleghi Abbasabadi M, Rashidi A, Safaei-Ghomi J, Khodabakhshi S, Rahighi R (2015) J Sulfur Chem 36:660

    CAS  Google Scholar 

  16. Shokuhi Rad A, Esfahanian M, Maleki S, Gharati G (2016) J Sulfur Chem 37:176

    CAS  Google Scholar 

  17. Krishnaveni K, Subadevi R, Sivakumar M, Raja M, Prem Kumar T (2019) J Sulfur Chem 40:377

    CAS  Google Scholar 

  18. dos Santos RB, Rivelino R, Mota FdB, Gueorguiev GK (2011) Phys Rev B 84:075417

    Google Scholar 

  19. Gharibzadeh F, Gohari S, Nejati K, Hashemzadeh B, Mohammadiyan S (2018) Chem Rev Lett 1:16

    Google Scholar 

  20. Kamel M, Morsali A, Raissi H, Mohammadifard K (2020) Chem Rev Lett 3:23

    Google Scholar 

  21. Cranford SW, Buehler MJ (2011) Carbon 49:411122

    Google Scholar 

  22. Narita N, Nagai S, Suzuki S, Nakao K (2000) Phys Rev B 62:11146

    CAS  Google Scholar 

  23. Liang B, Bai H, Huang Y (2017) Comput Theoret Chem 1115:261

    CAS  Google Scholar 

  24. Yang Z, Zhang Y, Guo M, Yun J (2019) Comput Mater Sci 160:197

    CAS  Google Scholar 

  25. Bhattacharya B, Singh NB, Sarkar U (2015) Int J Quantum Chem 115:820

    CAS  Google Scholar 

  26. Chen X, Qiao Q, An L, Xia D (2015) J Phys Chem C 119:11493

    CAS  Google Scholar 

  27. Asadpour M, Malakpour S, Faghihnasiri M, Taghipour B (2015) Solid State Commun 212:46

    CAS  Google Scholar 

  28. Zhang Y, Yun J, Wang K, Chen X, Yang Z, Zhang Z, Yan J, Zhao W (2017) Comput Mater Sci 136:12

    CAS  Google Scholar 

  29. Wei R, Jameh-Bozorghi S (2019) Mol Phys. https://doi.org/10.1080/00268976.2019.1691748

    Article  Google Scholar 

  30. Omidvar A, Mohajeri A (2015) Mol Phys 113:3900

    CAS  Google Scholar 

  31. Beheshtian J, Peyghan AA, Bagheri Z (2012) Comput Mater Sci 62:71

    CAS  Google Scholar 

  32. El-Barbary A, Eid KM, Kamel M, Taha H, Ismail G (2015) J Surf Eng Mater Adv Technol 5:154

    CAS  Google Scholar 

  33. Peyghan AA, Hadipour N, Bagheri Z (2013) J Phys Chem C 117:2427

    Google Scholar 

  34. Eslami M, Vahabi V, Peyghan AA (2016) Phys E 76:6

    CAS  Google Scholar 

  35. Samadizadeh M, Peyghan AA, Rastegar SF (2015) Chin Chem Lett 26:1042

    CAS  Google Scholar 

  36. Baikie I, Mackenzie S, Estrup P, Meyer J (1991) Rev Sci Instrum 62:1326

    CAS  Google Scholar 

  37. Stegmeier S, Fleischer M, Hauptmann P (2010) Thermally activated platinum as VOC sensing material for work function type gas sensors. Sens Actuators B Chem 144:418–424

    CAS  Google Scholar 

  38. Richardson O (1924) Phys Rev 23:153

    CAS  Google Scholar 

  39. Schmidt MW, Baldridge KK, Boatz JA, Elbert ST, Gordon MS, Jensen JH, Koseki S, Matsunaga N, Nguyen KA, Su S, Windus TL, Dupuis M, Montgomery JA Jr (1993) J Comp Chem 14:1347

    CAS  Google Scholar 

  40. Grimme S (2004) J Comput Chem 25:1463

    CAS  Google Scholar 

  41. Mohammadi S, Musavi M, Abdollahzadeh F, Babadoust S, Hosseinian A (2018) Chem Rev Lett 1:49

    Google Scholar 

  42. Beheshtian J, Peyghan AA, Bagheri Z (2012) Sens Actuators B Chem 171:846

    Google Scholar 

  43. Beheshtian J, Peyghan AA, Tabar MB, Bagheri Z (2013) Appl Surf Sci 266:182

    CAS  Google Scholar 

  44. Delchev VB, Mikosch H (2001) Monatsh Chem 132:223

    CAS  Google Scholar 

  45. Radenković S, Antić M, Đurđević J, Jeremić S (2014) Monatsh Chem 145:281

    Google Scholar 

  46. El-Mahdy AM (2016) Appl Surf Sci 383:353

    CAS  Google Scholar 

  47. Boys SF, Bernardi F (1970) Mol Phys 19:553

    CAS  Google Scholar 

  48. O’Boyle N, Tenderholt A, Langner K (2008) J Comput Chem 29:839

    PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ma Yinfei.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yinfei, M., Li, W. & Hamreh, S. A computational study on the potential application of yne-BN monolayer for selective detection of NO and CO gases. Monatsh Chem 151, 1039–1047 (2020). https://doi.org/10.1007/s00706-020-02642-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00706-020-02642-1

Keywords

Navigation