Skip to main content

Advertisement

Log in

Polyfuran-based chemical sensors: reactivity analysis via Fukui indexes and reactive molecular dynamics

  • Article
  • Published:
MRS Advances Aims and scope Submit manuscript

Abstract

In the present study we employ electronic structure calculations (based on Density Functional Theory -DFT approach) and Fully Atomistic Reactive Molecular Dynamics (FARMD) simulations (based on ReaxFF reactive force field) to evaluate the reactivity of branched polyfuran (PF) derivatives and identify promising systems for chemical sensing. Condensed-to-atoms Fukui indexes (CAFI) were employed to identify the most reactive sites on the oligomers structure. The chemical sensing abilities of the most promising systems were evaluated via FARMD simulations in the presence of distinct gaseous compounds. The results indicate the derivatives PF-CCH and PF-NO2 (i.e. CCH and NO2 as side groups) as the most promising systems for chemical sensor applications, presenting higher reactivity on the most accessible sites. An interesting correspondence between DFT and MD results was also identified, suggesting the plausibility of using CAFI parameters for the identification of improved materials for chemical sensors.

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

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. X. Liu, S. Cheng, H. Liu, et al., Sensors 12, 9635 (2012).

    Article  Google Scholar 

  2. L. Fortuna, Soft sensors for monitoring and control of industrial processes, 1st ed., Springer: London, 2007.

    Google Scholar 

  3. M. Hrubovčáková, E. Dudrová, E. Hryha, et al., Adv. Mater. Sci. Eng. 2013, 1 (2013).

    Article  Google Scholar 

  4. P. Villoria-Sáez, V. W. Y. Tam, would like to thank M. del Río Merino, et al., J. Clean. Prod. 127, 49 (2016).

    Article  Google Scholar 

  5. H. Bai, G. Shi, Sensors 7, 267 (2007).

    Article  CAS  Google Scholar 

  6. H. Yoon, Nanomaterials 3, 524 (2013).

    Article  CAS  Google Scholar 

  7. G. E. Zaikov, Interaction of polymers with polluted atmosphere nitrogen oxides, 1st ed., iSmithers: Shawbury, 2009.

    Google Scholar 

  8. W. Zeng, M. Q. Zhang, M. Z. Rong, Q. Zheng, Sens. Actuators B Chem. 124, 118 (2007).

    Article  CAS  Google Scholar 

  9. S. Sharma, N. Zamoshchik, M. Bendikov, Isr. J. Chem. 54, 712 (2014).

    Article  CAS  Google Scholar 

  10. A. Gandini, Prog. Polym. Sci. 22, 1203 (1997).

    Article  CAS  Google Scholar 

  11. F. A. Carey, R. J. Sundberg, Advanced Organic Chemistry: Part A: Structure and Mechanisms, 1st ed. Springer Science & Business Media, 2007.

    Google Scholar 

  12. E. F. Oliveira, F. C. Lavarda, Polym. Eng. Sci. 56, 479 (2016).

    Article  CAS  Google Scholar 

  13. E. F. Oliveira, F. C. Lavarda, Mater. Chem. Phys. 148, 923 (2014).

    Article  CAS  Google Scholar 

  14. J. J. P. Stewart, J. Mol. Model. 13, 1173 (2007).

    Article  CAS  Google Scholar 

  15. J. J. P. Stewart, MOPAC2016. Stewart Computational Chemistry, Colorado Springs, CO, USA, 2018

    Google Scholar 

  16. A. D. Becke, J. Chem. Phys. 98, 5648 (1993).

    Article  CAS  Google Scholar 

  17. M. J. Frisch, G. W. Trucks, H. B. Schlegel, et al., Gaussian 09. Gaussian, Inc., Wallingford, CT, 2009.

    Google Scholar 

  18. W. Yang, W. J Mortier, J. Am. Chem. Soc. 108, 5708 (1986).

    Article  CAS  Google Scholar 

  19. A. Batagin-Neto, E.S. Bronze-Uhle, M. Vismara, et al., Curr. Phys. Chem. 3, 431 (2013).

    Article  CAS  Google Scholar 

  20. E. S. Bronze-Uhle, A. Batagin-Neto, F. C. Lavarda, C. F. O. Graeff, J. Appl. Phys. 110, 073510 (2011).

    Google Scholar 

  21. I. Cesarino, R. P. Simões, F. C. Lavarda, A. Batagin-Neto, Electrochimica Acta 192, 8 (2016).

    CAS  Google Scholar 

  22. L. M. Martins, S. de Faria Vieira, G. B. Baldacim, et al., Dyes Pigments 148, 81 (2018).

    CAS  Google Scholar 

  23. L. O. Mandú, A. Batagin-Neto, J. Mol. Model 24, 157 (2018).

    Google Scholar 

  24. R. A. Maia, G. Ventorim, A. Batagin-Neto, J. Mol. Model. 25, 228 (2019).

    Article  Google Scholar 

  25. J. do Amaral Rodrigues, A. R. de Araújo, N. A. Pitombeira, et al., Int. J. Biol. Macromol. 128, 965 (2019).

    Article  Google Scholar 

  26. A. Rodrigues de Araújo, B. Iles, K. de Melo Nogueira, et al., Mart. J. Ethnopharmacol. 240, 111941 (2019).

    Article  Google Scholar 

  27. R. K. Roy, S. Pal, K. Hirao, J. Chem. Phys. 110, 8236 (1999).

    Article  CAS  Google Scholar 

  28. F. De Proft, C. Van Alsenoy, A. Peeters A, et al., J. Comput. Chem. 23, 1198 (2002).

    Article  Google Scholar 

  29. A. R. Leach, Molecular Modelling: Principles and Applications, 1st ed. Prentice Hall, 2001

    Google Scholar 

  30. A. C. T. van Duin, S. Dasgupta, F. Lorant, W. A. Goddard, J. Phys. Chem. A 105, 9396 (2001)

    Article  Google Scholar 

  31. D. Fantauzzi, J. E. Mueller, L. Sabo, et al., Chem. Phys. Chem. 16, 2797 (2015).

    Article  CAS  Google Scholar 

  32. S. J. Plimpton, Comput. Phys. 117, 1 (1995).

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lascane, L.G., Oliveira, E.F. & Batagin-Neto, A. Polyfuran-based chemical sensors: reactivity analysis via Fukui indexes and reactive molecular dynamics. MRS Advances 5, 497–503 (2020). https://doi.org/10.1557/adv.2020.203

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1557/adv.2020.203

Navigation