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image of Ambient-Stable Electroactive Graphene Nanoribbons: A Comprehensive Analysis of Distance, Degree, Energetics and 13C NMR Signals

Abstract

Introduction

Topological indices serve as mathematical descriptors for chemical structures, playing a crucial role in elucidating the physicochemical characteristics of compounds. Ambient-stable electroactive graphene nanoribbons are air-stable, electronically tunable and easily fabricated nanostructures, formed by the elongation of nanographene ribbon segments. This study aimed to develop precise topological formulations for three types of ambient-stable electroactive graphene nanoribbons (AEGNR) using graph-theoretical structural measures, and to evaluate their energetic properties along with their 13C NMR spectral characteristics.

Methods

The study employs the cut method, which is based on the Djoković-Winkler relation, to calculate topological indices.

Results

In this article, we evaluated selected spectral and energetic properties of AEGNR variants.

Discussion

The computed topological indices based on distance and vertex degree could provide important chemical insights into the properties of AEGNR(l).

Conclusions

We developed exact mathematical expressions for bond-additive molecular descriptors corresponding to three types of ambient-stable electroactive graphene nanoribbons (AEGNRs). An evaluation of HOMO-LUMO energy gaps was also performed for the AEGNR(l) chains.

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2025-10-28
2025-12-15

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References

  1. Ferrari A.C. Bonaccorso F. Fal’ko V. Novoselov K.S. Roche S. Bøggild P. Borini S. Koppens F.H.L. Palermo V. Pugno N. Garrido J.A. Sordan R. Bianco A. Ballerini L. Prato M. Lidorikis E. Kivioja J. Marinelli C. Ryhänen T. Morpurgo A. Coleman J.N. Nicolosi V. Colombo L. Fert A. Garcia-Hernandez M. Bachtold A. Schneider G.F. Guinea F. Dekker C. Barbone M. Sun Z. Galiotis C. Grigorenko A.N. Konstantatos G. Kis A. Katsnelson M. Vandersypen L. Loiseau A. Morandi V. Neumaier D. Treossi E. Pellegrini V. Polini M. Tredicucci A. Williams G.M. Hee Hong B. Ahn J.H. Min Kim J. Zirath H. van Wees B.J. van der Zant H. Occhipinti L. Di Matteo A. Kinloch I.A. Seyller T. Quesnel E. Feng X. Teo K. Rupesinghe N. Hakonen P. Neil S.R.T. Tannock Q. Löfwander T. Kinaret J. Science and technology roadmap for graphene, related two-dimensional crystals, and hybrid systems. Nanoscale 2015 7 11 4598 4810 10.1039/C4NR01600A 25707682
    [Google Scholar]
  2. Novoselov K.S. Geim A.K. Morozov S.V. Jiang D. Zhang Y. Dubonos S.V. Grigorieva I.V. Firsov A.A. Electric field effect in atomically thin carbon films. Science 2004 306 5696 666 669 10.1126/science.1102896 15499015
    [Google Scholar]
  3. Lin Y.M. Dimitrakopoulos C. Jenkins K.A. Farmer D.B. Chiu H.Y. Grill A. Avouris P. 100-GHz transistors from wafer-scale epitaxial graphene. Science 2010 327 5966 662 10.1126/science.1184289 20133565
    [Google Scholar]
  4. Wei D. Wu B. Guo Y. Yu G. Liu Y. Controllable chemical vapor deposition growth of few layer graphene for electronic devices. Acc. Chem. Res. 2013 46 1 106 115 10.1021/ar300103f 22809220
    [Google Scholar]
  5. Shende P. Augustine S. Prabhakar B. A review on graphene nanoribbons for advanced biomedical applications. Carbon Letters 2020 30 5 465 475 10.1007/s42823‑020‑00125‑1
    [Google Scholar]
  6. Johnson A.P. Gangadharappa H.V. Pramod K. Graphene nanoribbons: A promising nanomaterial for biomedical applications. J. Control. Release 2020 325 141 162 10.1016/j.jconrel.2020.06.034 32622962
    [Google Scholar]
  7. Bu H. Chen Y. Zou M. Yi H. Bi K. Ni Z. Atomistic simulations of mechanical properties of graphene nanoribbons. Phys. Lett. A 2009 373 37 3359 3362 10.1016/j.physleta.2009.07.048
    [Google Scholar]
  8. Liu J. Li B.W. Tan Y.Z. Giannakopoulos A. Sanchez-Sanchez C. Beljonne D. Ruffieux P. Fasel R. Feng X. Müllen K. Toward cove-edged low band gap graphene nanoribbons. J. Am. Chem. Soc. 2015 137 18 6097 6103 10.1021/jacs.5b03017 25909566
    [Google Scholar]
  9. Ivanov I. Hu Y. Osella S. Beser U. Wang H.I. Beljonne D. Narita A. Müllen K. Turchinovich D. Bonn M. Role of edge engineering in photoconductivity of graphene nanoribbons. J. Am. Chem. Soc. 2017 139 23 7982 7988 10.1021/jacs.7b03467 28525278
    [Google Scholar]
  10. Cao T. Zhao F. Louie S.G. Topological phases in graphene nanoribbons: Junction states, spin centers, and quantum spin chains. Phys. Rev. Lett. 2017 119 7 076401 10.1103/PhysRevLett.119.076401 28949674
    [Google Scholar]
  11. Narita A. Chen Z. Chen Q. Müllen K. Solution and on-surface synthesis of structurally defined graphene nanoribbons as a new family of semiconductors. Chem. Sci. (Camb.) 2019 10 4 964 975 10.1039/C8SC03780A 30774890
    [Google Scholar]
  12. Peurifoy S.R. Xu Q. May R. Gadjieva N.A. Sisto T.J. Jin Z. Marbella L.E. Nuckolls C. Air-stable, long-length, solution-based graphene nanoribbons. Chem. Sci. (Camb.) 2020 11 36 9978 9982 10.1039/D0SC02105A 34094260
    [Google Scholar]
  13. Begam B.F. Kumar J.S. A study on cheminformatics and its applications on modern drug discovery. Procedia Eng. 2012 38 1264 1275 10.1016/j.proeng.2012.06.156
    [Google Scholar]
  14. Gasteiger J. Chemoinformatics: Achievements and challenges, a personal view. Molecules 2016 21 2 151 10.3390/molecules21020151 26828468
    [Google Scholar]
  15. Todeschini R. Consonni V. Molecular descriptors for chemoinformatics 2009 10.1002/97835276287
    [Google Scholar]
  16. Gasteiger J. Of molecules and humans. J. Med. Chem. 2006 49 22 6429 6434 10.1021/jm0608964 17064061
    [Google Scholar]
  17. Polanski J. Gasteiger J. Computer representation of chemical compounds. In: Handbook of Computational Chemistry. Cham, Switzerland Springer International Publishing 2017 1997 2039 10.1007/978‑3‑319‑27282‑5_50
    [Google Scholar]
  18. Chen A. Xiong X. Lin F. Distance-based topological indices of the tree-like polyphenyl systems. Appl. Math. Comput. 2016 281 233 242 10.1016/j.amc.2016.01.057
    [Google Scholar]
  19. Hayat S. Computing distance-based topological descriptors of complex chemical networks: New theoretical techniques. Chem. Phys. Lett. 2017 688 51 58 10.1016/j.cplett.2017.09.055
    [Google Scholar]
  20. Arockiaraj M. Clement J. Balasubramanian K. Topological indices and their applications to circumcised donut benzenoid systems, kekulenes and drugs. Polycycl. Aromat. Compd. 2020 40 2 280 303 10.1080/10406638.2017.1411958
    [Google Scholar]
  21. Arockiaraj M. Klav S. Distance-based topological indices of strength-weighted graphs and their application to coronoid systems, carbon nanocones and SiO2 nanostructures. Mol. Inform. 2019 38 11-12 1900039 10.1002/minf.201900039 31529609
    [Google Scholar]
  22. Gutman I. Degree-based topological indices. Croat. Chem. Acta 2013 86 4 351 361 10.5562/cca2294
    [Google Scholar]
  23. Imran M. Baby S. Siddiqui H.M.A. Shafiq M.K. On the bounds of degree-based topological indices of the Cartesian product of F-sum of connected graphs. J. Inequal. Appl. 2017 2017 1 305 10.1186/s13660‑017‑1579‑5 29276360
    [Google Scholar]
  24. Hayat S. Wang S. Liu J.B. Valency-based topological descriptors of chemical networks and their applications. Appl. Math. Model. 2018 60 164 178 10.1016/j.apm.2018.03.016
    [Google Scholar]
  25. Ali P. Kirmani S.A.K. Al Rugaie O. Azam F. Azam F. Degree-based topological indices and polynomials of hyaluronic acid-curcumin conjugates. Saudi Pharm. J. 2020 28 9 1093 1100 10.1016/j.jsps.2020.07.010 32922140
    [Google Scholar]
  26. Zuo X. Liu J.B. Iqbal H. Ali K. Rizvi S.T.R. Topological indices of certain transformed chemical structures. J. Chem. 2020 2020 1 7 10.1155/2020/3045646
    [Google Scholar]
  27. Prabhu S. Murugan G. Arockiaraj M. Arulperumjothi M. Manimozhi V. Molecular topological characterization of three classes of polycyclic aromatic hydrocarbons. J. Mol. Struct. 2021 1229 129501 10.1016/j.molstruc.2020.129501
    [Google Scholar]
  28. Prabhu S. Arulperumjothi M. Manimozhi V. Balasubramanian K. Topological characterizations on hexagonal and rectangular tessellations of antikekulenes and its computed spectral, nuclear magnetic resonance and electron spin resonance characterizations. Int. J. Quantum Chem. 2024 124 7 e27365 10.1002/qua.27365
    [Google Scholar]
  29. Prabhu S. Arulperumjothi M. Ghani M.U. Imran M. Salu S. Jose B.K. Computational analysis of some more rectangular tessellations of kekulenes and their molecular characterizations. Molecules 2023 28 18 6625 10.3390/molecules28186625 37764401
    [Google Scholar]
  30. Radhakrishnan M. Prabhu S. Arockiaraj M. Arulperumjothi M. Molecular structural characterization of superphenalene and supertriphenylene. Int. J. Quantum Chem. 2022 122 2 e26818 10.1002/qua.26818
    [Google Scholar]
  31. Prabhu S. Molecular structural characterization of cycloparaphenylene and its variants. Polycycl. Aromat. Compd. 2022 42 8 5550 5566 10.1080/10406638.2021.1942082
    [Google Scholar]
  32. Arockiaraj M. Prabhu S. Arulperumjothi M. Kavitha S.R.J. Balasubramanian K. Topological characterization of hexagonal and rectangular tessellations of kekulenes as traps for toxic heavy metal ions. Theor. Chem. Acc. 2021 140 4 43 10.1007/s00214‑021‑02733‑0
    [Google Scholar]
  33. Klavžar S. Gutman I. Mohar B. Labeling of benzenoid systems which reflects the vertex-distancerelation. J. Chem. Inf. Comput. Sci. 1995 35 3 590 593 10.1021/ci00025a030
    [Google Scholar]
  34. Klavžar S. On the canonical metric representation, average distance, and partial Hamming graphs. Eur. J. Combin. 2006 27 1 68 73 10.1016/j.ejc.2004.07.008
    [Google Scholar]
  35. Bloom G.S. Kennedy J.W. Quintas L.V. Some problems concerning distance and path degree sequences. In: Graph Theory. Berlin, Heidelberg Springer Verlag 1983 179 190 10.1007/BFb0071628
    [Google Scholar]
  36. Stevanovi’c L. Brankov V. Cvetković D. Simić S. new-GRAPH 2021 Available from: http://www.mi.sanu.ac.rs/newgraph/index.html
  37. Redzepovic I. Furtula B. Gutman I. Relating total π-electron energy of benzenoid hydrocarbons with HOMO and LOMO energies. Match (Mulh.) 2020 84 1 229 237
    [Google Scholar]
  38. Balasubramanian K. Cas scf/ci calculations on Si4 and Si4+. Chem. Phys. Lett. 1987 135 3 283 287 10.1016/0009‑2614(87)85157‑6
    [Google Scholar]
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Ambient-Stable Electroactive Graphene Nanoribbons: A Comprehensive Analysis of Distance, Degree, Energetics and 13C NMR Signals
Bentham Science Publishers ; https://doi.org/10.2174/0113862073408572250925161251
/content/journals/cchts/10.2174/0113862073408572250925161251
/content/journals/cchts/10.2174/0113862073408572250925161251
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  • Article Type:     Research Article
Keywords: ambient-stable electroactive graphene nanoribbon ; π-electron energy ; HOMO-LUMO ; topological indices ; Molecular graph ; cut method ; 13C NMR

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