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2000
Volume 10, Issue 3
  • ISSN: 2405-4615
  • E-ISSN: 2405-4623

Abstract

Aims

Carbon nanocones possess exceptional properties compared to other nanomaterials, such as nanotubes, graphene, . Hence, they can be used as an alternative to other nanostructures. This work helps in determining various properties of the nanocone structure through topological descriptors. In this paper, various degree-based topological descriptors, along with their entropy measures, are evaluated for the adjacently and non-adjacently configured pentagonal structure of carbon nanocones.

Background

Carbon nanoparticles are gaining much importance in the contemporary world. Carbon nanocones have a wide range of acceptance in the field of nanotechnology due to their effective properties and applications. Nanocones, also known as nanohorns, are carbon networks that are planar in structure and have the majority of hexagonal faces along with some non-hexagonal faces, which are most commonly pentagons. Nanocones that include pentagons in their structure can be referred to as adjacently or non-adjacently configured pentagonal structures of nanocones. Various topological descriptors for a few nanocone classes were derived by researchers earlier, but not for the class of nanocones in this paper. Through this work, we try to fill the research gap in this field.

Objective

The degree-based descriptors and corresponding graph entropies for the adjacently and non-adjacently configured pentagonal structure of nanocones were determined, which further can be applied in quantitativestructure–activity property relationship studies. The concept of graph entropy is to assign a probability function to the edges in the chemical graph using the topological descriptor, and it helps to characterize the complexity of graphs.

Method

We have employed the degree counting method and edge partition based on the vertices and edges of the adjacently and non-adjacently configured pentagonal nanocone structures to obtain the edge partitions and then using the corresponding mathematical expression, the degree-based descriptors and their corresponding entropies were determined.

Result

The analytically closed formulas to compute the degree-based topological descriptors and graph entropies for any generation of the class of nanocone structures were obtained.

Conclusion

In this work, the degree-based descriptors and the corresponding graph entropies for the adjacently and non-adjacently configured pentagonal structure of carbon nanocones are determined by applying the degree counting method and edge partition based on the vertices and edges. Also, a graphical comparative study was done with the help of the obtained results.

© 2025 The Author(s). Published by Bentham Science Publisher. This is an open access article published under CC BY 4.0 https://creativecommons.org/licenses/by/4.0/legalcode
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References

  1. TerronesH. Curved graphite and its mathematical transformations.J. Math. Chem.199415114315610.1007/BF01277556
    [Google Scholar]
  2. IijimaS. YudasakaM. YamadaR. BandowS. SuenagaK. KokaiF. TakahashiK. Nano-aggregates of single-walled graphitic carbon nano-horns.Chem. Phys. Lett.19993093-416517010.1016/S0009‑2614(99)00642‑9
    [Google Scholar]
  3. AndrewsD. NannT. LipsonR.H. Comprehensive nanoscience and nanotechnology.Academic press2019
    [Google Scholar]
  4. TagmatarchisN. Advances in carbon nanomaterials: Science and applications.CRC Press201210.1201/b11990
    [Google Scholar]
  5. BrinkmannG. Van CleemputN. Classification and generation of nanocones.Discrete Appl. Math.2011159151528153910.1016/j.dam.2011.06.014
    [Google Scholar]
  6. KavithaS.R.J. AbrahamJ. ArockiarajM. JencyJ. BalasubramanianK. Topological characterization and graph entropies of tessellations of kekulene structures: existence of isentropic structures and applications to thermochemistry, nuclear magnetic resonance, and electron spin resonance.J. Phys. Chem. A2021125368140815810.1021/acs.jpca.1c0626434469167
    [Google Scholar]
  7. AdisaO.O. CoxB.J. HillJ.M. Open carbon nanocones as candidates for gas storage.J. Phys. Chem. C201111550245282453310.1021/jp2069094
    [Google Scholar]
  8. AjimaK. MurakamiT. MizoguchiY. TsuchidaK. IchihashiT. IijimaS. YudasakaM. Enhancement of in vivo anticancer effects of cisplatin by incorporation inside single-wall carbon nanohorns.ACS Nano20082102057206410.1021/nn800395t19206452
    [Google Scholar]
  9. KarousisN. Suarez-MartinezI. EwelsC.P. TagmatarchisN. Structure, properties, functionalization, and applications of carbon nanohorns.Chem. Rev.201611684850488310.1021/acs.chemrev.5b0061127074223
    [Google Scholar]
  10. YudasakaM. IijimaS. CrespiV.H. Single-wall carbon nanohorns and nanocones.Carbon nanotubes.Berlin, HeidelbergSpringer200760562910.1007/978‑3‑540‑72865‑8_19
    [Google Scholar]
  11. CharlierJ.C. RignaneseG.M. Electronic structure of carbon nanocones.Phys. Rev. Lett.200186265970597310.1103/PhysRevLett.86.597011415406
    [Google Scholar]
  12. LinC.T. LeeC.Y. ChiuH.T. ChinT.S. Graphene structure in carbon nanocones and nanodiscs.Langmuir20072326128061281010.1021/la701949k18001066
    [Google Scholar]
  13. UlloaP. LatgéA. OliveiraL.E. PachecoM. Cone-like graphene nanostructures: Electronic and optical properties.Nanoscale Res. Lett.20138138410.1186/1556‑276X‑8‑38424028308
    [Google Scholar]
  14. WienerH. Structural determination of paraffin boiling points.J. Am. Chem. Soc.1947691172010.1021/ja01193a00520291038
    [Google Scholar]
  15. LiuJ.B. ZhangT. WangY. LinW. The Kirchhoff index and spanning trees of Möbius/cylinder octagonal chain.Discrete Appl. Math.2022307223110.1016/j.dam.2021.10.004
    [Google Scholar]
  16. ShannonC.E. A mathematical theory of communication.Bell Syst. Tech. J.194827337942310.1002/j.1538‑7305.1948.tb01338.x
    [Google Scholar]
  17. SabirovD.S. ShepelevichI.S. Information entropy in chemistry: An overview.Entropy20212310124010.3390/e2310124034681964
    [Google Scholar]
  18. MowshowitzA. DehmerM. Entropy and the complexity of graphs revisited.Entropy201214355957010.3390/e14030559
    [Google Scholar]
  19. RashevskyN. Life, information theory, and topology.Bull. Math. Biophys.195517322923510.1007/BF02477860
    [Google Scholar]
  20. RahulM.P. ClementJ. Singh JuniasJ. ArockiarajM. BalasubramanianK. Degree-based entropies of graphene, graphyne and graphdiyne using Shannon’s approach.J. Mol. Struct.2022126013279710.1016/j.molstruc.2022.132797
    [Google Scholar]
  21. BalabanA.T. Chemical applications of graph theory.Academic Press1976
    [Google Scholar]
  22. GutmanI. ToganM. YurttasA. CevikA.S. CangulI.N. Inverse problem for sigma index.MATCH Commun. Math. Comput. Chem2018792491508
    [Google Scholar]
  23. RandićM. Characterization of molecular branching.J. Am. Chem. Soc.197597236609661510.1021/ja00856a001
    [Google Scholar]
  24. RandićM. Novel molecular descriptor for structure—property studies.Chem. Phys. Lett.19932114-547848310.1016/0009‑2614(93)87094‑J
    [Google Scholar]
  25. ShirakolS. KalyanshettiM. HosamaniS.M. QSPR analysis of certain distance based topological indices.Applied Mathematics and Nonlinear Sciences20194237138610.2478/AMNS.2019.2.00032
    [Google Scholar]
  26. YanL. FarahaniM. R. GaoW. Distance-based indices computation of symmetry molecular structures.Open journal of mathematical sciences201821323337
    [Google Scholar]
  27. ArockiarajM. PaulD. GhaniM.U. TiggaS. ChuY.M. Entropy structural characterization of zeolites BCT and DFT with bond-wise scaled comparison.Sci. Rep.20231311087410.1038/s41598‑023‑37931‑237407626
    [Google Scholar]
  28. Ashraful AlamM. GhaniM.U. KamranM. Shazib HameedM. Hussain KhanR. BaigA.Q. Degree-based entropy for a non-kekulean benzenoid graph.J. Math.2022202211210.1155/2022/2288207
    [Google Scholar]
  29. BabyA. JulietrajaK. XavierD.A. On molecular structural characterization of cyclen cored dendrimers.Polycycl. Aromat. Compd.202312310.1080/10406638.2023.2179641
    [Google Scholar]
  30. JavarajuS. AhmedH. AlsinaiA. SonerN.D. Domination topological properties of carbidopa-levodopa used for treatment Parkinson’s disease by using φp-polynomial.Eurasian Chemical Communications202139614621
    [Google Scholar]
  31. JavarajuS. AlsinaiA. AlwardiA. AhmedH. SonerN.D. Reciprocal leap indices of some wheel related graphs.Journal of Prime Research in Mathematics2021172101110
    [Google Scholar]
  32. GnanarajL.R.M. GanesanD. SiddiquiM.K. Topological indices and QSPR analysis of NSAID drugs.Polycycl. Aromat. Compd.2023431011710.1080/10406638.2022.2164315
    [Google Scholar]
  33. HasanA. QasmiM.H.A. AlsinaiA. AlaeiyanM. FarahaniM.R. CancanM. Distance and degree based topological polynomial and indices of X-level wheel graph.Journal of Prime Research in Mathematics20211723950
    [Google Scholar]
  34. ManzoorS. SiddiquiM.K. AhmadS. On entropy measures of polycyclic hydroxychloroquine used for novel coronavirus (COVID-19) treatment.Polycycl. Aromat. Compd.20224262947296910.1080/10406638.2020.1852289
    [Google Scholar]
  35. MondalS. DasK.C. Degree-based graph entropy in structure–property modeling.Entropy2023257109210.3390/e2507109237510039
    [Google Scholar]
  36. NagarajanS. ImranM. KumarP.M. PattabiramanK. GhaniM.U. Degree-based entropy of some classes of networks.Mathematics202311496010.3390/math11040960
    [Google Scholar]
  37. RaviV. DesikanK. Curvilinear regression analysis of benzenoid hydrocarbons and computation of some reduced reverse degree based topological indices for hyaluronic acid-paclitaxel conjugates.Sci. Rep.2023131323910.1038/s41598‑023‑28416‑336828838
    [Google Scholar]
  38. TangY. LabbaM. JamilM.K. AzeemM. ZhangX. Edge valency-based entropies of tetrahedral sheets of clay minerals.PLoS One2023187e028893110.1371/journal.pone.028893137478115
    [Google Scholar]
  39. AliA. GutmanI. RedžepovićI. Atom-bond sum-connectivity index of unicyclic graphs and some applications.Electron. J. Math2023517
    [Google Scholar]
  40. AlsinaiA. RehmanH. M. U. ManzoorY. CancanM. TaşZ. FarahaniM. R. Sharp upper bounds on forgotten and SK indices of cactus graph.Journal of Discrete Mathematical Sciences and Cryptography202212210.1080/09720529.2022.2027605
    [Google Scholar]
  41. DasK.C. MondalS. On neighborhood inverse sum indeg index of molecular graphs with chemical significance.Inf. Sci.202362311213110.1016/j.ins.2022.12.016
    [Google Scholar]
  42. IslamS.R. PalM. Second Zagreb index for fuzzy graphs and its application in mathematical chemistry.Iranian Journal of Fuzzy Systems2023201119136
    [Google Scholar]
  43. KumarS. SarkarP. PalA. A study on the energy of graphs and its applications.Polycycl. Aromat. Compd.202311010.1080/10406638.2023.2245104
    [Google Scholar]
  44. LiuH. YouL. HuangY. TangZ. On extremal Sombor indices of chemical graphs, and beyond.Match202389241543610.46793/match.89‑2.415L
    [Google Scholar]
  45. MageshwaranK. AlessaN. GopinathS. LoganathanK. Topological indices of graphs from vector spaces.Mathematics202311229510.3390/math11020295
    [Google Scholar]
  46. PantázJ. RodriguezJ. On the estrada index of graphene graph.Polycycl. Aromat. Compd.20234321888189710.1080/10406638.2022.2036779
    [Google Scholar]
  47. AlsinaiA. BasavanagoudB. SayyedM. FarahaniM.R. Sombor index of some nanostructures.Journal of Prime Research in Mathematics2021172123133
    [Google Scholar]
  48. RaufA. NaeemM. HanifA. Quantitative structure–properties relationship analysis of Eigen‐value ‐based indices using COVID ‐19 drugs structure.Int. J. Quantum Chem.20231234e2703010.1002/qua.2703036718482
    [Google Scholar]
  49. RazaZ. ArockiarajM. MaaranA. KavithaS.R.J. BalasubramanianK. Topological entropy characterization, NMR and ESR spectral patterns of coronene-based transition metal organic frameworks.ACS Omega2023814133711338310.1021/acsomega.3c0082537065084
    [Google Scholar]
  50. RedžepovićI. FurtulaB. Predictive potential of eigenvalue-based topological molecular descriptors.J. Comput. Aided Mol. Des.202034997598210.1007/s10822‑020‑00320‑232533372
    [Google Scholar]
  51. ShashidharaaA. A. AhmedbH. NandappaS. CancancM. Domination version: Sombor index of graphs and its significance in predicting physicochemical properties of butane derivatives.Eurasian Chemical Communications202351
    [Google Scholar]
  52. AlsinaiA. SalehA. AhmedH. MishraL.N. SonerN.D. On fourth leap Zagreb index of graphs.Discrete Math. Algorithms Appl.2023152225007710.1142/S179383092250077X
    [Google Scholar]
  53. ArockiarajM. KlavžarS. ClementJ. MushtaqS. BalasubramanianK. Edge distance‐based topological indices of strength‐weighted graphs and their application to coronoid systems, carbon nanocones and SiO 2 Nanostructures.Mol. Inform.20193811-12190003910.1002/minf.20190003931529609
    [Google Scholar]
  54. AsifM. HussainM. AlmohamedhH. AlhamedK.M. AlabdanR. AlmutairiA.A. AlmotairiS. Study of carbon nanocones CNC_k(n) via connection zagreb indices.Math. Probl. Eng.20212021113
    [Google Scholar]
  55. GaoW. FarahaniM.R. Computing the reverse eccentric connectivity index for certain family of nanocone and fullerene structures.J. Nanotechnol.201620161610.1155/2016/3129561
    [Google Scholar]
  56. JahanbaniA. On topological indices of carbon nanocones and nanotori.Int. J. Quantum Chem.20201206e2608210.1002/qua.26082
    [Google Scholar]
  57. KhaksarA. GhorbaniM. MaimaniH.R. On atom bond connectivity and GA indices of nanocones.Optoelectron. Adv. Mater. Rapid Commun.2010418681870
    [Google Scholar]
  58. NazeerW. FarooqA. YounasM. MunirM. KangS. On molecular descriptors of carbon nanocones.Biomolecules2018839210.3390/biom803009230205520
    [Google Scholar]
  59. PattabiramanK. Sanskruti index of bridge graph and some nanocones.Journal of Mathematical Nanoscienese2017728595
    [Google Scholar]
  60. ShanmukhaM.C. UshaA. ShilpaK.C. SiddiquiM.K. Structural investigation of carbon nanocone through topological coindices.Int. J. Quantum Chem.202312312e2710910.1002/qua.27109
    [Google Scholar]
  61. ZahidZ. AsifF. KhalafA.J.M. FarahaniM.R. On leap indices of CNC k [ n ] by using line operator on its subdivision.Journal of Discrete Mathematical Sciences and Cryptography202124234335210.1080/09720529.2021.1882157
    [Google Scholar]
  62. ShortT. The saturation number of carbon nanocones and nanotubes.arXiv:1807.11355.2018
    [Google Scholar]
  63. ZobairM.M. MalikM.A. ShakerH. Eccentricity‐based topological invariants of tightest nonadjacently configured stable pentagonal structure of carbon nanocones.Int. J. Quantum Chem.202112124e2680710.1002/qua.26807
    [Google Scholar]
  64. GutmanI. Degree-based topological indices.Croat. Chem. Acta201386435136110.5562/cca2294
    [Google Scholar]
  65. FajtlowiczS. On Conjectures of Grafitti II.Congr. Number198760189197
    [Google Scholar]
  66. ShirdelG. H. RezapourH. SayadiA. M. The hyper-Zagreb index of graph operations. Research Paper201342213220
    [Google Scholar]
  67. FurtulaB. GutmanI. A forgotten topological index.J. Math. Chem.20155341184119010.1007/s10910‑015‑0480‑z
    [Google Scholar]
  68. FavaronO. MahéoM. SacléJ-F. Some eigenvalue properties in graphs (conjectures of Graffiti — II).Discrete Math.19931111-319722010.1016/0012‑365X(93)90156‑N
    [Google Scholar]
  69. ZhouB. TrinajstićN. On general sum-connectivity index.J. Math. Chem.201047121021810.1007/s10910‑009‑9542‑4
    [Google Scholar]
  70. Vukicevic. FurtulaB. Topological index based on the ratios of geometrical´ and arithmetical means of end-vertex degrees of edges.Journal of mathematical chemistry200946413691376
    [Google Scholar]
  71. EstradaE. TorresL. RodriguezL. GutmanI. An atom-bond connectivity index: Modelling the enthalpy of formation of alkanes.1998
    [Google Scholar]
  72. AlbertsonM.O. The irregularity of a graph.Ars Comb.199746219225
    [Google Scholar]
  73. GutmanI. TrinajstićN. Graph theory and molecular orbitals. Total φ-electron energy of alternant hydrocarbons.Chem. Phys. Lett.197217453553810.1016/0009‑2614(72)85099‑1
    [Google Scholar]
  74. KazemiR. Entropy of weighted graphs with the degree-based topological indices as weights.MATCH Commun. Math. Comput. Chem20167616980
    [Google Scholar]
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