Advances in Materials Science and Engineering
Volume 2019 (2019), Article ID 9062535, 9 pages
https://doi.org/10.1155/2019/9062535

Research Article

Eccentric Connectivity Index of t-Polyacenic Nanotubes

Jia-Bao Liu,1,2 Hani Shaker,³ Imran Nadeem,³ and Mohammad Reza Farahani⁴

¹School of Mathematics, Southeast University, Nanjing 210096, China
²School of Mathematics and Physics, Anhui Jianzhu University, Hefei 230601, China
³Department of Mathematics, COMSATS University Islamabad, Lahore Campus, Lahore 54000, Pakistan
⁴Department of Applied Mathematics, Iran University of Science and Technology (IUST), Narmak, Tehran 16844, Iran

Correspondence should be addressed to Hani Shaker; hani.uet@gmail.com

Received 6 October 2018; Revised 12 December 2018; Accepted 10 January 2019; Published 11 February 2019

Academic Editor: Yuning Li

Copyright © 2019 Jia-Bao Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

The eccentric connectivity index ECI is a chemical structure descriptor that is currently being used for the modeling of biological activities of a chemical compound. This index has been proved to provide a high degree of predictability as compared to some other well-known indices in case of anticonvulsant, anti-inflammatory, and diuretic activities. The ECI of an infinite class of 1-polyacenic (phenylenic) nanotubes has been recently studied. In this article, we extend this study to generalized polyacenic nanotubes and find ECI of t-polyacenic nanotubes for .

1. Introduction

A basic concept of chemistry is that the properties/activities of a molecule depend upon its structural characteristics. Molecular graphs can be used to model the chemical structures of molecules and molecular compounds, by considering atoms as vertices and the chemical bonds between the atoms as edges. In the study of quantitative structure-property and structure-activity relationships (QSPR/QSAR), the topological indices are very helpful in detecting the biological activities of a chemical compound [1–4].

A topological index is a numerical graph invariant that is used to correlate the chemical structure of a molecule with its physicochemical properties and biological activities. Generally, topological indices are classified into five generations: first-generation topological indices are integer numbers obtained by simple operations from local vertex invariants involving only one vertex at a time. Some of the famous topological indices of this class are Wiener index, Hosoya index, and Centric indices of Balaban [5]. Second-generation topological indices are real numbers based on integer graph properties. These indices were obtained via structural operations from integer local vertex invariants, involving more than one vertex at a time. Some examples of this class include molecular connectivity indices, Balaban J index, bond connectivity indices, and kappa shape indices [5]. Third-generation topological indices are real numbers which are based on local properties of the molecular graph. These indices are of recent introduction and have very low degeneracy. These are based on information theory applied to the terms of distance sums or on newly introduced nonsymmetrical matrices. Some examples include information indices [6], the hyper-Wiener index [5], the Kirchhoff index [7], and electrotopological state indices [2]. Recently, fourth- and fifth-generation topological indices are placed as new generations topological indices. Fourth-generation topological indices are of highly discriminating power, i.e., . The examples of fourth-generation topological indices include eccentric connectivity index [8], superaugmented eccentric connectivity index [9], and superaugmented eccentric connectivity topochemical indices [10]. Detour matrix-based adjacent path eccentric distance sum indices [11] belong to the fifth-generation topological indices.

Let G be a connected molecular graph with vertex set and edge . Let be the set of those edges of G that are incident to a vertex , and then the degree of k is denoted by and is defined as the cardinality of . The distance from a vertex to a vertex is denoted by and is defined as the minimum number of edges lying between them. The eccentricity of a given vertex is defined as the largest distance between k and any vertex l of G.

Sharma et al. in [8] have presented a distance-based chemical structure descriptor, called the eccentric connectivity index (ECI), which is presented as

It is recorded in [12–16] that ECI provides good correlations with regard to physicochemical properties and biological activities. This index is reported as a highly discriminating descriptor for QSPR/QSAR studies [8, 9, 17]. The degree of prediction of ECI is better than the Wiener index in case of diuretic activity [18] and anti-inflammatory activity in [19]. Also, this index has been proved to provide a high degree of predictability with regard to anticonvulsant activity [20] in comparison to Zagreb indices. Recently, the eccentric connectivity index has been studied for certain nanotubes [21–26] and for several molecular graphs [27–29].

Polyacenes relate to a family of polycyclic aromatic hydrocarbon (PAH) compounds which are formed by the linearly fused benzene rings. Numerous molecules of this class have interesting optical, thermodynamic, electronic, ferromagnetic, and photoconductive properties [30–33]. In the first organic solid-state injection laser, the lasing was discovered by using the single crystals of tetracene [34, 35]. They have application in rechargeable Li-ion batteries [36] and also have presence in various celestial objects like planetary nebulae [37]. In this sense, the polyacenes have received much attention. The index of linear polyacenes has been studied in [38]. The molecular graphs of certain linear polyacene molecules are given in Figure 1.

(a)

(b)

(c)

(d)

(e)

(f)

(g)

Figure 1: The polyacene molecules. (a) L1: Benzene; (b) L2: Naphthalene; (c) L3: Anthracene; (d) L4: Tetracene; (e) L5: Pentacene; (f) L6: Hexacene; (g) L7: Heptacene.

Recently, the Zagreb indices of 3-polyacenic (anthracenic), 4-polyacenic (tetracenic), and 5-polyacenic (pentacenic) nanotubes have been studied in [39–41], respectively. The ECI of 1-polyacenic (phenylenic) nanotubes has been presented in [25]. In this paper, we generalize these results to t-polyacenic nanotubes for and present the ECI for these nanotubes.

2. Main Results

The generalized molecular graph of the t-polyacenic nanotube is shown in Figure 2. In this graphical representation, q counts the number of polyacene units in a row and p counts the number of alternative polyacene units in a column of the t-polyacenic nanotube, where a polyacene unit consists of t hexagons. The molecular graph of the t-polyacenic nanotube has rows and q columns. For , the t-polyacenic nanotube is known as phenylenic, naphthalenic, anthacenic, tetracenic, pentacenic, and hexacenic nanotubes, respectively. The molecular graphs of these nanotubes are presented in Figure 3. Let G be a molecular graph of the nanotube and then we can observe that for each . So, we have the vertex partitions of G as follows:

Figure 2: The generalized molecular graph of the t-polyacenic nanotube .

(a)

(b)

(c)

(d)

(e)

(f)

Figure 3: The molecular graphs of t-polyacenic nanotubes for . (a) : phenylenic nanotube; (b) : naphthalenic nanotube; (c) : anthracenic nanotube; (d) : tetracenic nanotube; (e) : pentacenic nanotube; (f) : hexacenic nanotube.

The vertex partitions of G along with their cardinalities corresponding to each row are presented in Table 1. In the following theorems, we formulate the eccentric connectivity index for nanotubes for .

Table 1: The vertex partitions of the nanotube along with their cardinalities corresponding to each row.

Vertex partition
Rows
Cardinality for each row

Theorem 1. Let be the graph of the t-polyacenic nanotube, and then for q even, we have

Proof. Consider . Let represents the vertices in the row. With respect to or , we have the following cases.

Case 1 (when and ). In this case, the eccentricity of each vertex in each row is . Hence, from Table 1 and (1), we have

Case 2 (when and ). In this case,

where . Hence, from Table 1 and (1), we have

Case 3 (when and ). In this case,

Also,

where . Hence, from Table 1 and (1), we have

Case 4 (when , is even and ). In this case,

Hence, from Table 1 and (1), we have

Case 5 (when , is odd and ). In this case, we use the eccentricities of vertices as given in case 4. From Table 1 and (1), we have

Theorem 2. Let be the graph of the t-polyacenic nanotube, and then for q odd, we have

Proof. Consider . Let represent the vertices in the row of G. With respect to or , we have the following cases.

Case 1 (when , and ). In this case, the eccentricity of each vertex in each row is . Hence, from Table 1 and (1), we have

Case 2 (when , and ). In this case, the eccentricity of each vertex in each row is . Hence, from Table 1 and (1), we have

Case 3 (when and ). In this case,

where . Hence, from Table 1 and (1), we have

Case 4 (when and is even). In this case,

Also,

where . Hence, from Table 1 and (1), we have

Case 5 (when and is odd). In this case,

Also,

where . Hence, from Table 1 and (1), we have

Case 6 (when and is odd). In this case,

Also,

where . Hence, from Table 1 and (1), we have

Case 7 (when and is odd). In this case,

Also,

Hence, from Table 1 and (1), we have

Case 8 (when , is even and ). In this case,

Hence, from Table 1 and (1), we have

Case 9 (when , is odd and ). In this case, we use the eccentricities of vertices as given in case 8. From Table 1 and (1), we have

Remark 1. The results presented by Rao and Lakshmi in [25] become special cases of the results given in Theorems 1 and 2 for .

3. Conclusion

In this paper, we present generalized formulae of ECI for t-polyacenic nanotubes. The comparability about biological activities of chemical compounds is of immense interest in QSAR/QSPR studies. The eccentric connectivity index ECI provides the best prediction accuracy rate compared to other indices in various biological activities of diverse nature such as anti-inflammatory activity, anticonvulsant activity, and diuretic activity. In this sense, this index can be very helpful in QSAR/QSPR studies, and by using the given results, we can present mathematical models of several biological activities of all chemical compounds, which correspond to t-polyacenic nanotubes such as phenylenic nanotubes, naphthalenic nanotubes, anthracenic nanotubes, tetracenic nanotubes, pentacenic nanotubes, and hexacenic nanotubes.

Data Availability

All data generated or analyzed during this study are included in this article.

Conflicts of Interest

The authors declare that there are no conflicts of interest.

Acknowledgments

The authors would like to express their sincere gratitude to the anonymous referees and the editor for many valuable, friendly, and helpful suggestions, which led to a great deal of improvement of the original manuscript. This work was done under the project supported by the Higher Education Commission, Pakistan, via Grant no. 5331/Federal/NRPU/R&D/HEC/2016. This research was funded by the China Postdoctoral Science Foundation under Grant no. 2017M621579, the Postdoctoral Science Foundation of Jiangsu Province under Grant no. 1701081B, and Project of Anhui Jianzhu University under Grant nos. 2016QD116 and 2017dc03.

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