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Analyzing the expressions for nanostructures via topological indices
⁎Corresponding author. adnanaslam15@yahoo.com (Adnan Aslam)
-
Received: ,
Accepted: ,
This article was originally published by Elsevier and was migrated to Scientific Scholar after the change of Publisher.
Abstract
In molecular science, one of the key problem is to model a chemical compound and predict its chemical characteristic. Numerous hypothetical methods have been created by various analysts in this respect and one of them is concerned with the topological indices. A topological index is a numerical value attached with the structural graph of a molecule and is expected to predict certain chemical/physical properties of molecule [6]. Among the classes of topological indices, degree based topological indices play a vital role in chemical graph theory. In the current study, we compute the neighborhood second Zagreb index and the first extended first–order connectivity index of Planar zigzag nanotube , polyhex zigzag nanotube , polyhex zigzag nanotori nanosheets, nanotubes, nanotori and armchair polyhex nanotubes .
Keywords
Keywords
Chemical graph theory
Zigzag polyhex nanostructure
Topological indices
05C09
05C92

1 Introduction
Graph theory has played a significant role in chemistry in the last decades. Topological indices are essential in identifying the structures of chemical compounds. It is primarily a number associated with a chemical compound that has excellent features in chemistry. In quantitative structure–property relationship (QSPR) and quantitative structure–activity relationship (QSAR) studies, topological indices plays an important role. The QSAR and QSPR studies are undoubtedly of major importance in material sciences. Topological indices provide an overview of structural features of molecular graphs and reflects the physico-chemical properties of the activity/property under investigation (Randić, 1991; Tavakoli et al., 2013). To overview the structure–activity relationship, topological indices are required to effectively characterize structural features and bioactivity of chemical compounds (Balaban, 1979; Balaban et al., 1983; Balaban, 1988).
Let G be a finite, simple connected graph. In chemical graph theory, a molecular structure is a simple graph(a graph portraying chemical compounds) in which vertices correspond to the atoms and the edges corresponds to the bonds between the atoms. A numerical quantity of a chemical structure (molecular graph) which remains invariant under graph isomorphism is recognized as graph invariant. Topological index is an example of graph invariant. The most significant and widely used topological indices are degree-based topological indices. They have a remarkable application in mathematical chemistry.
For a vertex , we use the notation for the set containing the vertices adjacent to w. The degree of a vertex w is the cardinality of the set and is denoted by . Let denote the sum of degrees of the vertices adjacent to w. In other words, and . For undefined terminologies related to graph theory, the author can read the following books (Gross and Yellen, 2000; Trinajstić, 1992; Godsil and Royle, 2001; Harary, 1969).
Consider the following general graph invariant
Some special cases of the above invariants I have already been appeared in mathematical chemistry. For example, if we take
and
then I gives neighborhood second Zagreb index(Réti et al., 2019) and the first extended first-order connectivity index (Bonchev and Kier, 1992; Toropov et al., 1997; Wang and Zhou, 2014; Zhou and Trinajstić, 2009), respectively. These indices are defined as:
2 Motivation
Topological indices are useful to predict certain physical and chemical properties of the underline molecule. To check the chemical applicability of
and
, we find their correlation coefficient with different physical/chemical properties of octane isomers. The values of acentric factor and entropy obtained from experiments and the computed values of
and
for octane isomers are depicted in Table 1. The correlation coefficients between the entropy, acentric factor and
are presented in Table 2. Observe that both the topological indices
and
shows a very good correlation with entropy and acentric factor of octane isomers and thus can be used to predict these properties.
Molecule
Acentric Factor
Entropy
NM2
2,2,3,3-Tretramethyl-butane
0.255294
93.06
217
0.068
2,4-Dimethyl-hexane
0.344223
106.98
121
0.091
2-Methyl-heptane
0.377916
109.84
98
0.101
2-Methyl-3-ethyl-pentane
0.332433
106.06
137
0.085
3-Ethyl-hexane
0.362472
109.43
115
0.093
2,2-Dimethyl-hexane
0.339426
103.42
132
0.087
3-Methyl-heptane
0.371002
111.26
106
0.097
2,3-Dimethyl-hexane
0.348247
108.02
129
0.088
2,5-Dimethyl-hexane
0.35683
105.72
113
0.094
2,2,4-Trimethyl-pentane
0.30537
104.09
147
0.082
4-Methyl-heptane
0.371504
109.32
107
0.096
3,3-Dimethyl-hexane
0.322596
104.74
148
0.082
3-Methyl-3-ethyl-pentane
0.306899
101.48
163
0.078
2,2,3-Trimethyl-pentane
0.300816
101.31
171
0.076
3,4-Dimethyl-hexane
0.340345
106.59
136
0.086
2,3,3-Trimethyl-pentane
0.293177
102.06
179
0.074
Octane
0.397898
111.67
84
0.104
2,3,4-Trimethyl-pentane
0.317422
102.39
151
0.081
Accentric factor
0.9708
0.9667
Entropy
0.8989
0.8418
One of the important use of topological indices is their discrimination power against octane isomers. The ability of discrimination of an index has applications within the coding and computer processing of molecular structures (isomers). The graphs of 18 octane isomers are depicted in Fig. 1. Let
be the number of edges in a graph G having end vertices of degree p and q respectively. Two graphs H and K are said to be edge equivalent iff
. Observe that the graph
and
are edge equivalent having different values of
and
(
and
). Similarly
and
are edge equivalent with different values of
and
(
and
). By using the definition, one can check that all the octane isomers have different values of
index. The same holds for
index. Hence the discriminatory power of these indices is much better than other bond incident degree indices.Graphs of Octane isomers.
3 Results and Discussion
The most valuable nanomaterials available to scientists to achieve various experimentation and control objectives are carbon nanotubes(CNT). CNTs are important object to study because of their growing application in different fields especially in medical sciences. They have excellent features which include outstanding penetration capacity on the cellular membrane, strong drug load and therapeutic discharge capabilities dependent on pH. This make them fit for cancer and brain medications. CNTs as a medicine could attain great effectiveness, improve specificity and reduce side effects. Some investigations makes CNTs center of attention to treat and diagnose the central nervous system but the fundamental use of CNTs is in cancer treatment. (See Fig. 2).2D structure of zigzag polyhex Lattice (
).
3.1 Results for Zigzag Polyhex Nanostructures
Graphene is a crystalline allotrope made from pure carbon atoms arranges in the form of two dimensional hexagonal lattice. It has unique properties containing best heat conductivity at room temperature and high optical transparency. zigzag polyhex lattice is a graphene lattice with m and n number of hexagons in each row and column respectively. We denote the graph of zigzag polyhex lattice by
. The graph of
is depicted in Fig. 4. A zigzag polyhex nanotube denoted by
is obtained by rolling the graphene sheet into seamless tube such that vertical axis of the tube is parallel to the carbon–carbon bonds. We denote the Zigzag polyhex nanotorus by
and is obtained by joining the two ends of zigzag polyhex nanotube. The graphs of
and
are depicted in Fig. 3 and Fig. 5 respectively. The order and size of each of these nanostructures is shown Table 3.The 3D structure of polyhex zigzag nanotube(
).
2D structure of zigzag polyhex Lattice (
).
The 3D structure of polyhex zigzag nanotori (
).
order
size
In the next Theorems, we compute the two connectivity indices (neighborhood second Zagreb index and the first extended first-order connectivity index) for the famous nanostructure and . For this we need to partition the edge set of each nanostructure depending on the sum of the degree of neighbors of the end vertices of each edge.
Let G be the graph of zigzag polyhex lattice, then
Let (or simply ) denotes the set containing those edges of graph G such that and . To compute and , we need to partition the edge set into the sets of the form and compute the its cardinality. This information is presented in the Table 4. To have a good understanding of this computation, we have colored the edges with same color that lies in the same set (see Fig. 4). Now using the values from the Table 4 in the definition of and , we get □
Let G be the graph of zigzag polyhex nanotube, then
The edge sets of the form of G and their cardinalities are depicted in Table 5. To have a good understanding of this computation, we have colored the edges with same color that lies in the same set (see Fig. 3). Now using the values from the Table 5 in the definition of and , we get □
Let G be the graph of zigzag polyhex nanotorus, then
In G, all the edges are of the form . Hence we have edges in the set and □
Cardinality | ||
---|---|---|
8 | ||
2n-4 | ||
4 | ||
4n-4 | ||
4 m-8 | ||
2 m-4 | ||
2n-2 | ||
4n-4 | ||
(m-3)(7n-9) |
Cardinality | |
---|---|
4 m | |
2 m | |
6mn-10 m |
3.2 Results for Nanosheets, Nanotubes and Nanotori covered by and
A mutual decoration created by alternating squares and octagons is referred to as nanosheet. and nanosheets are obtained by the positioning of squares and octagons. We denote the nanosheet with n hexagon in each row and m hexagons in each column by . The order and size of nanosheet are and respectively. Similarly, the nanosheet with m squares in each row and n squares in each column is denoted by . The order and size of nanosheet are and respectively. Fig. 6 and Fig. 7 depicts the graphs of and nanosheets respectively. These nanosheets have uniform thickness and are important due to their novel characteristics such as stability and flexibility. Significant application of nanosheets can be viewed in sensors, filtration membranes and even conductive coatings (Turchanin et al., 2009). The chemical, mechanical and thermal stability of these nanosheets is equally strong. For more information on the computation of different topological indices of these nanosheets, we refer the readers to (Al-Fozan et al., 2014; Manuel et al., 2013; Arockiaraj et al., 2016). In the next Theorems, we compute the two connectivity indices of these nanosheets.
Let G be the graph of nanosheet, then
The edge sets of the form of G and their cardinalities are depicted in Table 6. Now using the values from the Table 6 in the definition of and , we get □
Let G be the graph of nanosheet, then
The edge sets of the form of G and their cardinalities are depicted in Table 7. Now using the values from the Table 7 in the definition of and , we get □
Let G be the graph of nanotube, then
The edge sets of the form of G and their cardinalities are depicted in Table 8. Now using the values from the Table 8 in the definition of and , we get □
Let G be the graph of nanotube, then
The edge sets of the form of G and their cardinalities are depicted in Table 9. Now using the values from the Table 9 in the definition of and , we get □
Let G and H be the graphs of and nanotori, then
Note that all the edges of G and H belongs to the set . The results follow from the definition of and . □
![Structure of C 4 C 8 ( R ) [ 3 , 5 ] nanosheet.](/content/184/2022/15/1/img/10.1016_j.arabjc.2021.103469-fig6.png)
- Structure of
nanosheet.
![Structure of C 4 C 8 ( S ) [ 3 , 4 ] nanosheet.](/content/184/2022/15/1/img/10.1016_j.arabjc.2021.103469-fig7.png)
- Structure of
nanosheet.
Cardinality | ||
---|---|---|
4 | ||
8 | ||
2 m + 2n-8 | ||
4 m + 4n-8 | ||
2 m + 2n −4 | ||
4 m + 4n-8 | ||
12mn - 14 m - 14n + 16 |
Cardinality | ||
---|---|---|
4 | ||
8 | ||
4 m + 4n-8 | ||
2 m + 2n + 4 | ||
4 m + 4n-8 | ||
6mn - 5 m −5n + 4 |
![Structure of TUC 4 C 8 ( S ) [ 3 , 4 ] .](/content/184/2022/15/1/img/10.1016_j.arabjc.2021.103469-fig8.png)
- Structure of
.
![2D structure of TUC 4 C 8 ( R ) [ 3 , 5 ] .](/content/184/2022/15/1/img/10.1016_j.arabjc.2021.103469-fig9.png)
- 2D structure of
.
Cardinality | ||
---|---|---|
2n | ||
4n | ||
2n | ||
4n | ||
12mn - 14n |
Cardinality | ||
---|---|---|
4n + 4 | ||
2n + 2 | ||
4n + 4 | ||
6mn + 6 m-5n-5 |
![Structure of TUC 4 C 8 ( S ) [ 3 , 4 ] .](/content/184/2022/15/1/img/10.1016_j.arabjc.2021.103469-fig10.png)
- Structure of
.
![2D structure of TUC 4 C 8 ( R ) [ 3 , 5 ] .](/content/184/2022/15/1/img/10.1016_j.arabjc.2021.103469-fig11.png)
- 2D structure of
.
3.3 Armchair Polyhex Nanotubes
An Armchair Polyhex Nanotube denoted by is obtained by rolling the graphene sheet into seamless tube such that horizantal axis of the tube is parallel to the carbon–carbon bonds. We use the notation for the armchair polyhex nanotube with m and n hexagons in each row and column respectively. The graph of is depicted in Fig. 12. The order and size of are and respectively. Now, we compute the connectivity indices of .
Let G be the graph of nanotube, then
The edge sets of the form of G and their cardinalities are depicted in Table 10. Now using the values from the Table 10 in the definition of and , we get □
![Armchair Polyhex Nanotube TUAC 6 [ m , n ] for m = 10 and n = 6 .](/content/184/2022/15/1/img/10.1016_j.arabjc.2021.103469-fig12.png)
- Armchair Polyhex Nanotube
for
and
.
Cardinality | ||
---|---|---|
m | ||
2 m | ||
m | ||
2 m | ||
3mn-4 m |
4 Conclusion
In this paper, we have analyzed different nanotubes graphs such as zigzag nanotures, nanostructure and armchair polyhex nanotubes through newly introduced topological indices. Topological indices consequently determined can assist us with understanding their physical characteristics, synthetic reactivity and natural exercises. These findings are precious and useful for scientists to comprehend profound behavior and construction of some carbon nanotubes. These findings are also significant contributors to the study of chemical graph theory, quantum chemistry, QSPR and QSAR.
5 Data availability statement
No data were used to support this study.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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