Next Article in Journal
Separation of Protein-Binding Anthraquinones from Semen Cassiae Using Two-Stage Foam Fractionation
Previous Article in Journal
Towards the Grand Unification of Process Design, Scheduling, and Control—Utopia or Reality?

Processes 2019, 7(7), 462; https://doi.org/10.3390/pr7070462

Article
Topological Characterization of Nanosheet Covered by C3 and C6
1
College of Science and Human Studies, Prince Mohammad Bin Fahd University, Khobar Dhahran 34754, Saudi Arabia
2
Department of Mathematics, Al-Imam Mohammad Ibn Saud Islamic University, Riyadh 11432, Saudi Arabia
3
Department of Mathematics, Government College University Faisalabad, Faisalabad 38000, Pakistan
4
Department of Applied Chemistry, Government College University Faisalabad, Faisalabad 38000, Pakistan
*
Author to whom correspondence should be addressed.
Received: 11 June 2019 / Accepted: 9 July 2019 / Published: 18 July 2019

Abstract

:
A topological index of a graph is a single numeric quantity which relates the chemical structure with its underlying physical and chemical properties. Topological indices of a nanosheet can help us to understand the properties of the material better. This study deals with computation of degree-dependent topological indices like the Randic index, first Zagreb index, second Zagreb index, geometric arithmetic index, atom bond connectivity index, sum connectivity index and hyper Zagreb index of nanosheet covered by C3 and C6. Furthermore, M-polynomial of the nanosheet is also computed, which provides an alternate way to express the topological indices.
Keywords:
nanosheet; topological index; M-polynomial; Zagreb index; Randic index

1. Introduction

Nanosheets are two-dimensional polymeric materials which remain among the most actively researched areas of subject chemistry and physics. Generally, nanosheets are inorganic materials which can be created from bulk crystalline layered materials that have fascinating properties and functionalities, excellent electrochemical performance, and high potential for separation applications due to their exceptional molecular transport properties [1]. The nanomaterial has a sheet-like structure with a size larger than 100 nm and thickness less than 5 nm, which is only one or a few atoms thick. Topological indices quantify the physical as well as chemical properties of compounds by associating a unique number to chemical graphs which represent a chemical structure by denoting atoms by vertices and bonds are represented by edges of the graph.
Graphene derived from graphite is a highly attractive two-dimensional lubricating material, wear-resistant with low-friction characteristics [2,3,4], endowed with high conductivity, tensile strength, and remarkable toughness [5]. Other aspects of nanomaterials like optical properties, applications in human therapeutics, biocompatibility, and stability are established in [6,7,8]. Boron nitride nanosheets (BNNs) and nanotubes have closely analogous properties to carbon nanotubes. High stiffness and excellent chemical stability make BNNs an ideal material for reinforcement in polymers, ceramics, and metals. BNNs also exhibit excellent thermal conductivity, radiation shielding ability, and high electrical resistance [8,9]. These ultrathin 2D nanomaterials possess utilization for wide ranges of potential applications among the electronics/optoelectronics, electrocatalysis, batteries, supercapacitors, solar cells, photocatalysis, and sensing platforms.
Today, topological indices are extensively applied in computational chemistry methods such as (Q)SARs ((Quantitative) Structure-Activity Relationships) in the area of toxicology and drug design: computational models are used to predict the behavior and effects of nanomaterials in biological systems. Topological indices (descriptors) provide a comprehensive understanding of the relationships between the physicochemical properties and the behavior of nanomaterials in biological systems for designing safe and functional nanomaterials. Quantitative Structure-Activity Relationship (QSAR) methods help to establish such relationships and have been widely studied [10,11,12,13].
Let us consider G = ( V , E ) be such a graph having n vertices and m edges. The symbol d u is the degree of vertex u V ( G ) and is the number of vertices that are adjacent to u .
The first degree based topological index is a Randic index x ( G ) , invented by Milan Randic [14] in 1975 and is defined as:
x ( G ) = u v E 1 d u d v
Bollobás and Erdös [15] introduced the idea of the general Randic index in 1998.
The general Randic index of graph G is defined as:
R α ( G ) = u v E ( d u d v ) α
The first and second Zagreb index M 1 ( G ) ,   M 2 ( G ) , termed by Gutman and Trinajstić [16], are also among the oldest known topological indices and are defined as:
M 1 ( G ) = u v E [ d u + d v ]
M 2 ( G ) = u v E [ d u d v ]
The atom-bond connectivity index, or ABC index, is a degree based topological index which was introduced by Estrada et al. [17]. It is represented as:
A B C ( G ) = u v E d u + d v 2 d u d v
Sum connectivity index ( S C I ( G ) ) was invented by Zhou and Trinajstić [18], expressed by Equation (5).
S C I ( G ) = u v E 1 d u + d v
The Geometric-arithmetic index or G A ( G ) is a topological index of a molecular graph G which was introduced by Vukičević and Furtula [19].
The geometric-arithmetic topological index is defined as:
GA ( G ) = u v E 2 d u d v d u + d v
A new degree based topological index called the hyper-Zagreb index was introduced by Shirdel et al. [20], and is given as:
H M ( G ) = u v E ( d u + d v ) 2
The first and second multiple Zagreb indices, denoted by P M 1 ( G ) and P M 2 ( G ) , were introduced in 2012 [21].
P M 1 ( G ) = u v E [ d u + d v ]
P M 2 ( G ) = u v E [ d u × d v ]
Degree-based topological indices and M-polynomials of different types of nanotubes are being studied by many researchers. Jagadeesh et al. computed degree based topological indices of graphene [22]. Chen et al. [23] analyzed topological indices of nanotubes covered by C4. Hayat et al. computed topological indices of nanotubes covered by C5 and C7 [24]. Aslam et al. [25] worked for topological characterization of triangular boron nanotubes. Idrees et al. provided results for topological indices of an H-Naphthalenic nanosheet [26]. We refer readers to [27,28,29,30] for further studies in this area.
Degree based topological indices of nanosheets tessellated by C3 and C6, described in Figure 1, are computed in this paper. These computations can give further insight into the underlying information of the material. Moreover, M-polynomial of the nanosheet is also computed in the paper, which is an eloquent way to describe topological invariants in a single expression. These types of nanosheets appear as a type of coordination nanosheet; for further details of coordination nanosheet, see [31].

2. Methods

The degree-based topological indices can be computed by using the degrees of end vertices of the coordination nanosheet. We denote it by C [ m , n ] , where m denotes the number of hexagons in each row and   n denotes the number of hexagons in each column. Chemical graph of C [ m , n ] has successive columns of hexagons ( C 6 ) and triangles ( C 3 ). We partition the edges of the graph according to the degrees of the end vertices. All vertices having degrees according to edges connected with the respective vertex are computed as 2, 3, and 4. Here we have five different types of edges whose end vertices have a degree (2,2), (2,3), (3,3), (3,4), and (4,4), symbolically denoted by E ( 2 , 2 ) , E ( 2 , 3 ) , E ( 3 , 3 ) , E ( 3 , 4 ) and E ( 4 , 4 ) , respectively. Total number of edges computed of the type E ( 2 , 2 ) , E ( 2 , 3 ) , E ( 3 , 3 ) , E ( 3 , 4 ) and E ( 4 , 4 ) are 4, 4 n , 4 m 6 , 4 m + 2 n 6 and 6 m n 6 m 7 n + 7 , respectively. All of these results are summarized in Table 1.

3. Results

Theorem 1.
Randic index of coordination nanosheet, denoted by R α ( C [ m , n ] ) is given as:
R α ( C [ m , n ] ) = { 24 m n + ( 8 3 12 ) m + ( 4 3 + 4 6 28 ) n + 18 12 13                 i f   α = 1 2 3 2 m n + ( 1 + 4 3 6 ) m + 0.46 n + 0.0179                                                                                                 i f   α = 1 2
Proof. 
General Randic index of the coordination nanosheet is given by Equation (1) and can be computed as:
For α = 1 2 ,
R 1 2 ( C [ m , n ] ) = u v E d u d v = u v E ( 2 , 2 ) d u d v + u v E ( 2 , 3 ) d u d v + u v E ( 3 , 3 ) d u d v + u v E ( 3 , 4 ) d u d v + u v E ( 4 , 4 ) d u d v
Using values from Table 1, we get
R 1 2 ( C [ m , n ] ) = 4 + 4 n 2 × 2 + ( 4 m 6 ) 3 × 3   + ( 4 m + 2 n 6 ) 3 × 4 + ( 6 m n 6 m 7 n + 7 ) 4 × 4
which is simplified to
R 1 2 ( C [ m , n ] ) = 24 m n + ( 8 3 12 ) m + ( 4 3 + 4 6 28 ) n + 18 12 13  
For α = 1 2 ,
R 1 2 ( C [ m , n ] ) = u v E 1 d u d v = u v E ( 2 , 2 ) 1 d u d v + u v E ( 2 , 3 ) 1 d u d v + u v E ( 3 , 3 ) 1 d u d v + u v E ( 3 , 4 ) 1 d u d v + u v E ( 4 , 4 ) 1 d u d v
Again using Table 1, we get
R 1 2 ( C [ m , n ] ) = 4 1 2 × 2 + 4 n 1 2 × 3 + ( 4 m 6 ) 1 3 × 3 + ( 4 m + 2 n 6 ) 1 3 × 4 + ( 6 m n 6 m 7 n + 7 ) 1 4 × 4  
By simplification, we get
R 1 2 ( C [ m , n ] ) = 3 2 m n + ( 1 + 4 3 6 ) m + 0.46 n + 0.0179
Theorem 2.
First Zagreb index of nanosheet C [ m , n ] is given as:
M 1 ( C [ m , n ] ) = 48 m n + 4 m 22 n 6
Proof. 
We can compute the first Zagreb index of the nanosheet as defined in Equation (2) as:
M 1 ( C [ m , n ] ) = u v E [ d u + d v ] = u v E ( 2 , 2 ) [ d u + d v ] + u v E ( 2 , 3 ) [ d u + d v ] + u v E ( 3 , 3 ) [ d u + d v ] + u v E ( 3 , 4 ) [ d u + d v ] + u v E ( 4 , 4 ) [ d u + d v ]
Now, from Table 1, we get
M 1 ( C [ m , n ] ) = 4 ( 2 + 2 ) + 4 n ( 2 + 3 ) + ( 4 m 6 ) ( 3 + 3 ) + ( 4 m + 2 n 6 ) ( 3 + 4 ) + ( 6 m n 6 m 7 n + 7 ) ( 4 + 4 )
which can be simplified to
M 1 ( C [ m , n ] ) = 48 m n + 4 m 22 n 6
Theorem 3.
For nanosheet C [ m , n ] , the second Zagreb index is given as:
M 2 ( C [ m , n ] ) = 96 m n 12 m 64 n + 2
Proof. 
To compute the second Zagreb index of the coordination nanosheet, we use edge partition from Table 1 to split the relation in Equation (3) as:
M 2 ( C [ m , n ] ) = u v E [ d u d v ] = u v E ( 2 , 2 ) [ d u d v ] + u v E ( 2 , 3 ) [ d u d v ] + u v E ( 3 , 3 ) [ d u d v ] + u v E ( 3 , 4 ) [ d u d v ] + u v E ( 4 , 4 ) [ d u d v ]
After using values from Table 1, we have
M 2 ( C [ m , n ] ) = 4 ( 2 × 2 ) + 4 n ( 2 × 3 ) + ( 4 m 6 ) ( 3 × 3 ) + ( 4 m + 2 n 6 ) ( 3 × 4 ) + ( 6 m n 6 m 7 n + 7 ) ( 4 × 4 )
which yields
M 2 ( C [ m , n ] ) = 96 m n 12 m 64 n + 2
Theorem 4.
The ABC index of the nanosheet C [ m , n ] is given as:
A B C ( C [ m , n ] ) = 3.67 m n + 1.57 m 0.167 n 9.33
Proof. 
We can find the ABC index of coordination nanosheet as defined in Equation (4), which can be further expanded by the edge partition of Table 1:
A B C ( C [ m , n ] ) = u v E d u + d v 2 d u d v = u v E ( 2 , 2 ) d u + d v 2 d u d v + u v E ( 2 , 3 ) d u + d v 2 d u d v + u v E ( 3 , 3 ) d u + d v 2 d u d v + u v E ( 3 , 4 ) d u + d v 2 d u d v + u v E ( 4 , 4 ) d u + d v 2 d u d v
Using values from Table 1, we get
B C   ( C [ m , n ] = 4 2 + 2 2 2.2 + 4 n 2 + 3 2 2.3 + ( 4 m 6 )   3 + 3 2 3.3 + ( 4 m + 2 n 6 ) 3 + 4 2 3.4 + ( 6 m n 6 m 7 n + 7 ) 4 + 4 2 4.4
which further reduces to
A B C   C [ m , n ] = 3.67 m n + 1.57 m 0.167 n 9.33
Theorem 5.
Sum connectivity index SCI of C [ m , n ] is given as:
S C I ( C [ m , n ] ) = 2.12 m n + 1.02 m + 0.069 n 0.242
Proof. 
After using values from Table 1, we can calculate the sum connectivity index of a coordination nanosheet as defined in Equation (5):
S C I   ( C [ m , n ] ) = u v E   1 d u + d v = u v E ( 2 , 2 ) 1 d u + d v + u v E ( 2 , 3 ) 1 d u + d v + u v E ( 3 , 3 ) 1 d u + d v + u v E ( 3 , 4 ) 1 d u + d v + u v E ( 4 , 4 ) 1 d u + d v
Using the values from Table 1, we have
S C I   ( C [ m , n ] ) = 4 1 2 + 2   + 4 n 1 2 + 3   + ( 4 m 6 ) 1 3 + 3   + ( 4 m + 2 n 6 ) 1 3 + 4 + ( 6 m n 6 m 7 n + 7 ) 1 4 + 4  
Now, by simplifying,
S C I   ( C [ m , n ] ) = 2.12 m n + 1.02 m + 0.069 n 0.242
Theorem 6.
Geometric arithmetic index G A ( C [ m , n ] ) of such a coordination nanosheet, is given as:
G A ( C [ m , n ] ) = 6 m n + 1.95 m 0.101 n 0.94
Proof. 
Table 1 contains edge partition values; with these values the geometric arithmetic index of coordination nanosheet as defined in Equation (6) can be calculated as:
A ( C [ m , n ] ) = u v E 2 d u d v d u + d v = u v E ( 2 , 2 ) ( 2 d u d v d u + d v ) + u v E ( 2 , 3 ) ( 2 d u d v d u + d v ) + u v E ( 3 , 3 ) ( 2 d u d v d u + d v ) + u v E ( 3 , 4 ) ( 2 d u d v d u + d v ) + u v E ( 4 , 4 ) ( 2 d u d v d u + d v )
Now, from Table 1, we have
G A ( C [ m , n ] ) = 4 ( 2 2 × 2 2 + 2 ) + 4 n ( 2 2 × 3 2 + 3 ) + ( 4 m 6 ) ( 2 3 × 3 3 + 3 ) + ( 4 m + 2 n 6 ) ( 2 3 × 4 3 + 4 ) + ( 6 m n 6 m 7 n + 7 ) ( 2 4 × 4 4 + 4 )
Now, the simplified form is,
G A ( C [ m , n ] ) = 6 m n + 1.95 m 0.101 n 0.94
Theorem 7.
Hyper Zagreb index of the coordination nanosheet C [ m , n ] is given as:
H M ( C [ m , n ] ) = 348 m n 44 m 250 n + 2
Proof. 
Hyper Zagreb index of coordination nanosheet as defined in Equation (7) can be computed by using values from Table 1:
H M ( C [ m , n ] ) = u v E ( d u + d v ) 2 = u v E ( 2 , 2 ) ( d u + d v ) 2 + u v E ( 2 , 3 ) ( d u + d v ) 2 + u v E ( 3 , 3 ) ( d u + d v ) 2 + u v E ( 3 , 4 ) ( d u + d v ) 2 + u v E ( 4 , 4 ) ( d u + d v ) 2
From Table 1, we get
H M ( C [ m , n ] ) = 4 ( 2 + 2 ) 2 + 4 n ( 2 + 3 ) 2 + ( 4 m 6 ) ( 3 + 3 ) 2 + ( 4 m + 2 n 6 ) ( 3 + 4 ) 2 + ( 6 m n 6 m 7 n + 7 ) ( 4 + 4 ) 2
Now we have
H M ( C [ m , n ] ) = 384 m n 446 n 44 m + 2
Theorem 8.
Let us consider the coordination nanosheet C [ m , n ] , then first multiple Zagreb index is given as:
P M 1 ( C [ m , n ] ) = 256 × ( 5 ) 4 n × ( 6 ) ( 4 m 6 ) × ( 7 ) ( 4 m + 2 n 6 ) × ( 8 ) ( 6 m n 6 m 7 n + 7 )
Proof. 
Using the edge partition from Table 1, we can find the first multiple Zagreb index of the nanosheet as defined in Equation (9):
P M 1 ( C [ m , n ] ) = u v E [ d u + d v ] = u v E ( 2 , 2 ) [ d u + d v ] + u v E ( 2 , 3 ) [ d u + d v ] + u v E ( 3 , 3 ) [ d u + d v ] + u v E ( 3 , 4 ) [ d u + d v ] + u v E ( 4 , 4 ) [ d u + d v ]
Now from Table 1,
P M 1 ( C [ m , n ] ) = ( 2 + 2 ) 4 × ( 2 + 3 ) 4 n × ( 3 + 3 ) ( 4 m 6 ) × ( 3 + 4 ) ( 4 m + 2 n 6 ) × ( 4 + 4 ) ( 6 m n 6 m 7 n + 7 ) P M 1 ( C [ m , n ] ) = 256 × 5 4 n × 6 ( 4 m 6 ) × 7 ( 4 m + 2 n 6 ) × 8 ( 6 m n 6 m 7 n + 7 )
Theorem 9.
The second multiple Zagreb index of C [ m , n ] is given as:
P M 2 C [ m , n ] = 256 × ( 6 ) 4 n × ( 9 ) ( 4 m 6 ) × ( 12 ) ( 4 m + 2 n 6 ) × ( 16 ) ( 6 m n 6 m 7 n + 7 )
Proof. 
Edge partitions are given in Table 1, and with these values we can calculate the second multiple Zagreb index of coordination nanosheet as defined in Equation (9):
P M 2 C [ m , n ] = u v E [ d u × d v ] = u v E ( 2 , 2 ) [ d u d v ] + u v E ( 2 , 3 ) [ d u d v ] + u v E ( 3 , 3 ) [ d u d v ] + u v E ( 3 , 4 ) [ d u d v ] + u v E ( 4 , 4 ) [ d u d v ]
Using the values from Table 1, we get
P M 2 ( C [ m , n ] ) = 256 × ( 6 ) 4 n × ( 9 ) ( 4 m 6 ) × ( 12 ) ( 4 m + 2 n 6 ) × ( 16 ) ( 6 m n 6 m 7 n + 7 )

4. The M-Polynomial of Nanosheet

Let us consider a molecular graph G = ( V , E ) having n vertices and   m edges. Then the degree of vertex u V ( G ) is denoted by d u and is the number of vertices that are adjacent to u .
The M-polynomial [32] of a graph, G is defined as
M ( G , x , y ) = i y m i j ( G ) x i y j
where m i j ( G ) , ( i , j 1 ) denotes the number of edges e = u v of molecular graph G such that ( d u , d v ) = ( i , j ) .
Theorem 10.
Let G be the graph nanosheet C [ m , n ] , then M-polynomial of G is
M ( G , x , y ) = 4 x 2 y 2 + 4 n x 2 y 3 + ( 4 m 6 ) x 3 y 3 + ( 4 m + 2 n 6 ) x 3 y 4 + ( 6 m n 6 m 7 n + 7 ) x 4 y 4
Proof. 
By definition, M-polynomial is expressed as
M ( G , x , y ) = i y m i j ( G ) x i y j = 2 = 2 m 2 2 ( G ) x 2 y 2 + 2 3 m i j ( G ) x 2 y 3   + 3 = 3 m 33 ( G ) x 3 y 3   + 3 4 m 3 4 ( G ) x 3 y 4 + 4 = 4 m 44 ( G ) x 4 y 4 = u v E ( 2 , 2 ) m 22 ( G ) x 2 y 2 + u v E ( 2 , 3 ) m i j ( G ) x 2 y 3 + u v E ( 3 , 3 ) m 3 3 ( G ) x 3 y 3 + u v E ( 3 , 4 ) m 3 4 ( G ) x 3 y 4 + u v E ( 4 , 4 ) m 4 4 ( G ) x 4 y 4 M ( G , x , y ) = 4 x 2 y 2 + 4 n x 2 y 3 + ( 4 m 6 ) x 3 y 3 + ( 4 m + 2 n 6 ) x 3 y 4   + ( 6 m n 6 m 7 n + 7 ) x 4 y 4
By differentiating M-polynomial with respect to x , we get
D x = 8 x y 2 + 8 n x y 3 + 3 ( 4 m 6 ) x 2 y 3 + 3 ( 4 m + 2 n 6 ) x 2 y 4 + 4 ( 6 m n 6 m 7 n + 7 ) x 3 y 4 D x   x = 1 , y = 1   = 8 + 8 n + 3 ( 4 m 6 ) + 3 ( 4 m + 2 n 6 ) + 4 ( 6 m n 6 m 7 n + 7 ) D y = 8 x 2 y + 12 n x 2 y 2 + 3 ( 4 m 6 ) x 3 y 2 + 4 ( 4 m + 2 n 6 ) x 3 y 3 + 4 ( 6 m n 6 m 7 n + 7 )   x 4 y 3 D y   x = 1 ,   y = 1   = 8 + 12 n + 3 ( 4 m 6 ) + 4 ( 4 m + 2 n 6 ) + 4 ( 6 m n 6 m 7 n + 7 )
S x and S y are obtained by integrating M-polynomial with respect to x and y , respectively.
S x = 4 x 2 y 2 2 + 4 n x 2 y 3 2 +   ( 4 m 6 ) x 3 y 3 3 + ( 4 m + 2 n 6 ) x 3 y 4 3 + ( 6 m n 6 m 7 n + 7 )   x 4 y 4 4 S x   x = 1 ,   y = 1   = 2 + 2 n   + ( 4 m 6 ) 3   +   ( 4 m + 2 n 6 ) 3 + ( 6 m n 6 m 7 n + 7 ) 4 S y = 4 x 2 y 2 2 + 4 n x 2 y 3 3 + ( 4 m 6 )   x 3 y 3 3 + ( 4 m + 2 n 6 ) x 3 y 4 4 +   ( 6 m n 6 m 7 n + 7 ) x 4 y 4 4 S y   x = 1 ,   y = 1   = 2 + 4 n 3   + ( 4 m 6 ) 3   +   ( 4 m + 2 n 6 ) 4 + ( 6 m n 6 m 7 n + 7 ) 4
Figure 2 shows graphical interpretation of the M-polynomial of the nanosheet. Some topological indices, derived from M-polynomial, are described in Table 2 below.

5. Conclusions

For the nanosheets covered by C 3 and C 6 , various types of degree-based topological indices like Randic index variants of Zagreb indices, atom bond connectivity index, Geometric Arithmetic index, and sum connectivity index etc. are computed analytically. These results depend upon the structural connectivity of the chemical graph of the nanosheet. M-polynomial of the nanosheet is also computed, which provides an eloquent way to express and compute the degree-based topological indices. These findings are extremely helpful in the theoretical study of physical features, chemical reactivity, and biological activities of nanosheets. Topological indices computed in the study can be employed in quantitative structure activity relations and quantitative structure property relations of the nanosheets, and in turn, can be further helpful in understanding the physiochemical properties of the nanosheet.

Author Contributions

Conceptualization, N.I.; Formal analysis, S.N. and F.B.F.; Investigation, M.J.S.; Methodology, S.N. and F.S.; Writing—original draft, F.S.; Writing—review & editing, N.I.

Acknowledgments

The authors are thankful to the reviewers for their valuable comments and suggestions which helped a lot to improve the paper.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Kim, S.; Wang, H.; Lee, Y.M. 2D Nanosheets and Their Composite Membranes for Water, Gas, and Ion Separation. Angew. Chem. Int. Ed. 2019. [Google Scholar] [CrossRef]
  2. Kim, K.S.; Lee, H.J.; Lee, C.; Lee, S.K.; Jang, H.; Ahn, J.H.; Kim, J.H.; Lee, H.J. Chemical vapor deposition-grown graphene: The thinnest solid lubricant. ACS Nano 2011, 5, 5107–5114. [Google Scholar] [CrossRef]
  3. Peng, Y.T.; Wang, Z.G.; Zout, K. Friction and Wear Properties of Different Types of Graphene Nanosheets as Effective Solid Lubricants. Langmuir 2015, 31, 7782–7791. [Google Scholar] [CrossRef]
  4. Berman, D.; Erdemir, A.; Sumant, A.V. Graphene: A new emerging lubricant. Mater. Today 2014, 17, 31–42. [Google Scholar] [CrossRef]
  5. He, X.; Cao, L.; He, G.; Zhao, A.; Mao, X.; Huang, T.; Li, Y.; Wu, H.; Sun, J.; Jiang, Z. A highly conductive and robust anion conductor obtained via synergistic manipulation in intra-and inter-laminate of layered double hydroxide nanosheets. J. Mater. Chem A 2018, 6, 10277–10285. [Google Scholar] [CrossRef]
  6. Răileanu, M.; Crişan, M.; Niţoi, I.; Ianculescu, A.; Oancea, P.; Crişan, D.; Todan, L. TiO2-based nanomaterials with photocatalytic properties for the advanced degradation of xenobiotic compounds from water. A literature survey. Water Air Soil Pollut. 2013, 224, 1548–1593. [Google Scholar] [CrossRef]
  7. Bawa, R. Nanoparticle-based therapeutics in humans: A survey. Nanotech. L. Bus. 2008, 5, 135–155. [Google Scholar]
  8. Staedler, D.; Magouroux, T.; Hadji, R.; Joulaud, C.; Extermann, J.; Schwung, S.; Passemard, S.; Kasparian, C.; Clarke, G.; Gerrmann, M.; et al. Harmonic nanocrystals for biolabeling: A survey of optical properties and biocompatibility. ACS Nano 2012, 6, 2542–2549. [Google Scholar] [CrossRef]
  9. Jakubinek, M.B.; Martinez-Rubi, Y.; Ashrafi, B.; Guan, J.; Kim, K.S.; O’Neill, K.; Kingston, C.T.; Simard, B. Polymer nanocomposites incorporating boron nitride nanotubes. In Proceedings of the Nanotech 2015 Conference, Washington, DC, USA, 14–17 June 2015. [Google Scholar]
  10. Katritzky, A.R.; Wang, Y.; Sild, S.; Tamm, T.; Karelson, M. QSPR studies on vapor pressure, aqueous solubility, and the prediction of water–air partition coefficients. J. Chem. Inf. Comput. Sci. 1998, 38, 720–725. [Google Scholar] [CrossRef]
  11. Burello, E. Review of QSAR models for regulatory assessment of nanomaterials risks. NanoImpact 2017, 8, 48–58. [Google Scholar] [CrossRef]
  12. Fourches, D.; Tropsha, A. Quantitative nanostructure-activity relationships: From unstructured dataaa to predictive models for designing nanomaterials with controlled properties. Nanotoxicol. Prog. Toward Nanomed. 2015, 1–39. [Google Scholar]
  13. Burello, E.; Worth, A.P. QSAR modeling of nanomaterials. Wiley Interdiscip. Rev. Nanomed. Nanobiotechnol. 2011, 3, 298–306. [Google Scholar] [CrossRef]
  14. Randic, M. On Characterization of molecular branching. J. Am. Chem. Soc. 1975, 97, 6609–6615. [Google Scholar] [CrossRef]
  15. Bollobás, B.; Erdös, P. Graphs of extermal weights. Ars Comb. 1998, 50, 225–233. [Google Scholar]
  16. Gutman, I.; Trinajstić, N. Graph theory and moleculer orbitals. Total φ-eletrone energy of alternant hydrocarbons. Chem. Phys. Lett. 1972, 17, 535–538. [Google Scholar] [CrossRef]
  17. Estrada, E.; Torres, L.; Rodríguez, L.; Gutman, I. An atom-bond connectivity index: Modelling the enthalpy of formation of alkanes. Indian J. Chem. Sect. A Inorg. Phys. Theor. Anal. Chem. 1998, 37, 849–855. [Google Scholar]
  18. Zhou, B.; Trinajstić, N. On general sum-connectivity index. J. Math. Chem. 2010, 47, 210–218. [Google Scholar] [CrossRef]
  19. Vukičević, D.; Furtula, B. Topological index based on the ratios of geometrical and arithmetical means of end vertex degrees of edges. J. Math. Chem. 2009, 46, 1369–1376. [Google Scholar] [CrossRef]
  20. Shirdel, G.H.; Rezapour, H.; Sayadi, A.M. The hyper Zagreb index of graph operations. Iran. J. Math. Chem. 2013, 4, 213–220. [Google Scholar]
  21. Ghorbani, M.; Hosseinzade, M.A. A new version of Zagreb indices. Filomat 2012, 26, 93–100. [Google Scholar] [CrossRef]
  22. Jagadeesh, R.; Kanna, M.R.; Indumathi, R.S. Some results on topological indices of graphene. Nanomater. Nanotechnol. 2016, 6. [Google Scholar] [CrossRef]
  23. Chen, S.; Jang, Q.; Hou, Y. The Wiener and Schultz index of nanotubes covered by C4. Match Commun. Math. Comput. Chem. 2008, 59, 429–435. [Google Scholar]
  24. Hayat, S.; Imran, M. Computation of certain topological indices of nanotubes covered by C5 and C7. J. Comput. Theor. Nanosci. 2015, 12, 533–541. [Google Scholar] [CrossRef]
  25. Aslam, A.; Ahmad, S.; Gao, W. On certain topological indices of boron triangular nanotubes. Z. Nat. A 2017, 72, 711–716. [Google Scholar] [CrossRef]
  26. Idrees, N.; Saif, M.J.; Sadiq, A.; Rauf, A.; Hussain, F. Topological indices of H-naphtalenic nanosheet. Open Chem. 2018, 16, 1184–1188. [Google Scholar] [CrossRef]
  27. Munir, M.; Nazeer, W.; Rafique, S.; Kang, S. M-polynomial and degree-based topological indices of polyhex nanotubes. Symmetry 2016, 8, 149. [Google Scholar] [CrossRef]
  28. Gao, W.; Wang, W.; Farahani, M.R. Topological indices study of molecular structure in anticancer drugs. J. Chem. 2016. [Google Scholar] [CrossRef]
  29. Hayat, S.; Imran, M. On degree based topological indices of certain nanotubes. J. Comput. Nanosci. 2015, 12, 1599–1605. [Google Scholar] [CrossRef]
  30. Yang, H.; Rashid, M.A.; Ahmad, S.; Khan, S.S.; Siddiqui, M.K. On molecular descriptors of face-centered cubic lattice. Processes 2019, 7, 280. [Google Scholar] [CrossRef]
  31. Tan, C.; Cao, X.; Wu, X.; He, Q.; Yang, J.; Zhang, X.; Chen, J.; Zhao, W.; Han, S.; Nam, G.; et al. Recent advances in ultrathin two-dimensional nanomaterials. Chem. Rev. 2017, 117, 6226–6227. [Google Scholar] [CrossRef]
  32. Deutsch, E.; Deutsch, S. M-polynomial and degree based topological indices. Iran. J. Math. Chem. 2015, 6, 93–102. [Google Scholar]
Figure 1. Chemical graph of nanosheet C[6,5] with five rows and six hexagons in each row.
Figure 1. Chemical graph of nanosheet C[6,5] with five rows and six hexagons in each row.
Processes 07 00462 g001
Figure 2. The graph of M-polynomial of coordination nanosheet.
Figure 2. The graph of M-polynomial of coordination nanosheet.
Processes 07 00462 g002
Table 1. Edge partition of coordination nanosheet C [ m , n ] .
Table 1. Edge partition of coordination nanosheet C [ m , n ] .
Type of Edges E ( 2 , 2 ) E ( 2 , 3 ) E ( 3 , 3 ) E ( 3 , 4 ) E ( 4 , 4 )
( d u , d v )
uv E ( C [ m , n ] )
(2,2)(2,3)(3,3)(3,4)(4,4)
Number of edges4 4 n 4 m 6 4 m + 2 n 6 6 m n 6 m 7 n + 7
Table 2. The relation between topological indices and M-polynomial.
Table 2. The relation between topological indices and M-polynomial.
Topological Index f ( x , y ) Derivation   from   M ( G , x , y )
1st Zagreb index x + y ( D x + D y )   M ( G , x , y ) x = 1 , y = 1
2nd Zagreb index x y ( D x D y )   M ( G , x , y ) x = 1 , y = 1
Randic index 1 x y ( S x S y )   M ( G , x , y ) x = 1 , y = 1
D x = ( f ( x , y ) ) x , D y = ( f ( x , y ) ) y , S x = 0 x f ( t , y ) t   d t , and S y = 0 y f ( x , t ) t d t , J = f ( x , x ) .

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Back to TopTop