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Article

Characterizations of Chemical Networks Entropies by K-Banhatii Topological Indices

1
Institute of Mathematics, Khawaja Fareed University of Engineering & Information Technology, Abu Dhabi Road, Rahim Yar Khan 64200, Pakistan
2
Department of Mathematics and Statistics, College of Science, De La Salle University, 2401 Taft Avenue, Malate, Manila 1004, Metro Manila, Philippines
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Department of Mathematics, The Islamia University Bahawalpur Rahim Yar Khan Campus, Rahim Yar Khan 64200, Pakistan
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Department of Mathematics and Statistics Quaid-e-Awam University of Engineering, Science and Technology, Sakrand Road, Nawabshah 67480, Sindh, Pakistan
5
Faculty of Education, Yuzuncu Yil University, Van 65090, Turkey
6
Department of Mathematics, Al-Qunfudah University College, Umm Al-Qura University, Mecca, Saudi Arabia
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Department of Mechanical Engineering, College of Engineering in Wadi Alddawasir, Prince Sattam bin Abdulaziz University, Saudi Arabia
8
Production Engineering and Mechanical Design Department, Faculty of Engineering, Mansoura University, Mansoura P.O. Box 35516, Egypt
*
Authors to whom correspondence should be addressed.
Submission received: 2 November 2022 / Revised: 21 December 2022 / Accepted: 26 December 2022 / Published: 3 January 2023
(This article belongs to the Topic Molecular Topology and Computation)

Abstract

:
Entropy is a thermodynamic function in physics that measures the randomness and disorder of molecules in a particular system or process based on the diversity of configurations that molecules might take. Distance-based entropy is used to address a wide range of problems in the domains of mathematics, biology, chemical graph theory, organic and inorganic chemistry, and other disciplines. We explain the basic applications of distance-based entropy to chemical phenomena. These applications include signal processing, structural studies on crystals, molecular ensembles, and quantifying the chemical and electrical structures of molecules. In this study, we examine the characterisation of polyphenylenes and boron ( B 12 ) using a line of symmetry. Our ability to quickly ascertain the valences of each atom, and the total number of atom bonds is made possible by the symmetrical chemical structures of polyphenylenes and boron B 12 . By constructing these structures with degree-based indices, namely the K Banhatti indices, R e Z G 1 -index, R e Z G 2 -index, and R e Z G 3 -index, we are able to determine their respective entropies.

1. Introduction

In mathematical chemistry, topological indices are numerical values that describe the topology of molecular structures. The chemical process conceptual framework is a significant area of applied mathematics. This theory can be used to model issues in the real world. Since their inception, chemical networks have drawn the attention of researchers because of their widespread applications. The correlation coefficient (r) between the physicochemical characteristics and topological indices is determined in order to assess the utility of a topological index to forecast the physicochemical behavior of a chemical compound [1,2]. Additionally, it falls within a class of challenging chemical graph theory applications for precise molecular issue resolutions. In the fields of chemical sciences and chemical graph theory, this theory is crucial. The QSAR/QSPR analysis included physiochemical properties and topological indices such as the 1st multiple Zagreb index, 2nd multiple Zagreb index, and hyper Zagreb index [3,4]. Recently, Ali et al. defined the atom–bond sum–connectivity index in [5].
Let G ( V G , E G ) be a graph, with the vertices and edges denoted by V G and E G , respectively. In chemical graph theory, a molecular graph is a simple connected graph that contains chemical atoms and bonds, which are commonly referred to as atoms and atom-bonds, respectively [6,7].
The valency of atom bonds (line segments) and a few Banhatti indices, each of which had the following description [8], was used by Kulli to begin constructing valency-based topological indices in 2016 [9,10,11].
The 1st and 2nd K-Banhatti indices are as follows, respectively:
B 1 ( G ) = a i , a j E G ( d a i + d a j ) & B 2 ( G ) = a i , a j E G ( d a i × d a j )
The 1st and 2nd hyper K-Banhatti indices are as follows, respectively:
H B 1 ( G ) = a i , a j E G ( d a i + d a j ) 2 & H B 2 ( G ) = a i , a j E G ( d a i × d a j ) 2
The 1st and 2ndK-generalized Banhatti indices are as follows, respectively:
G B 1 ( G ) = a i , a j E G ( d a i + d a j ) α & G B 2 ( G ) = a i , a j E G ( d a i × d a j ) α
The redefined Zagreb indices R e Z G 1 , R e Z G 2 , and R e Z G 3 were 1st proposed by Ranjini [12] in 2013:
R e Z G 1 = a i , a j E G d a i + d a j d a i × d a j & R e Z G 2 = a i , a j E G d a i × d a j d a i + d a j .
The 3rd redefined Zagreb index is defined as
R e Z G 3 = a i , a j E G ( d a i × d a j ) ( d a i + d a j )
Entropy is the measurement of the amount of thermal energy per unit of temperature in a system that cannot be used for productive labour. Entropy is a measure of a system’s molecular disorder or unpredictability since work is produced by organised molecular motion, see new works on graph theory in [13,14]. Entropy was initially discussed by Shannon in his well-known [15] from 1948. The entropy of a probability distribution measures the unpredictable nature of information content or the uncertainty of a system. Entropy was then used to analyse chemical networks and graphs in order to comprehend the structural information contained within these networks. Recently, graph entropies have become more well-liked in a variety of academic disciplines, including biology, chemistry, ecology, and sociology. Graph theory and network theory have both undertaken substantial study on invariants, which are utilised as information functionals in science and have been around for a long time. The degree of every atom is vitally crucial [16,17,18]. The following sections will discuss graph entropy measures that have been applied to analyse biological and chemical networks in chronological order for further information [19].
In this article, we construct the boron B 12 and polyphenylenes P [ s , t ] . We determine the K-Banhatti entropies, redefined 1st, 2nd and 3rd Zagreb entropies by using K-Banhatti indices [20,21,22], 1st Zagreb index, 2nd Zagreb index, 3rd Zagreb index and the concept of entropy from Shazia Manzoor’s article [23] and Ghani et al. [24,25]. Many researchers discussed several aspects of distance-based entropies in [26,27,28,29,30,31,32,33].

Entropy Related to Valency-Based Indices

The entropy of an edge-weighted graph G is defined in [34], which was published in 2009. Ghani et al. defined the modified definition of entropy in [35]. A network with lines that are weighted has the equation G = ( V G , E G ) , μ ( a i a j ) ) , where V G , E G , and the vertex set, edge set, and edge–weight of edge ( a i a j ) are each represented by μ ( a i a j ) :
E N T μ ( G ) = a i , a j E G μ ( a i a j ) a i , a j E G μ ( a i a j ) log { μ ( a i a j ) a i , a j E G μ ( a i a j ) }
  • Entropy related to the 1st  K -Banhatti index
Assume μ ( a i a j ) = d a i + d a j . Then, the 1st K-Banhatti B 1 index (1) is thus provided by
B 1 ( G ) = a i , a j E G { d a i + d a j } = a i , a j E G μ ( a i a j ) .
By putting these parameters into Equation (6), the 1st K-Banhatti entropy is
E N T B 1 ( G ) = log ( B 1 ( G ) ) 1 B 1 ( G ) log { a i , a j E G [ d a i + d a j ] [ d a i + d a j ] } .
  • Entropy related to the 2nd K -Banhatti index
Assume μ ( a i a j ) = d a i × d a j . Then, the 2nd K-Banhatti B 2 index (1) is thus provided by
B 2 ( G ) = a i , a j E G { ( d a i × d a j ) } = a i , a j E G μ ( a i a j ) .
By putting these parameters into Equation (6), the 2nd K-Banhatti entropy is
E N T B 2 ( G ) = log ( B 2 ( G ) ) 1 B 2 ( G ) log { a i , a j E G [ d a i × d a j ] [ d a i × d a j ] } .
  • Entropy related to the 1st  K hyper Banhatti index
Assume μ ( a i a j ) = ( d a i + d a j ) 2 . Then, the 1st K hyper Banhatti H B 1 index (2) is thus provided by
H B 1 ( G ) = a i , a j E G { ( d a i + d a j ) 2 } = a i , a j E G μ ( a i a j ) .
By putting these parameters into Equation (6), the 1st K hyper Banhatti entropy is
E N T H B 1 ( G ) = log ( H B 1 ( G ) ) 1 H B 1 ( G ) log { a i , a j E G [ d a i + d a j ] 2 [ d a i + d a j ] 2 } .
  • Entropy related to the 2nd K hyper Banhatti index
Assume μ ( a i a j ) = ( d a i × d a j ) 2 . Then, the 2nd K hyper Banhatti index (2) is thus provided by
H B 2 ( G ) = a i , a j E G { ( d a i × d a j ) 2 } = a i , a j E G μ ( a i a j ) .
By putting these parameters into Equation (6), the 2nd K hyper Banhatti entropy is
E N T H B 2 ( G ) = log ( H B 1 ( G ) ) 1 H B 1 ( G ) log { a i , a j E G [ d a i × d a j ] 2 [ d a i × d a j ] 2 } .
  • The first redefined Zagreb entropy
Assume μ ( a i a j ) = d a i + d a j d a i d a j . Then, the 1st redefined Zagreb index (4) is thus provided by
R e Z G 1 = a i , a j E G { d a i + d a j d a i d a j } = a i , a j E G μ ( a i a j ) .
By putting these parameters into Equation (6), the 1st redefined Zagreb entropy is
E N T R e Z G 1 = log ( R e Z G 1 ) 1 R e Z G 1 log { a i , a j E G [ d a i + d a j d a i d a j ] [ d a i + d a j d a i d a j ] } .
  • The second redefined Zagreb entropy
Assume μ ( a i a j ) = d a i d v d a i + d a j . Then, the 2nd redefined index (4) is thus provided by
R e Z G 2 = a i , a j E G { d a i d a j d a i + d a j } = a i , a j E G μ ( a i a j ) .
By putting these parameters into Equation (6), the 2nd redefined Zagreb entropy is
E N T R e Z G 2 = log ( R e Z G 2 ) 1 R e Z G 2 log { a i , a j E G [ d a i d v d a i + d a j ] [ d a i d a j d a i + d a j ] } .
  • The third redefined Zagreb entropy
Assume μ ( a i a j ) = { ( d a i d a j ) ( d a i + d a j ) } . Then, the 3rd redefined Zagreb index (5) is thus provided by
R e Z G 3 = a i , a j E G { ( d a i d a j ) ( d u + d v ) } = a i , a j E G μ ( a i a j ) .
By putting these parameters into Equation (6), the 3rd redefined Zagreb entropy is
E N T R e Z G 3 = log ( R e Z G 3 ) 1 R e Z G 3 log { a i , a j E G [ ( d a i d a j ) ( d a i + d a j ) ] [ ( d a i d a j ) ( d a i + d a j ) ] } .

2. The Boron Network

We discuss the topological characteristics of boron B 12 in this article. The icosahedral network of boron B 12 has two dimensions. The existence of icosahedral structures containing B 12 was confirmed by a recent investigation of high-pressure solid boron [36]. However, prior theoretical and practical investigations of multiple boron clusters have demonstrated that the B 12 structure is unstable in the gas phase [37,38,39]. Figure 1 displays the molecular graph of boron B 12 . The dotted line in Figure 1 represents the line of symmetry; using this line, we can easily obtain the edge-partition of B 12 .

2.1. Results and Discussion

Now, ( s , t ) are the units of B 12 , where s and t show the number of B 12 in horizontal rows and vertical columns. In the boron network, the edge set E ( G ) is divided into seven groups based on the degree of each edge’s end vertices. The set that is disjoint is shown by the symbols ξ ( d ( u i ) , d ( v j ) ) . The 1st set that is disjoint is ξ ( 2 , 4 ) , the 2nd set that is disjoint is ξ ( 2 , 5 ) , the 3rd set that is disjoint is ξ ( 3 , 4 ) , the 4th set that is disjoint is ξ ( 3 , 5 ) , the 5th set that is disjoint is ξ ( 4 , 4 ) , the 6th set that is disjoint is ξ ( 4 , 5 ) , and the 7th set that is disjoint is ξ ( 5 , 5 ) .
From the symmetrical chemical structure of boron, B 12 , we find the edge-partition of B 12 easily:
ξ ( 2 , 4 ) = { e = a i a j , a i , a j E ( B 12 ) | d a i = 2 , d a j = 4 } = 2 ( s + t ) , ξ ( 2 , 5 ) = { e = a i a j , a i , a j E ( B 12 ) | d a i = 2 , d a j = 5 } = 2 ( s + t ) , ξ ( 3 , 4 ) = { e = a i a j , a i , a j E ( B 12 ) | d a i = 3 , d a j = 4 } = 3 s t + s + 5 , ξ ( 3 , 5 ) = { e = a i a j , a i , a j E ( B 12 ) | d a i = 3 , d a j = 5 } = 3 s t + 2 s + 3 t + 4 , ξ ( 4 , 4 ) = { e = a i a j , a i , a j E ( B 12 ) | d a i = 4 , d a j = 4 } = s + 2 t + 1 , ξ ( 4 , 5 ) = { e = a i a j , a i , a j E ( B 12 ) | d a i = 4 , d a j = 5 } = 9 s t + 7 s + 6 t + 5 , ξ ( 5 , 5 ) = { e = a i a j , a i , a j E ( B 12 ) | d a i = 5 , d a j = 5 } = 9 s t + 7 s + 7 t + 3 .
This partition provides
  • The 1st  K -Banhatti entropy of B 12
Assume that B 12 is an icosahedral network of boron. Then, by using Equation (1) and the edge-partition of B 12 , the 1st K-Banhatti index is
B 1 ( B 12 ) = 190 s + 190 t + 216 s t + 147
By using the edge-partition of B 12 and Equation (7) as described below,
E N T B 1 ( B 12 ) = log ( B 1 ) 1 B 1 log { E ( 2 , 4 ) ( d a i + d a j ) ( d a i + d a j ) × E ( 2 , 5 ) ( d a i + d a j ) ( d a i + d a j ) × E ( 3 , 4 ) ( d a i + d a j ) ( d a i + d a j ) × E ( 3 , 5 ) ( d a i + d a j ) ( d a i + d a j ) × E ( 4 , 4 ) ( d a i + d a j ) ( d a i + d a j ) × E ( 4 , 5 ) ( d a i + d a j ) ( d a i + d a j ) × E ( 5 , 5 ) ( d a i + d a j ) ( d a i + d a j ) = log ( 190 s + 190 t + 216 s t + 147 ) 1 190 s + 190 t + 216 s t + 147 log { 2 ( s + t ) ( 6 ) 6 × 2 ( s + t ) ( 7 ) 7 × ( 3 s t + s + 5 ) ( 7 ) 7 × ( 3 s t + 2 s + 3 t + 4 ) ( 8 ) 8 × ( s + 2 t + 1 ) ( 8 ) 8 × ( 9 s t + 7 s + 6 t + 5 ) ( 9 ) 9 × ( 9 s t + 7 s + 7 t + 3 ) ( 10 ) 10 } .
After simplifying the preceding expression, the following equation yields the precise value of the 1st K-Banhatti entropy:
E N T B 1 ( B 12 ) = log ( 190 s + 190 t + 216 s t + 147 ) 1 190 s + 190 t + 216 s t + 147 log { 2 ( s + t ) ( 6 ) 6 × ( 3 s t + 3 s + 2 t + 5 ) ( 7 ) 7 × ( 3 s t + 3 s + 5 t + 5 ) ( 8 ) 8 × ( 9 s t + 7 s + 6 t + 5 ) ( 9 ) 9 × ( 9 s t + 7 s + 7 t + 3 ) ( 10 ) 10 } .
  • The second K -Banhatti entropy of B 12
Assume that B 12 is an icosahedral network of boron. Then, by using Equation (1) and the edge-partition of B 12 , the 2nd K-Banhatti entropy index is
B 2 ( B 12 ) = 409 s + 408 t + 486 s t + 311
By using the edge-partition of B 12 and Equation (8) as described below,
E N T B 2 ( B 12 ) = log ( B 2 ) 1 B 2 log { E ( 2 , 4 ) ( d a i × d a j ) ( d a i × d a j ) × E ( 2 , 5 ) ( d a i × d a j ) ( d a i × d a j ) × E ( 3 , 4 ) ( d a i × d a j ) ( d a i × d a j ) × E ( 3 , 5 ) ( d a i × d a j ) ( d a i × d a j ) × E ( 4 , 4 ) ( d a i × d a j ) ( d a i × d a j ) × E ( 4 , 5 ) ( d a i × d a j ) ( d a i × d a j ) × E ( 5 , 5 ) ( d a i × d a j ) ( d a i × d a j ) } = log ( 409 s + 408 t + 486 s t + 311 ) 1 409 s + 408 t + 486 s t + 311 log { 2 ( s + t ) 8 8 × 2 ( s + t ) 10 10 × ( 3 s t + s + 5 ) 12 12 × ( 3 s t + 2 s + 3 t + 4 ) 15 15 × ( s + 2 t + 1 ) 16 16 × ( 9 s t + 7 s + 6 t + 5 ) 20 20 × ( 9 s t + 7 s + 7 t + 3 ) 25 25 } .
  • The 1st hyper K -Banhatti entropy of B 12
Assume that B 12 is an icosahedral network of boron. Then, by using the Equation (2) and the edge-partition of B 12 , the 1st K hyper Banhatti index is
H B 1 ( B 12 ) = 1678 s + 1676 t + 1968 s t + 1270
By using the edge-partition of B 12 and Equation (9) as described below;
E N T H B 1 ( B 12 ) = log ( H B 1 ) 1 H B 1 log { E ( 2 , 4 ) ( d a i + d a j ) 2 ( d a i + d a j ) 2 × E ( 2 , 5 ) ( d a i + d a j ) 2 ( d a i + d a j ) 2 × E ( 3 , 4 ) ( d a i + d a j ) 2 ( d a i + d a j ) 2 × E ( 3 , 5 ) ( d a i + d a j ) 2 ( d a i + d a j ) 2 × E ( 4 , 4 ) ( d a i + d a j ) 2 ( d a i + d a j ) 2 × E ( 4 , 5 ) ( d a i + d a j ) 2 ( d a i + d a j ) 2 × E ( 5 , 5 ) ( d a i + d a j ) 2 ( d a i + d a j ) 2 = log ( 1678 s + 1676 t + 1968 s t + 1270 ) 1 1678 s + 1676 t + 1968 s t + 1270 × log { 2 ( s + t ) 6 72 × 2 ( s + t ) 7 98 × ( 3 s t + s + 5 ) 7 98 × ( 3 s t + 2 s + 3 t + 4 ) 8 128 × ( s + 2 t + 1 ) 8 128 × ( 9 s t + 7 s + 6 t + 5 ) 9 162 × ( 9 s t + 7 s + 7 t + 3 ) 10 200 } .
After simplification, we obtain
E N T H B 1 ( B 12 ) = log ( 1678 s + 1676 t + 1968 s t + 1270 ) 1 1678 s + 1676 t + 1968 s t + 1270 × log { 2 ( s + t ) 6 72 × ( 3 s t + 3 s + 3 t + 5 ) 7 98 × ( 3 s t + 3 s + 5 t + 5 ) 8 128 × ( 9 s t + 7 s + 6 t + 5 ) 9 162 × ( 9 s t + 7 s + 7 t + 3 ) 10 200 } .
  • The 2nd hyper K -Banhatti entropy of B 12
Assume that B 12 is an icosahedral network of boron. Then, by using Equation (2) and the edge-partition of B 12 , the 2nd K hyper Banhatti index is
H B 2 ( B 12 ) = 8233 s + 8290 t + 9972 s t + 5151
By using the edge-partition of B 12 and Equation (10) as described below,
E N T H B 2 ( B 12 ) = log ( H B 2 ) 1 H B 2 log { E ( 2 , 4 ) ( d a i × d a j ) 2 ( d a i × d a j ) 2 × E ( 2 , 5 ) ( d a i × d a j ) 2 ( d a i × d a j ) 2 × E ( 3 , 4 ) ( d a i × d a j ) 2 ( d a i × d a j ) 2 × E ( 3 , 5 ) ( d a i × d a j ) 2 ( d a i × d a j ) 2 × E ( 4 , 4 ) ( d a i × d a j ) 2 ( d a i × d a j ) 2 × E ( 4 , 5 ) ( d a i × d a j ) 2 ( d a i × d a j ) 2 × E ( 5 , 5 ) ( d a i × d a j ) 2 ( d a i × d a j ) 2 = log ( 8233 s + 8290 t + 9972 s t + 5151 ) 1 8233 s + 8290 t + 9972 s t + 5151 × log { 2 ( s + t ) 8 128 × 2 ( s + t ) 10 200 × ( 3 s t + s + 5 ) 12 288 × ( 3 s t + 2 s + 3 t + 4 ) 15 450 × ( s + 2 t + 1 ) 16 512 × ( 9 s t + 7 s + 6 t + 5 ) 20 800 × ( 9 s t + 7 s + 7 t + 3 ) 25 1250 } .
  • The 1st redefined Zagreb entropy of B 12
Assume that B 12 is an icosahedral network of boron. Then, by using Equation (4) and the edge-partition of B 12 , the 1st redefined Zagreb index is
R e Z G 1 ( B 12 ) = 11 s t + 11 s + 11 t + 9
By using the edge-partition of B 12 and Equation (11) as described below,
E N T R e Z G 1 ( B 12 ) = log ( R e Z G 1 ) 1 R e Z G 1 log { E ( 2 , 4 ) [ d a i + d a j d a i d a j ] [ d a i + d a j d a i d v ] × E ( 2 , 5 ) [ d a i + d a j d a i d a j ] [ d a i + d v d a i d a j ] × E ( 3 , 4 ) [ d a i + d a j d a i d a j ] [ d a i + d a j d a i d a j ] × E ( 3 , 5 ) [ d a i + d a j d a i d a j ] [ d a i + d a j d a i d a j ] × E ( 4 , 4 ) [ d a i + d a j d a i d a j ] [ d a i + d a j d a i d a j ] × E ( 4 , 5 ) [ d a i + d a j d a i d a j ] [ d a i + d a j d a i d a j ] × E ( 5 , 5 ) [ d a i + d a j d a i d a j ] [ d a i + d a j d a i d a j ] } = log ( 11 s t + 11 s + 11 t + 9 ) 1 11 s t + 11 s + 11 t + 9 × log { 2 ( s + t ) ( 4 3 ) 4 3 × 2 ( s + t ) ( 7 10 ) 7 10 × ( 3 s t + s + 5 ) ( 7 12 ) 7 12 × ( 3 s t + 2 s + 3 t + 4 ) ( 8 15 ) 8 15 × ( s + 2 t + 1 ) ( 1 2 ) 1 2 × ( 9 s t + 7 s + 6 t + 5 ) ( 9 20 ) 9 20 × ( 9 s t + 7 s + 7 t + 3 ) ( 2 5 ) 2 5 } .
  • The 2nd redefined Zagreb entropy of B 12
Assume that B 12 is an icosahedral network of boron. Then, by using Equation (4) and the edge-partition of B 12 , the 2nd redefined Zagreb index is
R e Z G 2 ( B 12 ) = 1 504 ( 26847 s t + 23210 s + 23175 t + 18488 )
By using the edge-partition of B 12 and Equation (12) as described below,
E N T R e Z G 2 ( B 12 = log ( R e Z G 2 ) 1 R e Z G 2 log { E ( 2 , 4 ) [ d a i × d a j d a i + d a j ] [ d a i × d a j d a i + d a j ] × E ( 2 , 5 ) [ d a i × d a j d a i + d a j ] [ d a i × d v d a i + d a j ] × E ( 3 , 4 ) [ d a i × d a j d a i + d a j ] [ d a i × d a j d a i + d a j ] × E ( 3 , 5 ) [ d a i × d a j d a i + d a j ] [ d a i × d a j d a i + d a j ] × E ( 4 , 4 ) [ d a i × d a j d a i + d a j ] [ d a i × d a j d a i + d a j ] × E ( 4 , 5 ) [ d a i × d a j d a i + d a j ] [ d a i × d a j d a i + d a j ] × E ( 5 , 5 ) [ d a i × d a j d a i + d a j ] [ d a i × d a j d a i + d a j ] } = log 1 504 ( 26847 s t + 23210 s + 23175 t + 18488 ) 504 ( 26847 s t + 23210 s + 23175 t + 18488 ) × log { 2 ( s + t ) ( 4 3 ) 4 3 × 2 ( s + t ) ( 7 10 ) 7 10 × ( 3 s t + s + 5 ) ( 12 7 ) 12 7 × ( 3 s t + 2 s + 3 t + 4 ) ( 15 8 ) 15 8 × 4 ( s + 2 t + 1 ) × ( 9 s t + 7 s + 6 t + 5 ) ( 20 9 ) 20 9 × ( 9 s t + 7 s + 7 t + 3 ) ( 5 2 ) 5 2 } .
  • The 3rd redefined Zagreb entropy of B 12
Assume that B 12 is a hexagonal grid of benzenoid. Then, by using Equation (5) and the edge-partition of B 12 , the 3rd redefined Zagreb index is
R e Z G 3 ( B 12 ) = 4482 s t + 3698 s + 3682 t + 2678
Now, we compute the 3rd redefined Zagreb entropy by using the edge-partition of B 12 and Equation (13) as described below,
E N T R e Z G 3 ( B 12 ) = log ( R e Z G 3 ) 1 R e Z G 3 log { E ( 2 , 4 ) [ ( d a i d a j ) ( d a i + d a j ) ] [ d a i + d a j d a i d a j ] × E ( 2 , 5 ) [ ( d a i d a j ) ( d a i + d a j ) ] [ d a i + d v d a i d a j ] × E ( 3 , 4 ) [ d a i d a j ) ( d a i + d a j ] [ d a i d a j ) ( d a i + d a j ] × E ( 3 , 5 ) [ d a i d a j ) ( d a i + d a j ] [ d a i d a j ) ( d a i + d a j ] × E ( 4 , 4 ) [ d a i d a j ) ( d a i + d a j ] [ d a i d a j ) ( d a i + d a j ] × E ( 4 , 5 ) [ d a i d a j ) ( d a i + d a j ] [ d a i d a j ) ( d a i + d a j ] × E ( 5 , 5 ) [ d a i d a j ) ( d a i + d a j ] [ d a i d a j ) ( d a i + d a j ] } = log ( 4482 s t + 3698 s + 3682 t + 2678 ) 1 4482 s t + 3698 s + 3682 t + 2678 × log { 2 ( s + t ) 48 48 × 2 ( s + t ) 70 70 × ( 3 s t + s + 5 ) 84 84 × ( 3 s t + 2 s + 3 t + 4 ) 120 120 × ( s + 2 t + 1 ) 2 896 × ( 9 s t + 7 s + 6 t + 5 ) 180 180 × ( 9 s t + 7 s + 7 t + 3 ) 250 250 } .

2.2. Comparison of K-Banhatti and Redefined Zagreb Indices of B 12

Here, we present numerical and graphical comparison of K-Banhatti indices and redefined Zagreb indices of boron B 12 for s = 2 , 4 , 6 , 16 and t = 3 , 5 , 7 , , 17 , in Table 1 and Figure 2 respectively.

3. The Polyphenylenes Network

Polyphenylenes include benzenoid aromatic nuclei that are linked together by a carbon-carbon bond [40]. Polyphenylenes have been the subject of research for many years. Up until 1979, there was a lot of interest in polyphenylenes because of its thermal and thermo-oxidative stability. The quest for a single group of polymers that can be converted to another, such as an electrical insulator that can be transformed into an electrical conductor by utilizing doping with an electron acceptor or donor, is a key ongoing subject in polyphenylene [41].
Figure 3 for polyphenylenes P [ s , t ] has been shown.
In 2011, Zhen Zhou [42] indicated that two-dimensional polyphenylene is a conventional semiconductor with a large band gap and that the porous structure gives it a remarkable selectivity for H 2 permeability compared to C O 2 , C O , and C H 4 . This porous graphene, which has been tested, is likely to find use in a hydrogen-powered civilization. In Figure 3, the dot lines represent the line of symmetry, with 6 s ( t + 1 ) atoms on the left side and the same on the right. Here, in the P [ s , t ] , there are two sorts of atoms v i and a j such that d v i = 2 and d a j = 3 , where d v i and d a j mean the valency of atoms ∀ v i , v j P [ s , t ] . The order and size of P [ s , t ] , is
| P [ s , t ] | = 12 s ( t + 1 ) S ( P [ s , t ] ) = ( 30 t + 13 ) s t
From the symmetrical chemical structure of polyphenylene, P [ s , t ] , we find the edge-partition of P [ s , t ] easily. The edge partition of polyphenylenes P [ s , t ] is shown in Table 2.
  • Entropy related to the 1st  K -Banhatti index of P [ s , t ]
Assume that P [ s , t ] is a network of benzenoid aromatic nuclei in polyphenylenes. Equation (1) and Table 2 are then used to calculate the 1st K Banhatti index:
B 1 ( P [ s , t ] ) = 26 s + 42 t + 188 s t
By using Table 2 and Equation (7) as follows:
E N T B 1 ( P [ s , t ] ) = log ( B 1 ) 1 B 1 log { E ( 2 , 2 ) ( d a i + d a j ) ( d a i + d a j ) × E ( 2 , 3 ) ( d a i + d a j ) ( d a i + d a j ) × E ( 3 , 3 ) ( d a i + d a j ) ( d a i + d a j ) = log ( 26 s + 42 t + 188 s t ) 1 26 s + 42 t + 188 s t log { 4 ( 2 s t + t ) ( 4 ) 4 × 4 ( 6 s t + s t ) ( 5 ) 5 × ( 6 s t + s t ) ( 6 ) 6
After simplification, we obtain
E N T B 1 ( P [ s , t ] ) = log ( 26 s + 42 t + 188 s t ) 1 26 s + 42 t + 188 s t log { 356984 s t + 59156 s 58132 t } .
  • Entropy related to 2nd  K -Banhatti index of P [ s , t ]
Assume that P [ s , t ] is a network of benzenoid aromatic nuclei in polyphenylenes. Then, by using Equation (1) and Table 2, the 2nd K-Banhatti index is
B 2 ( P [ s , t ] ) = 33 s + 49 t + 230 s t
By using Table 2 and Equation (8) as described below:
E N T B 2 ( P [ s , t ] ) = log ( B 2 ) 1 B 2 log { E ( 2 , 2 ) ( d a i × d a j ) ( d a i × d a j ) × E ( 2 , 3 ) ( d a i × d a j ) ( d a i × d a j ) × E ( 3 , 3 ) ( d a i × d a j ) ( d a i × d a j ) } = log ( 33 s + 49 t + 230 s t ) 1 33 s + 49 t + 230 s t log { 4 ( 2 s t + t ) 4 4 × 4 ( 6 s t + s t ) 6 6 × ( 6 s t + s t ) 9 9 } .
  • Entropy related to the 1st  K hyper Banhatti index of P [ s , t ]
Assume that P [ s , t ] is a network of benzenoid aromatic nuclei in polyphenylenes. The 1st hyper Banhatti index is then determined using Equation (2) and Table 2
H B 1 ( P [ s , t ] ) = 8 ( 118 s t + 17 s + 25 t )
By using Table 2 and Equation (10) as described below,
E N T H B 1 ( P [ s , t ] ) = log ( H B 1 ) 1 H B 1 log { E ( 2 , 2 ) ( d a i + d a j ) 2 ( d a i + d a j ) 2 × E ( 2 , 3 ) ( d a i + d a j ) 2 ( d a i + d a j ) 2 × E ( 3 , 3 ) ( d a i + d a j ) 2 ( d a i + d a j ) 2 = log ( 8 ( 118 s t + 17 s + 25 t ) ) 1 8 ( 118 s t + 17 s + 25 t ) log { 4 ( 2 s t + t ) 4 32 × 4 ( 6 s t + s t ) 5 50 × ( 6 s t + s t ) 6 72
  • Entropy related to the 2nd  K hyper Banhatti index of P [ s , t ]
Assume that P [ s , t ] is a network of benzenoid aromatic nuclei in polyphenylenes. The 2nd K hyper Banhatti index is then calculated using the Equation (2) and Table 2:
H B 2 ( P [ s , t ] ) = 225 s + 289 t + 1478 s t
By using Table 2 and Equation (10) as described below,
E N T H B 1 ( P [ s , t ] ) = log ( H B 1 ) 1 H B 1 log { E ( 2 , 2 ) ( d a i + d a j ) 2 ( d a i + d a j ) 2 × E ( 2 , 3 ) ( d a i + d a j ) 2 ( d a i + d a j ) 2 × E ( 3 , 3 ) ( d a i + d a j ) 2 ( d a i + d a j ) 2 = log ( 225 s + 289 t + 1478 s t ) 1 225 s + 289 t + 1478 s t log { 4 ( 2 s t + t ) 4 32 × 4 ( 6 s t + s t ) 5 50 × ( 6 s t + s t ) 6 72
  • Entropy related to the 1st redefined Zagreb index of P [ s , t ]
Assume that P [ s , t ] is a network of benzenoid aromatic nuclei in polyphenylenes. The 1st redefined Zagreb index is then obtained by using Equation (4) and Table 2
R e Z G 1 ( P [ s , t ] ) = 8 ( 12 s t + s + 2 t )
By using Table 2 and Equation (11) as described below,
E N T R e Z G 1 ( P [ s , t ] ) = log ( R e Z G 1 ) 1 R e Z G 1 log { E ( 2 , 2 ) [ d a i + d a j d a i d a j ] [ d a i + d a j d a i d v ] × E ( 2 , 3 ) [ d a i + d a j d a i d a j ] [ d a i + d v d a i d a j ] × E ( 3 , 3 ) [ d a i + d a j d a i d a j ] [ d a i + d a j d a i d a j ] } = log 8 ( 12 s t + s + 2 t ) 1 8 ( 12 s t + s + 2 t ) log { 4 ( 2 s t + t ) × 4 ( 6 s t + s t ) ( 5 6 ) 5 6 × ( 6 s t + s t ) ( 2 3 ) 2 3 } .
  • Entropy related to the 2nd redefined Zagreb in the index of P [ s , t ]
Assume that P [ s , t ] is a network of benzenoid aromatic nuclei in polyphenylenes. The 2nd redefined Zagreb index is then obtained by utilizing Equation (4) and Table 2:
R e Z G 2 ( P [ s , t ] ) = 158 s t + 13 s + 27 t
By using Table 2 and Equation (12) as described below,
E N T R e Z G 2 ( P [ s , t ] ) = log ( R e Z G 2 ) 1 R e Z G 2 log { E ( 2 , 2 ) [ d a i d a j d a i + d a j ] [ d a i d a j d a i + d a j ] × E ( 2 , 3 ) [ d a i d a j d a i + d a j ] [ d a i d a j d u + d a j ] × E ( 3 , 3 ) [ d a i d a j d a i + d a j ] [ d a i d a j d a i + d a j ] } = log ( 158 s t + 13 s + 27 t ) 1 158 s t + 13 s + 27 t log { 4 ( 2 s t + t ) × 4 ( 6 s t + s t ) ( 6 5 ) 6 5 × ( 6 s t + s t ) ( 3 2 ) 3 2 } .
  • Entropy related to the 3rd redefined Zagreb index of P [ s , t ]
Assume that P [ s , t ] is a network of benzenoid aromatic nuclei in polyphenylenes. The 3rd redefined Zagreb index is then obtained using Equation (5) and Table 2
R e Z G 3 ( P [ s , t ] ) = 1172 s t + 174 s 110 t
By using Table 2 and Equation (13) as described below,
E N T R e Z G 3 ( P [ s , t ] ) = log ( R e Z G 3 ) 1 R e Z G 3 log { E ( 2 , 2 ) [ ( d u d a j ) ( d u + d a j ) ] [ ( d a i d a j ) ( d a i + d a j ) ] × E ( 2 , 3 ) [ ( d a i d a j ) ( d a i + d a j ) ] [ ( d u d a j ) ( d a i + d a j ) ] × E ( 3 , 3 ) [ ( d a i d a j ) ( d a i + d a j ) ] [ ( d a i d a j ) ( d a i + d a j ) ] } = log ( 1172 s t + 174 s 110 t ) 1 1172 s t + 174 s 110 t log { 4 ( 2 s t + t ) 2 64 × 4 ( 6 s t + s t ) 30 30 × ( 6 s t + s t ) 54 54 } .

Comparison of K-Banhatti and Redefined Zagreb Indices of P ( s , t )

In this section, we present numerical and graphical comparison of B 1 , B 2 3 , H B 1 , H B 1 , R e Z G 1 , R e Z G 2 and R e Z G 3 , of polyphenylenes P ( s , t ) for s , t = 1 , 2 , 3 , , 11 , in Table 3 and Figure 4 respectively.

4. Conclusions

We investigated a variety of imperative molecules, namely boron B 12 and poly-phenylenes P [ s , t ] and estimated their valency-based K Banhatti indices using four K Banhatti polynomials by a set partition using an atom-bonds approach. The acquired results are valuable in anticipating numerous molecular features of chemical substances, such as boiling point, electron energy, pi, pharmaceutical configuration, and many more concepts. Using Shannon’s entropy and Chen et al. entropy’s definitions, we looked into the graph entropies connected to a novel information function and assessed the link between degree-based topological indices and degree-based entropies in this work. Industrial chemistry has a strong foundation in the concept of distance-based entropy. It is employed to determine the electronic structure, signal processing, physicochemical reactions, and complexity of molecules and molecular ensembles. Together with chemical structure, thermodynamic entropy, energy, and computer sciences, the K-Banhatti entropy can be crucial in linking different fields and serving as the basis for future interdisciplinary research. We intend to extend this idea to different chemical structures in the future, opening up new directions for study in this area. Furthermore, we can compute more results by using the valency-based technique for these symmetrical chemical structures.

Author Contributions

Conceptualization, M.U.G. and F.J.H.C.; methodology, M.U.G.; software, F.J.H.C.; validation, S.D. and S.A.; formal analysis, S.A.; investigation, M.U.G.; resources, A.M.G.; data curation, F.J.H.C.; writing—review and editing, S.D.; visualization, M.C.; supervision, F.J.H.C. and S.A.; project administration, F.M.A. All authors have read and agreed to the published version of the manuscript.

Funding

This study is supported via funding from Prince Sattam bin Abdulaziz University project number (PSAU/2023/R/1444).

Data Availability Statement

No data were used to support this study.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Boron B 12 .
Figure 1. Boron B 12 .
Symmetry 15 00143 g001
Figure 2. Graphical representation indices of B 12 .
Figure 2. Graphical representation indices of B 12 .
Symmetry 15 00143 g002
Figure 3. 2D-polyphenylenes molecular.
Figure 3. 2D-polyphenylenes molecular.
Symmetry 15 00143 g003
Figure 4. Graphical representation of indices P ( s , t ) .
Figure 4. Graphical representation of indices P ( s , t ) .
Symmetry 15 00143 g004
Table 1. Comparison of K-Banhatti and redefined Zagreb indices of B 12 .
Table 1. Comparison of K-Banhatti and redefined Zagreb indices of B 12 .
( s , t ) B 1 B 2 HB 1 HB 2 ReZG 1 ReZG 2 ReZG 3
(2, 3)2393526921,462106,319130586.3548,012
(4, 5)617713,70755,722278,9733281516.20125,520
(6, 7)11,68926,033105,726531,4036142872.20238,884
(8, 9)18,92942,247171,474863,6099884654.36388,104
(10, 11)27,89762,349252,9661,275,59114506862.68573,180
(12, 13)38,59386,339350,2021,767,34920009497.16794,112
(14, 15)51,017114,217463,1822,338,883263812,557.801,050,900
(16, 17)65,169145,983591,9062,990,193336416,044.601,343,544
Table 2. Edge-partition of polyphenylenes P [ s , t ] .
Table 2. Edge-partition of polyphenylenes P [ s , t ] .
Edge-Partition E ( 2 2 ) E ( 2 3 ) E ( 3 3 )
Number of bonds 4 ( 2 s + t ) 4 ( 6 s t + s t ) ( 6 s t + s t )
Table 3. K-Banhatti and redefined Zagreb indices of P ( s , t ) .
Table 3. K-Banhatti and redefined Zagreb indices of P ( s , t ) .
( s , t ) B 1 B 2 HB 1 HB 2 ReZG 1 ReZG 2 ReZG 3
(1, 1)256312128019921201981236
(2, 2)8881084444869404327124816
(3, 3)18962316950414,844936154210,740
(4, 4)3280400816,44825,7041632268819,008
(5, 5)5040616025,28039,5202520415029,620
(6, 6)7176877236,00056,2923600592842,576
(7, 7)968811,84448,60876,0204872802257,876
(8, 8)12,57615,37663,10498,704633610,43275,520
(9, 9)15,84019,36879,488124,344799213,15895,508
(10, 10)19,48023,82097,760152,940984016,200117,840
(11, 11)23,49628,732117,920184,49211,88019,558142,516
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Ghani, M.U.; Campena, F.J.H.; Ali, S.; Dehraj, S.; Cancan, M.; Alharbi, F.M.; Galal, A.M. Characterizations of Chemical Networks Entropies by K-Banhatii Topological Indices. Symmetry 2023, 15, 143. https://0-doi-org.brum.beds.ac.uk/10.3390/sym15010143

AMA Style

Ghani MU, Campena FJH, Ali S, Dehraj S, Cancan M, Alharbi FM, Galal AM. Characterizations of Chemical Networks Entropies by K-Banhatii Topological Indices. Symmetry. 2023; 15(1):143. https://0-doi-org.brum.beds.ac.uk/10.3390/sym15010143

Chicago/Turabian Style

Ghani, Muhammad Usman, Francis Joseph H. Campena, Shahbaz Ali, Sanaullah Dehraj, Murat Cancan, Fahad M. Alharbi, and Ahmed M. Galal. 2023. "Characterizations of Chemical Networks Entropies by K-Banhatii Topological Indices" Symmetry 15, no. 1: 143. https://0-doi-org.brum.beds.ac.uk/10.3390/sym15010143

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