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Article

Computational Analysis of Imbalance-Based Irregularity Indices of Boron Nanotubes

1
School of artificial Intelligence and big data, Hefei University, Hefei 230601, China
2
Department of Mathematics, Division of Science and Technology, University of Education, Lahore 54000, Pakistan
3
Center for Excellence in Molecular Biology, Punjab University Lahore, Lahore 53700, Pakistan
4
School of Mathematics and Physics, Anhui Jianzhu University, Hefei 230601, China
5
School of Mathematics, Southeast University, Nanjing 210096, China
*
Author to whom correspondence should be addressed.
Processes 2019, 7(10), 678; https://doi.org/10.3390/pr7100678
Submission received: 18 August 2019 / Revised: 18 September 2019 / Accepted: 26 September 2019 / Published: 1 October 2019
(This article belongs to the Section Materials Processes)

Abstract

:
Molecular topology provides a basis for the correlation of physical as well as chemical properties of a certain molecule. Irregularity indices are used as functions in the statistical analysis of the topological properties of certain molecular graphs and complex networks, and hence help us to correlate properties like enthalpy, heats of vaporization, and boiling points etc. with the molecular structure. In this article we are interested in formulating closed forms of imbalance-based irregularity measures of boron nanotubes. These tubes are known as α-boron nanotube, triangular boron nanotubes, and tri-hexagonal boron nanotubes. We also compare our results graphically and come up with the conclusion that alpha boron tubes are the most irregular with respect to most of the irregularity indices.

1. Introduction

Mathematical chemistry is evidently proving useful with efficient and time saving tools to assist in determining the properties of chemical compounds without going into laborious laboratory details. Topological indices are the structure preserving maps which capture some key combinatorial and topological aspects of the structure and determine properties of chemical compounds without the help of quantum mechanics as the final output [1,2]. Among such invariants, most are known as degree-based indices, and are widely used nowadays, [3,4,5,6,7]. Some relations of topological indices with properties of compounds can be seen in [1,2,3,4,5,6]. In short, these indices actually forecast some mathematical formulation of the properties of the substances under discussion. Wiener used these indices to guess the boiling points of parafin [4] and Randic determined the degree of molecular branching [3]. Estrada determined energies and atom bond connectives of branched alkanes [5] and determined the enthalpy of formation of alkanes using atom-bond connectivity index [6]. Molecular connectivity and its relationship with structure analysis have been given by Kier et al. [7,8].
Nanomaterials at present are being used in as electronics and cosmetics. Many other sectors, for example, polymeric composite materials, are carrying out a lot of scientific and technological works, and there are also plans for a wide range of projects involving nanomaterials. It has caught tremendous attention and interest for the promotion of nanostructured compounds. All this is because of the unique properties that are at hand, offering possibilities of multi-functionality, reduction of thickness, and a great spectrum of applications relating to technology. Indeed, recent works on nanoparticles showcase potential risks of nano-object releases and highlight the interest in the management of nano-risk in workplaces by making possible the removal of some lab tests in a research process [9]. For example, many studies highlight nano-object emissions due to nanomaterial use [10,11,12]. Cases of nano-object exposure in the field of occupational hygiene at workplaces have been reported [13]. These aspects are addressed according to metrological challenges related to particle characterization [14].
In QSAR (Quantitative structure-activity relationship), scientists use topological indices to study relationships of different quantities with chemical properties of nanomaterials. A broad class of the indices is the irregularity indices of the molecular graph of a certain molecule. Irregularity indices have been selected to study the topological pattern of the molecular structure recently [15,16,17,18,19,20,21,22,23,24]. Term network irregularity was put forth by Collatz and Sinogowitz in 1957 [18]. Actually, these indices are used in complex networks which represent disparate systems. Key topological features possessed by these systems are small-worldness, network motifs, scale-freeness, and self-similarity, [19,20,21]. In a nutshell, the power-law degree distribution of complex networks contrasts sharply with the regularity observed in random models like the one proposed by Erdös and Rényi [23]. Reti et al. used these indices to test the physiochemical properties like entropy, entropy of vaporization, boiling point, standard enthalpy of vaporization, and the acentric factor of octane isomers [15]. In fact, they provided that these properties of four octane isomers can be predicted with good accuracy by using irregularity indices. Estrada et al. analyzed the irregularity of 10 protein-protein interaction networks in different organisms ranging from 50 to 3000 nodes [16]. They, in fact, proved that these networks attain higher irregularity than a regular random network. A graph is said to be regular if all its vertices are of same degree, otherwise it is irregular. However, one is deeply interested to know the degree of irregularity in the graph [23,24,25,26,27]. These structures are used as long infinite chains macromolecules in chemistry and related areas. Total irregularity index has been introduced recently and some well stabilized graphs have been studied. Due to the ever-increasing interest in the complexity of molecular structures, one is interested to know the degree of complexity in the underlined structure. One way is to compute the irregularity indices of the structure [24,25,26,27]. Bell discussed the most irregular graphs according to some irregularity measures [24]. Gutman gave some fundamental results for irregularity indices of some graphs in [26].
In this article, we are interested in characteristic study of irregularity determinants of three types nanotube structures. The first nanotube is the tri-hexagonal boron nanotube, and the other two are boron nanotubes which can be formulated easily on to the structure of carbon nanotubes. Boron nanotubes are considered as an effective replacement of carbon nanotubes because of their high conductivity and thermal properties [28,29,30,31,32,33,34]. Figure 1 presents a tabular view of these tubes. Figure 1a is carbon nanotubes, whereas Figure 1b is triangular boron nanotube structure, and Figure 1c is α-boron nanotubes.
These tubes and their computational aspects have been treated in [29] by Manuel et al. Because of increasing interest and the development of new nanomaterials, computations have minimized the burden of experimental labor to some extent. Amongst the nanomaterials, nanocrystals, nanowires, and nanotubes constitute three major categories, the last two being one-dimensional [29,30]. Boron nanotubes are becoming increasingly interesting because of their remarkable properties like structural stability, work function, transport properties, and electronic structure. Triangular Boron is derived from a triangular sheet as shown in Figure 1. The first boron nanotubes were created in 2004 from a buckled triangular latticework [30,31,32,33,34]. Another well-known type, α-boron, is derived from α-sheet. Irrespective of their structures and chiralities, both types are more conductive than carbon nanotubes. Figure 2 presents molecular graphs of these three tubes in the same order as given in order of Figure 1.
As far as the structure of both tubes is concerned, the α-Boron nanotube is more complicated than the triangular boron nanotubes with the addition of an extra atom to the center of some of the hexagons. The authors proved that this is the most stable known theoretical structure for a boron nanotube. They also showed that, with this pattern, boron nanotubes should have variable electrical properties—wider ones would be metallic conductors [30,31,32,33,34].
Other degree-based indices are also recently studied on a large scale. Several authors preferred to use the approach of a general polynomial, and to then compute these indices using variety of differential and integral operators. The authors computed M-polynomials and different famous degree based indices for different graphs, [35,36,37,38,39]. Other different popular indices and their relations have been showcased in [36,37,38].

2. Preliminaries and Notations

Let G be a simple connected graph with vertex V, edge set E, du and dv the degree of vertices u and v. A topological invariant is an isomorphism of the graph that preserves the topology of the graph. A graph is said to be regular if every vertex of the graph has the same degree. A topological invariant is called an irregularity index if this index vanishes for a regular graph, and is non-zero for a non-regular graph. Regular graphs have been extensively investigated, particularly in mathematics. Their applications in chemical graph theory came to be known after the discovery of nanotubes and fullerenes. Paul Erdos emphasized this in the study of irregular graphs for the first time in history in [40]. In the Second Krakow Conference on Graph Theory (1994), Erdos officially posed it as an open problem, “The determination of extreme size of highly irregular graphs of given order” [41]. Since then, irregular graphs and the degree of irregularity have become one of the core open problems of graph theory. A graph in which each vertex has a different degree then the other vertices is known as a perfect graph. The authors of [42] demonstrated that no graph is perfect. The graphs lying in between are called quasi-perfect graphs, in which all except two vertices have different degrees [41]. Simplified ways of expressing the irregularities are irregularity indices. These irregularity indices have been studied recently in a novel way [43,44]. The first such irregularity index was introduced in [45]. Most of these indices used the concept of the imbalance of an edge defined as i m b a l l u v = | d u d v | , [46,47]. The Albertson index, AL(G), was defined by Alberston in [47] as A L ( G ) = U V E | d u d v | . In this index, the imbalance of edges is computed. The irregularity index IRL(G) and IRLU(G) is introduced by Vukicevic and Gasparov, [47] as I R L ( G ) = U V E | l n d u l n d v | , and I R L U ( G ) = U V E | d u d v | m i n ( d u , d v ) . Recently, Abdoo et al. introduced the new term “total irregularity measure of a graph G”, which is defined as, [46,48,49], I R R t ( G ) = 1 2 U V E | d u d v | . Recently, Gutman et al. introduced the IRF(G) irregularity index of the graph G, which is described as I R F ( G ) = U V E ( d u d v ) 2 in [50]. The Randic index itself is directly related to an irregularity measure, which is described as I R A ( G ) = U V E ( d u 1 2 d v 1 2 ) 2 in [50]. Further irregularity indices of similar nature can be traced in [50] in detail. These indices are given as I R D I F ( G ) = U V E | d u d v d v d v | , I R L F ( G ) = U V E | d u d v | ( d u d v ) , L A ( G ) = 2 U V E | d u d v | ( d u + d v ) , I R D 1 = U V E l n { 1 + | d v d v | } , I R G A ( G ) = U V E l n d u + d v 2 ( d u d v ) , and I R B ( G ) = U V E ( d u 1 2 d v 1 2 ) 2 .
Recently, Zahid et al. computed the irregularity indices of a nanotube [51]. Gao et al. recently computed irregularity measures of some dendrimer structures in [52] and molecular structures in [53]. These structures are used as long infinite chain macromolecules in chemistry and related areas.
Hussain et al. computed some irregularity indices of benzenoid systems [54] and dendrimers in [55]. Liu et al. computed Zagreb indices and multiplicative Zagreb indices of Eulerian graphs in [56].
In the current article, we are interested in finding the degree of imbalance-based irregularity of the three boron nanotubes discussed in Figure 3, Figure 4 and Figure 5. The main motivation comes from the fact that graphs of the irregularity indices show close accurate results about properties like entropy, standard enthalpy, vaporization, and acentric factors of octane isomers [52]. The molecular pattern and topology of these three boron nanotubes are shown in these figures.

3. Main Results

In this section we put together our main computational results. We start with the tri-hexagonal boron nanotube structure C N T H [ p , q ] .
Theorem 1.
For tri-hexagonal boron nanotube C N T H [ p , q ] , for positive values of p and q, we have
1. 
I R D I F ( C N T H [ p , q ] ) = 37 10 q + 37 10 p q
2. 
A L ( C N T H [ p , q ] ) = 6 q + 12 p q
3. 
I R L ( C N T H [ p , q ] ) = 1.7260887 q + 2.677722616 p q
4. 
I R L U ( C N T H [ p , q ] ) = 5 2 q + 3 p q
5. 
I R L U ( C N T H [ p , q ] ) = 2 15 3 5 5 q + 6 5 5 p q
6. 
I R F ( C N T H [ p , q ] ) = 18 q + 12 p q
7. 
I R L A ( C N T H [ p , q ] ) = 5 3 q + 8 3 p q
8. 
I R D 1 ( C N T H [ p , q ] ) = 2.432790649 q + 8.317766167 p q
9. 
I R A ( C N T H [ p , q ] ) = 0.8489489603 q + 27 12 5 2 p q
10. 
I R G A ( C N T H [ p , q ] ) = 0.1563480034 q + 0.0745351199 p q
11. 
I R B ( C N T H [ p , q ] ) = 1.189831306 q + 0.66873708 p q
Proof. 
In order to prove the above theorem we have to consider Figure 3. Following Table 1 contains information for the distribution of edges into different classes.
Now using above Table 1 and definitions we have,
  • I R D I F ( G ) = U V E | d u d v d v d v |
    I R D I F ( C N T H [ p , q ] ) = 6 q | 5 3 3 5 | + 2 p q q | 4 4 4 4 | + 6 q ( 2 p 1 ) | 5 4 4 5 | + 4 p q | 5 5 5 5 | = 6 q | 5 3 3 5 | + 6 q ( 2 p 1 ) | 5 4 4 5 |
  • A L ( G ) = U V E | d u d v |
    A L ( C N T H [ p , q ] ) = 6 q | 5 3 | + 2 p q q | 4 4 | + 6 q ( 2 p 1 ) | 5 4 | + 4 p q | 5 5 | = 12 p + 6 q ( 2 p 1 )
  • I R L ( G ) = U V E | l n d u l n d v |
    I R L ( C N T H [ p , q ] ) = 6 q | l n 5 l n 3 | + 2 p q q | l n 4 l n 4 | + 6 q ( 2 p 1 ) | l n 5 l n 4 | + 4 p q | l n 5 l n 5 | = 6 q l n 5 3 + 6 q ( 2 p 1 ) l n 5 4
  • I R L U ( G ) = U V E | d u d v | m i n ( d u d v )
    I R L U ( C N T H [ p , q ] ) = 6 q | 5 3 | 3 + 2 p q q | 4 4 | 4 + 6 q ( 2 p 1 ) | 5 4 | 4 + 4 p q | 5 5 | 5 = 12 q 3 + 6 q ( 2 p 1 ) 4
  • I R L U ( G ) = U V E | d u d v | ( d u d v )
    I R L U ( C N T H [ p , q ] ) = 6 q | 5 3 | 15 + 2 p q q | 4 4 | 16 + 6 q ( 2 p 1 ) | 5 4 | 20 + 4 p q | 5 5 | 25 = 6 q 15 + 6 q ( 2 p 1 ) 20
  • I R F ( G ) = U V E ( d u d v ) 2
    I R F ( C N T H [ p , q ] ) = 6 q ( 5 3 ) 2 + 2 p q q ( 4 4 ) 2 + 6 q ( 2 p 1 ) ( 5 4 ) 2 + 4 p q ( 5 5 ) 2 = 24 q + 6 q ( 2 p 1 )
  • I R L A ( G ) = 2 U V E | d u d v | ( d u + d v )
    I R L A ( C N T H [ p , q ] ) = 2 [ 6 q | 5 3 | 8 + 2 p q q | 4 4 | 8 + 6 q ( 2 p 1 ) | 5 4 | 9 + 4 p q | 5 5 | 10 ] = 24 q 8 + 12 q ( 2 p 1 ) 9
  • I R D 1 = U V E l n { 1 + | d v d v | }
    I R D 1 ( C N T H [ p , q ] ) = 6 q l n { 1 + | 5 3 | } + 2 p q q l n { 1 + | 4 4 | } + 6 q ( 2 p 1 ) l n { 1 + | 5 4 | } + 4 p q l n { 1 + | 5 5 | } = 6 q l n 3 + 6 q ( 2 p 1 ) l n 2
  • I R A ( G ) = U V E ( d u 1 2 d v 1 2 ) 2
    I R A ( C N T H [ p , q ] ) = 6 q ( 1 5 1 3 ) 2 + 2 p q q ( 1 4 1 4 ) 2 + 6 q ( 2 p 1 ) ( 1 5 1 4 ) 2 + 4 p q ( 1 5 1 5 ) 2 = 6 q ( 1 5 1 3 ) 2 + 6 q ( 2 p 1 ) ( 1 5 1 4 ) 2
  • I R G A ( G ) = U V E l n d u + d v 2 ( d u d v )
    I R G A ( C N T H [ p , q ] ) = 6 q l n 5 + 3 2 15 + 2 p q q l n 4 + 4 2 16 + 6 q ( 2 p 1 ) l n 5 + 4 2 20 + 4 p q l n 5 + 5 2 25 = 6 n l n 5 + 3 2 15 + 6 n ( 2 m 1 ) l n 5 + 4 2 20
  • I R B ( G ) = U V E ( d u 1 2 d v 1 2 ) 2
    I R B ( C N T H [ p , q ] ) = 6 q ( 5 3 ) 2 + 2 p q q ( 4 4 ) 2 + 6 q ( 2 p 1 ) ( 5 4 ) 2 + 4 p q ( 5 5 ) 2 = 6 q ( 5 3 ) 2 + 6 q ( 2 p 1 ) ( 5 4 ) 2
Following Table 2 contains some calculated results of these indices for C N T H [ p , q ] for different values of p and q where p > 0. □
Now, we move towards triangular boron nanotubes. We represent an arbitrary structure of this nanotube with B N T α [ p ,   q ] with p and q be the numbers of boron atoms in a row and a column respectively.
Theorem 2.
Let B N T α [ p ,   q ] with p and q both positive, then
1. 
I R D I F ( B N T α [ p ,   q ] ) = 127 30 p + 33 30 p 2
2. 
A L ( B N T α [ p ,   q ] ) = 10 p + 3 p 2
3. 
I R L ( B N T α [ p ,   q ] ) = 2.0866 p + 0.5469646 p 2
4. 
I R L U ( B N T α [ p ,   q ] ) = 5 2 p + 3 5 p 2
5. 
I R L U ( B N T α [ p ,   q ] ) = 10 6 + 3 5 15 p + 30 10 p 2
6. 
I R F ( B N T α [ p ,   q ] ) = 18 p + 3 p 2
7. 
I R L A ( B N T α [ p ,   q ] ) = 92 45 p + 6 11 p 2
8. 
I R D 1 ( B N T α [ p ,   q ] ) = 5.7807435 p + 2.07944 p 2
9. 
I R A ( B N T α [ p ,   q ] ) = 0.0392463138 p + 11 2 30 10 p 2
10. 
I R G A ( B N T α [ p ,   q ] ) = 0.0940665090 p + 0.01244820422 p 2
11. 
I R B ( B N T α [ p ,   q ] ) = 0.9196202955 p + 33 6 30 p 2
Proof. 
We prove these results on the same lines as then in the case of Theorem 1. In order to prove the above theorem we have to consider the following edge partition of the B N T α [ p ,   q ] in the Table 3 as depicted in the Figure 4.
Now, using above Table 3 and definitions we have,
  • I R D I F ( G ) = U V E | d u d v d v d v |
    I R D I F ( B N T α [ p , q ] ) = 3 p | 4 4 4 4 | + 2 p | 5 4 4 5 | + 4 p | 6 4 4 6 | + p 2 ( 3 q 11 ) | 5 5 5 5 | + 3 p 2 | 6 5 5 6 | + ( p + q 3 ) | 6 6 6 6 | = 127 30 p + 33 30 p 2
  • A L ( G ) = U V E | d u d v |
    A L ( B N T α [ p , q ] ) = 3 p | 4 4 | + 2 p | 5 4 | + 4 p | 6 4 | + p 2 ( 3 q 11 ) | 5 5 | + 3 p 2 | 6 5 | + ( p + q 3 ) | 6 6 | = 3 p 2 + 10 p
  • I R L ( G ) = U V E | l n d u l n d v |
    I R L ( B N T α [ p , q ] ) = 3 p | l n 4 l n 4 | + 2 p | l n 5 l n 4 | + 4 p | l n 6 l n 4 | + p 2 ( 3 q 11 ) | l n 5 l n 5 | + 3 p 2 | l n 6 l n 5 | + ( p + q 3 ) | l n 6 l n 6 | = 2 p l n 5 4 + 4 p l n 6 4 + 3 p 2 l n 6 5
  • I R L U ( G ) = U V E | d u d v | m i n ( d u d v )
    I R L U ( B N T α [ p , q ] ) = 3 p | 4 4 | 4 + 2 p | 5 4 | 4 + 4 p | 6 4 | 4 + p 2 ( 3 q 11 ) | 5 5 | 5 + 3 p 2 | 6 5 | 5 + ( p + q 3 ) | 6 6 | 6 = 2 p 1 4 + 4 p 1 2 + 3 p 2 1 5
  • I R L U ( G ) = U V E | d u d v | ( d u d v )
    I R L U ( B N T α [ p , q ] ) = 3 p | 4 4 | 16 + 2 p | 5 4 | 20 + 4 p | 6 4 | 24 + p 2 ( 3 q 11 ) | 5 5 | 25 + 3 p 2 | 6 5 | 30 + ( p + q 3 ) | 6 6 | 36 = 2 p 20 + 8 p 24 + 3 p 2 30
  • I R F ( G ) = U V E ( d u d v ) 2
    I R F ( B N T α [ p , q ] ) = 3 p ( 4 4 ) 2 + 2 p ( 5 4 ) 2 + 4 p ( 6 4 ) 2 + p 2 ( 3 q 11 ) ( 5 5 ) 2 + 3 p 2 ( 6 5 ) 2 + ( p + q 3 ) ( 6 6 ) 2 = 18 p + 3 p 2
  • I R L A ( G ) = 2 U V E | d u d v | ( d u + d v )
    I R L A ( B N T α [ p , q ] ) = 2 [ 3 p | 4 4 | ( 8 ) + 2 p | 5 4 | ( 9 ) + 4 p | 6 4 | ( 10 ) + p 2 ( 3 q 11 ) | 5 5 | ( 10 ) + 3 p 2 | 6 5 | ( 11 ) + ( p + q 3 ) | 6 6 | ( 12 ) ] = 92 p 45 + 6 p 2 11
  • I R D 1 = U V E l n { 1 + | d v d v | }
    I R D 1 = 3 p l n { 1 + | 4 4 | } + 2 p l n { 1 + | 5 4 | } + 4 p l n { 1 + | 6 4 | } + p 2 ( 3 q 11 ) l n { 1 + | 5 5 | } + 3 p 2 l n { 1 + | 6 5 | } + ( p + q 3 ) l n { 1 + | 6 6 | } = 2 p l n ( 2 ) + 4 p l n ( 3 ) + 3 p 2 l n ( 2 )
  • I R A ( G ) = U V E ( d u 1 2 d v 1 2 ) 2
    I R A ( B N T α [ p , q ] ) = 3 p ( 1 4 1 4 ) 2 + 2 p ( 1 5 1 4 ) 2 + 4 p ( 1 6 1 4 ) 2 + p 2 ( 3 q 11 ) ( 1 5 1 5 ) 2 + 3 p 2 ( 1 6 1 5 ) 2 + ( p + q 3 ) ( 1 6 1 6 ) 2 = 2 p ( 1 5 1 4 ) 2 + 4 p ( 1 6 1 4 ) 2 + 3 p 2 ( 1 6 1 5 ) 2
  • I R G A ( G ) = U V E l n d u + d v 2 ( d u d v )
    I R G A ( B N T α [ p , q ] ) = 3 p l n 4 + 4 2 ( 16 ) + 2 p l n 5 + 4 2 ( 20 ) + 4 p l n 6 + 4 2 ( 24 ) + p 2 ( 3 q 11 ) l n 5 + 5 2 ( 25 ) + 3 p 2 l n 6 + 5 2 ( 30 ) + ( p + q 3 ) l n 6 + 6 2 ( 36 ) = 2 p l n 9 2 ( 20 ) + 4 p l n 10 2 ( 24 ) + 3 p 2 l n 11 2 ( 30 )
  • I R B ( G ) = U V E ( d u 1 2 d v 1 2 ) 2
    I R B ( B N T α [ p , q ] ) = 3 p ( 4 4 ) 2 + 2 p ( 5 4 ) 2 + 4 p ( 6 4 ) 2 + p 2 ( 3 q 11 ) ( 5 5 ) 2 + 3 p 2 ( 6 5 ) 2 + ( p + q 3 ) ( 6 6 ) 2 = 2 p ( 5 4 ) 2 + 4 p ( 6 4 ) 2 + 3 p 2 ( 6 5 ) 2
Following Table 4 computes some values of the above indices of B N T α [ p , q ] for p and q both positive. □
The following theorem contains results about triangular boron nanotubes B N T t [ p ,   q ] .
Theorem 3.
Let B N T t [ p ,   q ] be the triangular boron nanotube with p and q both positive, we have
1. 
I R D I F ( B N T t [ p ,   q ] ) = 5 p
2. 
A L ( B N T t [ p ,   q ] ) = 12 p
3. 
I R L ( B N T t [ p ,   q ] ) = 2.432790 p
4. 
I R L U ( B N T t [ p ,   q ] ) = 3 p
5. 
I R L U ( B N T t [ p ,   q ] ) = 6 p
6. 
I R F ( B N T t [ p ,   q ] ) = 24 p
7. 
I R L A ( B N T t [ p ,   q ] ) = 24 10 p
8. 
I R D 1 ( B N T t [ p ,   q ] ) = 6.591673732 p
9. 
I R A ( B N T t [ p ,   q ] ) = 5 2 6 2 p
10. 
I R G A ( B N T t [ p ,   q ] ) = 0.122465 p
11. 
I R B ( B B N T t [ p ,   q ] ) = 60 24 6 p
Proof. 
In order to prove the above theorem, we have to consider Figure 5 and Table 5 which contain facts relating edge distributions of this graph.
Now using above Table 5 and definitions we have,
  • I R D I F ( G ) = U V E | d u d v d v d v |
    I R D I F ( B N T t [ p , q ] ) = 3 p | 4 4 4 4 | + 6 p | 6 4 4 6 | + p 2 ( 9 q 24 ) | 6 6 6 6 | = 6 p | 6 4 4 6 |
  • A L ( G ) = U V E | d u d v |
    A L ( B N T t [ p , q ] ) = 3 p | 4 4 | + 6 p | 6 4 | + p 2 ( 9 q 24 ) | 6 6 | = 12 p
  • I R L ( G ) = U V E | l n d u l n d v |
    I R L ( B N T t [ p , q ] ) = 3 p | l n 4 l n 4 | + 6 p | l n 6 l n 4 | + p 2 ( 9 q 24 ) | l n 6 l n 6 | = 6 p l n 6 4
  • I R L U ( G ) = U V E | d u d v | m i n ( d u d v )
    I R L U ( B N T t [ p , q ] ) = 3 p | 4 4 | 4 + 6 p | 6 4 | 4 + p 2 ( 9 q 24 ) | 6 6 | 6 = 3 p
  • I R L U ( G ) = U V E | d u d v | ( d u d v )
    I R L U ( B N T t [ p , q ] ) = 3 p | 4 4 | 16 + 6 p | 6 4 | 24 + p 2 ( 9 q 24 ) | 6 6 | 36 = 12 p 24
  • I R F ( G ) = U V E ( d u d v ) 2
    I R F ( B N T t [ p , q ] ) = 3 p ( 4 4 ) 2 + 6 p ( 6 4 ) 2 + p 2 ( 9 q 24 ) ( 6 6 ) 2 = 24 p
  • I R L A ( G ) = 2 U V E | d u d v | ( d u + d v )
    I R L A ( B N T t [ p , q ] ) = 2 [ 3 p | 4 4 | ( 8 ) + 6 p | 6 4 | ( 10 ) + p 2 ( 9 q 24 ) | 6 6 | ( 12 ) ] = 24 p 10
  • I R D 1 = U V E l n { 1 + | d v d v | }
    I R D 1 = 3 p l n { 1 + | 4 4 | } + 6 p l n { 1 + | 6 4 | } + p 2 ( 9 q 24 ) l n { 1 + | 6 6 | } = 6 p l n 3
  • I R A ( G ) = U V E ( d u 1 2 d v 1 2 ) 2
    I R A ( B N T t [ p , q ] ) = 3 p ( 1 4 1 4 ) 2 + 6 p ( 1 6 1 4 ) 2 + p 2 ( 9 q 24 ) ( 1 6 1 6 ) 2 = 6 p ( 1 6 1 4 ) 2
  • I R G A ( G ) = U V E l n d u + d v 2 ( d u d v )
    I R G A ( B N T t [ p , q ] ) = 3 p l n 4 + 4 2 ( 16 ) + 6 p l n 6 + 4 2 ( 24 ) + p 2 ( 9 q 24 ) l n 6 + 6 2 ( 36 ) = 6 p l n 10 2 ( 24 )
  • I R B ( G ) = U V E ( d u 1 2 d v 1 2 ) 2
    I R B ( B N T t [ p , q ] ) = 3 p ( 4 4 ) 2 + 6 p ( 6 4 ) 2 + p 2 ( 9 q 24 ) ( 6 6 ) 2 = 6 p ( 6 4 ) 2
The following Table 6 provides some values of the irregularity indices of B N T t [ p , q ] for positive values of p and q. □

4. Conclusions, Graphical Analysis and Discussions

In this part we give a graphical analysis of the irregularity indices of three tubes, and compare the results presented in the above section. We use two types of graphs as tools for our comparisons. One is the 2D graph where the dependence of a certain irregularity index is plotted against one parameter of the structure p or q while other is kept fixed. Second tool is the 3D graph where dependence of a certain irregularity index is plotted against both parameter of the structure and obtained surface represent the trends of irregularity index against both parameters p and q at the same time. We use blue color to show the surface of irregularity indices of alpha (α)-boron nanotube, black color to show the surface of irregularity index of triangular boron nanotube system, and green color to show the surface of irregularity indices of tri-hexagonal boron nanotube structure C N T H [ p , q ] . All surfaces plotted in the Figure 6, Figure 7, Figure 8, Figure 9, Figure 10 and Figure 11 below show that the alpha boron tube structure is the most irregular whereas triangular boron tubes are somewhat in the middle and tri-hexagonal boron nanotube structure C N T H [ p , q ] is the most regular structure with respect to most irregular indices discussed above.
However, the associated surfaces for IRA and IRGA behave differently, as shown in the following Figure 12 and Figure 13.
In the following Figure 14, we demonstrate 2D graph for q = 1 and change p. Here, red color shows the behavior of the irregularity index for the alpha boron nanotube. Figure 15 shows that alpha boron nanotube becomes rapidly irregular with respect to change in p than triangular and carbon boron tubes.
This is just a model of the behavior of almost all irregularity indices described above.
Only one of the irregularity indices, namely IRA, shows a different trend. For some values of p, triangular boron becomes more irregular than alpha boron nanotubes.
Finally, we conclude that alpha boron tubes are the most irregular in pattern, as compared to the other two structures. These facts contribute towards the complexity and the pattern of structures, and can be effectively used in nano-engineering and nano-devices.

Author Contributions

M.M. gave the idea, H.A. and S.R. wrote the article. B.Y. and J.-B.L. computed edited and verified the results.

Funding

This work is partially supported by Major University Science Research Project of Anhui Province (KJ2016A605) and Science Research Talents Foundation of Hefei University (13RC02).

Conflicts of Interest

Authors declare no conflict of interests.

References

  1. Rucker, G.; Rucker, C. On topological indices, boiling points, and cycloalkanes. J. Chem. Inf. Comput. Sci. 1999, 39, 788–802. [Google Scholar] [CrossRef]
  2. Gutman, I.; Polansky, O.E. Mathematical Concepts in Organic Chemistry; Springer: New York, NY, USA, 1986. [Google Scholar]
  3. Randic, M. On the characterization of molecular branching. J. Am. Chem. Soc. 1975, 97, 6609–6615. [Google Scholar] [CrossRef]
  4. Wiener, H. Structural determination of paraffin boiling points. J. Am. Chem. Soc. 1947, 69, 17–20. [Google Scholar] [CrossRef] [PubMed]
  5. Estrada, E. Atomic bond connectivity and the energetic of branched alkanes. Chem. Phys. Lett. 2008, 463, 422–425. [Google Scholar] [CrossRef]
  6. Estrada, E.; Torres, L.; Rodríguez, L.; Gutman, I. An atom–bond connectivity index: Modeling the enthalpy of formation of alkanes. Indian J. Chem. 1998, 37, 849–855. [Google Scholar]
  7. Kier, L.B.; Hall, L.H. Molecular Connectivity in Chemistry and Drug Research; Academic Press: New York, NY, USA, 1976. [Google Scholar]
  8. Kier, L.B.; Hall, L.H. Molecular Connectivity in Structure Activity Analysis; Wiley: New York, NY, USA, 1986. [Google Scholar]
  9. ISO. TS 12901-2 Nanotechnologies—Occupational Risk Management Applied to Engineered Nanomaterials—Part 2: Use of the Control Banding Approach; The International Organization for Standardization: Geneva, Switzerland, 2014. [Google Scholar]
  10. Warheit, D.B. Hazard and risk assessment strategies for nanoparticle exposures: How far have we come in the past 10 years? F1000Research 2018, 7, 376. [Google Scholar] [CrossRef] [PubMed]
  11. Morgeneyer, M.; Aguerre-Chariol, O.; Bressot, C. Stem imaging to characterize nanoparticle emissions and help to design nanosafer paints. Chem. Eng. Res. Des. 2018, 136, 663–674. [Google Scholar] [CrossRef]
  12. Salmatonidis, A.; Viana, M.; Pérez, N.; Alastuey, A.; de la Fuente, G.F.; Angurel, L.A.; Sanfélix, V.; Monfort, E. Nanoparticle formation and emission during laser ablation of ceramic tiles. J. Aerosol Sci. 2018, 126, 152–168. [Google Scholar] [CrossRef] [Green Version]
  13. Bressot, C.; Shandilya, N.; Jayabalan, T.; Fayet, G.; Voetz, M.; Meunier, L.; Le Bihan, O.; Aguerre-Chariol, O.; Morgeneyer, M. Exposure assessment of nanomaterials at production sites by a short time sampling (sts) approach strategy and first results of measurement campaigns. Process Saf. Environ. Prot. 2018, 116, 324–332. [Google Scholar] [CrossRef]
  14. Morgeneyer, M.; Ramirez, A.; Smith, S.M.; Tweedie, R.; Heng, J.; Maass, S.; Bressot, C. Particle technology as a uniform discipline? Towards a holistic approach to particles, their creation, characterization, handling and processing! Chem. Eng. Res. Des. 2019, 146, 162–165. [Google Scholar] [CrossRef]
  15. Reti, T.; Sharfdini, R.; Dregelyi-Kiss, A.; Hagobin, H. Graph irregularity indices used as molecular discriptors in QSPR studies. MATCH Commun. Math. Comput. Chem. 2018, 79, 509–524. [Google Scholar]
  16. Estrada, E. Randic index, irregularity and complex biomolecular networks. Acta Chim. Slov. 2010, 57, 597–603. [Google Scholar] [PubMed]
  17. Strogatz, S.H. Exploring complex networks. Nature 2001, 410, 268–276. [Google Scholar] [CrossRef] [Green Version]
  18. Von Collatz, L.; Sinogowitz, U. Spektren Endlicher Grafen. In Abhandlungen aus dem Mathematischen Seminar der Universitat Hamburg; Springer-Verlag: Hamberg, Germany, 1957; Volume 21, pp. 63–77. [Google Scholar]
  19. Dorogovtsev, S.N.; Mendes, J.F.F. Evolution of networks with aging of sites. Phys. Rev. E 2000, 62, 1842–1845. [Google Scholar] [CrossRef] [Green Version]
  20. Krapivsky, P.L.; Redner, S.; Leyvraz, F. Connectivity of growing random networks. Phys. Rev. Lett. 2000, 85, 4629–4632. [Google Scholar] [CrossRef]
  21. West, D.B. An Introduction to Graph Theory; Prentice-Hall: Upper Saddle River, NJ, USA, 1996. [Google Scholar]
  22. Albert, R.; Jeong, H.; Barabasi, A.L. Error and attack tolerance of complex networks. Nature 2000, 406, 378–382. [Google Scholar] [CrossRef] [Green Version]
  23. Erdös, P.; Rényi, A. On the evolution of random graphs. Publ. Math. Inst. Hung. Acad. Sci. 1960, 5, 17–61. [Google Scholar]
  24. Bell, F.K. A note on the irregularity of graphs. Linear Algebra Appl. 1992, 161, 45–54. [Google Scholar] [CrossRef] [Green Version]
  25. Albertson, M.O. The irregularity of a graph. Ars Comb. 1997, 46, 219–225. [Google Scholar]
  26. Gutman, I. Irregularity of molecular graphs. Kragujev. J. Sci. 2016, 38, 71–78. [Google Scholar] [CrossRef]
  27. Dimitrov, D.; Reti, T. Graphs with equal irregularity indices. Acta Polytech. Hung. 2014, 11, 41–57. [Google Scholar]
  28. Bezugly, V.J.; Kunstmann Stok, G.B.; Frauenheim, T.; Niehaus, T.; Cuniberti, G. Highly conductive boron nanotubes: Transport properties, work functions, and structural stabilities. ACS Nano 2011, 5, 4997–5005. [Google Scholar] [CrossRef] [PubMed]
  29. Manuel, P. Computational aspects of carbon and boron nanotubes. Molecules 2010, 15, 8709–8722. [Google Scholar] [CrossRef] [PubMed]
  30. Yang, X.; Ding, Y.; Ni, J. Ab initio prediction of stable boron sheets and boron nanotubes: Structure, stability, and electronic properties. Phys. Rev. B 2008, 77, 041402. [Google Scholar] [CrossRef]
  31. Sun, M.L.; Slanina, Z.; Lee, S.L. Square/hexagon route towards the boron-nitrogen clusters. Chem. Phys. Lett. 1995, 233, 279–283. [Google Scholar] [CrossRef]
  32. Slanina, Z.; Sun, M.L.; Lee, S.L. AM1 stability prediction: B36N24 > B36P24 > Al36N24 > Al36P24. J. Mol. Struct. 1995, 334, 229–233. [Google Scholar] [CrossRef]
  33. Slanina, Z.; Sun, M.L.; Lee, S.L. Computations of boron and boron-nitrogen cages. Nan. Mater. 1997, 8, 623–635. [Google Scholar] [CrossRef]
  34. Lau, K.C.; Pandey, R. Stability and Electronic Properties of Atomistically Engineered 2D Boron Sheets. Phys. Chem. C 2007, 111, 2906–2912. [Google Scholar] [CrossRef]
  35. Rehman, M.U.; Sardar, R.; Raza, A. Computing topological indices of Hex Board and its line graph. Open J. Math. Sci. 2017, 1, 62–71. [Google Scholar] [CrossRef]
  36. Riaz, M.; Gao, W.; Baig, A.Q. M-Polynomials and degree-based Topological Indices of Some Families of Convex Polytopes. Open J. Math. Sci. 2018, 2, 18–28. [Google Scholar] [CrossRef]
  37. Kwun, Y.C.; Munir, M.; Nazeer, W.; Rafique, S.; Kang, S.M. M-Polynomials and topological indices of V-Phenylenic Nanotubes and Nanotori. Sci. Rep. 2017, 7, 8756. [Google Scholar] [CrossRef] [PubMed]
  38. Kwun, Y.C.; Munir, M.; Nazeer, W.; Rafique, S.; Kang, S.M. Computational Analysis of topological indices of two Boron Nanotubes. Sci. Rep. 2018, 8, 14843. [Google Scholar] [CrossRef] [PubMed]
  39. Hussain, Z.; Munir, M.; Rafique, S.; Kang, S.M. Topological Characterizations and Index-Analysis of New Degree-Based Descriptors of Honeycomb Networks. Symmetry 2018, 10, 478. [Google Scholar] [CrossRef]
  40. Chartrand, G.; Erdos, P.; Oellermann, O. How to define an irregular graph. Coll. Math. J. 1988, 19, 36–42. [Google Scholar] [CrossRef]
  41. Majcher, Z.; Michael, J. Highly irregular graphs with extreme numbers of edges. Discr. Math. 1997, 164, 237–242. [Google Scholar] [CrossRef] [Green Version]
  42. Behzad, M.; Chartrand, G. No graph is perfect. Am. Math. Mon. 1947, 74, 962–963. [Google Scholar] [CrossRef]
  43. Horoldagva, B.; Buyantogtokh, L.; Dorjsembe, S.; Gutman, I. Maximum size of maximally irregular graphs. Match Commun. Math. Comput. Chem. 2016, 76, 81–98. [Google Scholar]
  44. Liu, F.; Zhang, Z.; Meng, J. The size of maximally irregular graphs and maximally irregular triangle–free graphs. Graphs Comb. 2014, 30, 699–705. [Google Scholar] [CrossRef]
  45. Collatz, L.; Sinogowitz, U. Spektren endlicher Graphen. Abh. Math. Sem. Univ. Hambg. 1957, 21, 63–77. [Google Scholar]
  46. Abdo, H.; Brandt, S.; Dimitrov, D. The total irregularity of a graph. Discr. Math. Theor. Comput. Sci. 2014, 16, 201–206. [Google Scholar]
  47. Vukičević, D.; Graovac, A. Valence connectivities versus Randić, Zagreb and modified Zagreb index: A linear algorithm to check discriminative properties of indices in acyclic molecular graphs. Croat. Chem. Acta 2004, 77, 501–508. [Google Scholar]
  48. Abdo, H.; Dimitrov, D. The total irregularity of graphs under graph operations. Miskolc Math. Notes 2014, 15, 3–17. [Google Scholar] [CrossRef]
  49. Abdo, H.; Dimitrov, D. The irregularity of graphs under graph operations. Discuss. Math. Graph Theory 2014, 34, 263–278. [Google Scholar] [CrossRef]
  50. Gutman, I. Topological Indices and Irregularity Measures. J. Bull. 2018, 8, 469–475. [Google Scholar]
  51. Zahid, I.; Aslam, A.; Ishaq, M.; Aamir, M. Characteristic study of irregularity measures of some Nanotubes. Can. J. Phys. 2019. [Google Scholar] [CrossRef]
  52. Gao, W.; Aamir, M.; Iqbal, Z.; Ishaq, M.; Aslam, A. On Irregularity Measures of Some Dendrimers Structures. Mathematics 2019, 7, 271. [Google Scholar] [CrossRef]
  53. Gao, W.; Abdo, H.; Dimitrov, D. On the irregularity of some molecular structures. Can. J. Chem. 2017, 95, 174–183. [Google Scholar] [CrossRef] [Green Version]
  54. Hussain, Z.; Rafique, S.; Munir, M.; Athar, M.; Chaudhary, M.; Ahmad, H.; Min Kang, S. Irregularity Molecular Descriptors of Hourglass, Jagged-Rectangle, and Triangular Benzenoid Systems. Processes 2019, 7, 413. [Google Scholar] [CrossRef]
  55. Hussain, Z.; Munir, M.; Rafique, S.; Hussnain, T.; Ahmad, H.; Chel Kwun, Y.; Min Kang, S. Imbalance-Based Irregularity Molecular Descriptors of Nanostar Dendrimers. Processes 2019, 7, 517. [Google Scholar] [CrossRef]
  56. Liu, J.B.; Wang, C.; Wang, S.; Wei, B. Zagreb Indices and Multiplicative Zagreb Indices of Eulerian Graphs. Bull. Malays. Math. Sci. Soc. 2019, 42, 67–78. [Google Scholar] [CrossRef]
Figure 1. Tabular view of carbon, Triangular boron and α-boron nanotubes. (a) Carbon nanotube; (b) Triangular boron nanotube; (c) α-boron nanotube.
Figure 1. Tabular view of carbon, Triangular boron and α-boron nanotubes. (a) Carbon nanotube; (b) Triangular boron nanotube; (c) α-boron nanotube.
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Figure 2. Molecular graphs of tubes presented in Figure 1: (a) Carbon nanotube; (b) Triangular boron nanotube; (c) α-boron nanotube.
Figure 2. Molecular graphs of tubes presented in Figure 1: (a) Carbon nanotube; (b) Triangular boron nanotube; (c) α-boron nanotube.
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Figure 3. Tri-hexagonal boron nanotubes, CNTH [p,q].
Figure 3. Tri-hexagonal boron nanotubes, CNTH [p,q].
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Figure 4. Alpha Boron nanotubes B N T α [ p ,   q ] .
Figure 4. Alpha Boron nanotubes B N T α [ p ,   q ] .
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Figure 5. Triangular Boron Nanotube B N T t [ p ,   q ] .
Figure 5. Triangular Boron Nanotube B N T t [ p ,   q ] .
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Figure 6. Surfaces of I R D I F ( G ) .
Figure 6. Surfaces of I R D I F ( G ) .
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Figure 7. Surfaces of A L ( G ) .
Figure 7. Surfaces of A L ( G ) .
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Figure 8. Surfaces of I R L ( G ) .
Figure 8. Surfaces of I R L ( G ) .
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Figure 9. Surfaces of I R L U ( G ) .
Figure 9. Surfaces of I R L U ( G ) .
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Figure 10. Surfaces of I R L U ( G ) .
Figure 10. Surfaces of I R L U ( G ) .
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Figure 11. Surfaces of I R F ( G ) .
Figure 11. Surfaces of I R F ( G ) .
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Figure 12. Surfaces of I R A ( G ) .
Figure 12. Surfaces of I R A ( G ) .
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Figure 13. Surfaces of I R G A ( G ) .
Figure 13. Surfaces of I R G A ( G ) .
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Figure 14. Irregularity indices for three tubes.
Figure 14. Irregularity indices for three tubes.
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Figure 15. I R G A ( G ) for three tubes.
Figure 15. I R G A ( G ) for three tubes.
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Table 1. Edge partition of tri-hexagonal boron nanotube structure C N T H [ p , q ] .
Table 1. Edge partition of tri-hexagonal boron nanotube structure C N T H [ p , q ] .
Number   of   Edges   ( d u , d v ) Number of Indices
(3,5)6q
(4,4)2pqq
(4,5)6q (2p − 1)
(5,5)4pq
Table 2. Irregularity indices for tri-hexagonal boron nanotube structure C N T H [ p , q ] .
Table 2. Irregularity indices for tri-hexagonal boron nanotube structure C N T H [ p , q ] .
Irregularity Indicesp = 1, q = 1p = 2, q = 2p =3, q = 3p = 4, q = 4p = 5, q = 5
I R D I F ( G ) = U V E | d u d v d v d v | 7.4022.2044.4074111
A L ( G ) = U V E | d u d v | 1860126216330
I R L ( G ) = U V E | l n d u l n d v | 4.4114.1729.2849.7575.58
I R L U ( G ) = U V E | d u d v | m i n ( d u , d v ) 5.501734.505887.50
I R L U ( G ) = U V E | d u d v | ( d u d v ) 2.8911.1524.7843.7768.12
I R F ( G ) = U V E ( d u d v ) 2 3084162264390
I R L A ( G ) = 2 U V E | d u d v | ( d u + d v ) 4.34142949.3475
I R D 1 = U V E l n { 1 + | d v d v | } 10.7638.1482.16142.82220.109
I R A ( G ) = U V E ( d u 1 2 d v 1 2 ) 2 0.942.0333.2994.746.34
I R G A ( G ) = U V E l n d u + d v 2 ( d u d v ) 0.240.621.141.822.65
I R B ( G ) = U V E ( d u 1 2 d v 1 2 ) 2 1.865.0559.5915.4622.67
7.4022.2044.4074111
Table 3. Edge partition of alpha (α)-Boron Nano tube.
Table 3. Edge partition of alpha (α)-Boron Nano tube.
Number   of   Edges   ( d u , d v ) Number of Indices
(4,4) 3 p
(4,5) 2 p
(4,6) 4 p
(5,5) p 2 ( 3 q 11 )
(5,6) 3 p 2
(6,6) p + q 3
Table 4. Irregularity indices for Alpha (α) Boron Nanotube.
Table 4. Irregularity indices for Alpha (α) Boron Nanotube.
Irregularity Indicesp = 1, q = 1p = 2, q = 2p = 3, q = 3p = 4, q = 4p = 5, q = 5
I R D I F ( G ) = U V E | d u d v d v d v | 5.3312.8722.6034.5348.67
A L ( G ) = U V E | d u d v | 13325788125
I R L ( G ) = U V E | l n d u l n d v | 2.63296466.359858411.180681417.095433624.1041150
I R L U ( G ) = U V E | d u d v | m i n ( d u , d v ) 3.107.4012.9019.6027.50
I R L U ( G ) = U V E | d u d v | ( d u d v ) 2.6279306.35130611.17012817.08439624.094110
I R F ( G ) = U V E ( d u d v ) 2 214881120165
I R L A ( G ) = 2 U V E | d u d v | ( d u + d v ) 2.596.2711.0416.9023.86
I R D 1 = U V E l n { 1 + | d v d v | } 7.860183519.8792436.057190556.394014080.8897175
I R A ( G ) = U V E ( d u 1 2 d v 1 2 ) 2 0.04380110.09671180.15873210.22986200.3101015
I R G A ( G ) = U V E l n d u + d v 2 ( d u d v ) 0.1065140.237920.394230.575430.78153
I R B ( G ) = U V E ( d u 1 2 d v 1 2 ) 2 1.467344.03017.688312.442018.2911
5.3312.8722.6034.5348.67
Table 5. Edge partition of Triangular Boron Nanotube.
Table 5. Edge partition of Triangular Boron Nanotube.
Number   of   Edges   ( d u , d v ) Number of Indices
(4,4) 3 p
(4,6) 6 p
(6,6) p 2 ( 9 q 24 )
Table 6. Irregularity indices for Triangular Boron Nanotube.
Table 6. Irregularity indices for Triangular Boron Nanotube.
Irregularity Indicesp = 1, q = 1p = 2, q = 2p =3, q = 3p = 4, q = 4p = 5, q = 5
I R D I F ( G ) = U V E | d u d v d v d v | 510152025
A L ( G ) = U V E | d u d v | 1224364860
I R L ( G ) = U V E | l n d u l n d v | 2.444.877.309.7512.17
I R L U ( G ) = U V E | d u d v | m i n ( d u , d v ) 3691215
I R L U ( G ) = U V E | d u d v | ( d u d v ) 2.454.907.359.8012.25
I R F ( G ) = U V E ( d u d v ) 2 24487296120
I R L A ( G ) = 2 U V E | d u d v | ( d u + d v ) 2.44.87.29.612
I R D 1 = U V E l n { 1 + | d v d v | } 6.5913.1819.7826.3732.98
I R A ( G ) = U V E ( d u 1 2 d v 1 2 ) 2 0.050510.101020.151530.202040.2526
I R G A ( G ) = U V E l n d u + d v 2 ( d u d v ) 0.1230.2450.36740.4890.612
I R B ( G ) = U V E ( d u 1 2 d v 1 2 ) 2 1.21222.42443.63684.84906.0612
510152025

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Yang, B.; Munir, M.; Rafique, S.; Ahmad, H.; Liu, J.-B. Computational Analysis of Imbalance-Based Irregularity Indices of Boron Nanotubes. Processes 2019, 7, 678. https://doi.org/10.3390/pr7100678

AMA Style

Yang B, Munir M, Rafique S, Ahmad H, Liu J-B. Computational Analysis of Imbalance-Based Irregularity Indices of Boron Nanotubes. Processes. 2019; 7(10):678. https://doi.org/10.3390/pr7100678

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Yang, Bin, Mobeen Munir, Shazia Rafique, Haseeb Ahmad, and Jia-Bao Liu. 2019. "Computational Analysis of Imbalance-Based Irregularity Indices of Boron Nanotubes" Processes 7, no. 10: 678. https://doi.org/10.3390/pr7100678

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