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. 2023 Jul 11;9(7):e17998. doi: 10.1016/j.heliyon.2023.e17998

Computational analysis for eccentric neighborhood Zagreb indices and their significance

Hanan Ahmed a,b,, Anwar Saleh c, Rashad Ismail d, Ruby Salestina M a, Abdu Alameri e
PMCID: PMC10372232  PMID: 37519713

Abstract

In this paper, a novel eccentric neighborhood degree-based topological indices, termed eccentric neighborhood Zagreb indices, have been conceptualized and its discriminating power investigated with regard to the predictability of the boiling point of the chemical substances. The discriminating power of the eccentric neighborhood Zagreb indices was compared with that of Wiener and eccentric connectivity indices. Some explicit results for those new indices for some graphs and graph operations such as join, disjunction, composition, and symmetric difference.

MSC: 05C12, 05C90, 05C76

Keywords: Eccentric neighborhood Zagreb indices, Eccentricity neighborhood degree, Graph operations, Boiling point, Molecular descriptors

1. Introduction

A molecular graph [8], [9] is a connected simple graph such that the vertices and edges are supposed to be atoms and chemical bonds respectively. Chemical graph theory is an important branch of both chemistry and graph theory as it has taken a lot of attention because of the important results obtained in chemical graph theory and has been applied in many applications such as chemical engineering as well as pharmaceutical [13]. The main idea of chemical graph theory is that the physical and chemical properties of molecules can be studied and explained using information [10]. It can also be noted that in contemporary mathematical chemical literature, there are many descriptors of molecular structure based on vertex degree. In this research by a graph, we main undirected finite, simple and connected graph. For a graph, G=(V(G),E(G)), V(G) and E(G) denote the vertex set and edge set, respectively. The set N(u) of all neighbors of u is said the open neighborhood of u, i.e., N(u)={vV(G):uvE(G)}. The degree dG(u)=d(u) of a vertex u in G is defined as d(u)=|N(u)|. The length of the shortest path joining between the two vertices u and v is called the distance between those two vertices and is denoted by dG(u,v) or d(u,v). The origin of topological indices goes back to 1947 when a chemist by name, Wiener established the first topological index, recognize as the Wiener index [16], to search for boiling points and defined as W(G)=12{u,v}V(G)d(u,v). Among the topological indices defined in the initial phase, Zagreb indices are related to the most common molecular descriptors. First introduced by Gutman and Trinajestic [7], the first and second Zagreb indices are given as follows:

M1(G)=uV(G)dG2(u)=uvE(G)(dG(u)+dG(v)),
M2(G)=uvE(G)dG(u)dG(v).

For more details of those indices see [3], [6], [11]. The eccentricity ε(u)=maxvV(G)dG(u,v).

Also, r(G)=minuV(G)ε(u) and D(G)=maxuV(G)ε(u) are the radius and diameter of G respectively. The eccentric connectivity index [15] is defined as ξc=vV(G)dG(v)εG(v). For some applications of eccentric connectivity index see [5], [10], [14], and for the mathematical properties of this topological index [12], [17], [19]. The goal of this research is to define new topological indices based on new parameter known as the neighborhood eccentricity of the vertex, these new indices have a good significant to applied in chemical graph theory also have mathematical significance.

Lemma 1.1

[4] Let G1 and G2 be any two graphs. Then

  • (a)

    εG1+G2(u)={1,if εGi(u)=1;2,if εGi(u)2.

  • (b)

    εG1G2(u,v)={1,if εG1(u)=εG2(v)=1;2,if εG1(u)2 or εG2(v)2.

  • (c)

    εG1[G2](u,v)={1,if εG1(u)=εG2(v)=1;2,if εG1(u)=1,εG2(v)2;εG1(u),if εG1(u)2.

  • (d)

    εG1G2(u,v)=2 .

2. Materials and methods

In this research, the primary amines group was adopted as a standard group in which the chemical and physical applicability of the new indices are tested. Primary amines are widely used to test the applicability of topological indices, as they were used in the Wiener index test in estimating the boiling points of these compounds [15]. Also, it is used for the structural determination of the paraffin boiling point [16]. For more studies application of topological indices on primary amines, the reader can refer to the following references [2], [18]. The values of the boiling point are described in Table 2 according to their experimental data [15], and also https://pubchem.ncbi.nlm.nih.gov After that, a non-linear regression analysis is performed using the R-program analysis, and with this analysis, the expected boiling point values of the primary amines are estimated. Linear combinations of the obtained models are plotted using Excel. This is the first part of organizing the main results of this research. In the second part, the novel-designed indices are studied and analyzed mathematically to study their properties, apply them to different families of graphs, and perform basic operations on them. We have used the analytical method, in the process.

Table 2.

Relationship of predicted boiling points calculated by eccentric neighborhood Zagreb indices, ξc(G) and W(G) with BP of primary amines.

Compound BP BP ENM1(G) BP ENM2(G) BP ENM3(G) BP ξc(G) BP W(G)
n-propylamine 49 50.94 52.67 45.63 53.27 46.7
2-aminopropane 33 42.76 36.41 41.65 39.97 44.1
2-amino-2-methylpropane 46 50.12 45.91 60.19 48.19 60.52
2-aminobutane 63 65.06 67.08 64.68 64.97 64.57
2-methylpropylamine 69 65.06 67.08 64.68 64.97 64.57
n-butylamine 77 71.72 74.96 66.87 75.6 68.42
2-amino-2-methylbutane 78 80.13 81.02 87.25 75.62 82.33
2-aminopentane 92 87.74 90.84 88.21 89.31 88.6
3-methylbutylamine 96 87.74 90.84 88.21 89.31 87.07
2-methylbutylamine 96 82.9 88.26 84.35 85.52 88.6
n-pentylamine 104 98.38 100.75 92.94 101.94 93.08
4-methylpentylamine 125 116.57 117.86 116.78 117.05 113.25
n-hexylamine 130 124.74 125.49 119.29 128.1 120.54
3-methylpentylamine 114 110.97 115.83 112.55 113.79 113.25
4-aminoheptane 139 135.26 137.65 137.76 138.67 141.55
2-aminoheptane 142 145.13 144.02 145.44 144.5 145.65
n-heptylamine 155 154.88 154.88 149.21 157.22 150.65
n-octylamine 180 184.83 181.7 179.32 186.2 183.3
n-nonylamine 201 217.67 211.99 212.35 217.59 218.39
2-aminoundecane 237 276.5 267.77 278.43 268.93 289.23
3-aminopentane 91 82.9 88.26 84.35 85.52 87.07

3. Results and discussion

To understand the different properties of chemicals, laboratory tests must be performed, and this is extremely costly. To vanquish this problem, many topological indices in theoretical chemistry have been introduced and defined. To define a new topological index one must verify two things. The index must correspond well with at least one physical or chemical property of a standard data set, on the other hand, it should be simple in the formulation it and give some theoretical insight. In this section, we have two subsections. First, we define the significance of the first, second, and third eccentric neighborhood Zagreb indices in determining the predicted boiling point using nonlinear regression analysis. Second, we study the eccentric neighborhood Zagreb indices mathematically.

3.1. The significance of the eccentric neighborhood Zagreb indices in predicting the boiling point of molecular descriptors

To verify the importance and the efficiency of a topological index for modeling physicalchemical properties we use nonlinear regression analysis. Commonly, for such an investigation, primary amines are useful because of their diverse structurally. In this section, we find the Wiener index and eccentric connectivity index with the eccentric neighborhood Zagreb indices and the data listed in Table 1. We get the relationship of eccentric neighborhood Zagreb indices with boiling points of primary amines as in Table 2. Table 3, is shown that the predicted boiling points calculated by the first, second, and third eccentric neighborhood Zagreb indices are strongly correlated with boiling points of primary amines (R=0.987), (R=0.993) and (R=0.9814) respectively, (see Fig. 1, a, b and c). Also, we present the correlation coefficient of boiling points predicted by the eccentric connectivity index and Wiener index with these indices (see Fig. 2, a and b). In Table 4, we determined the correlation coefficient of ENM1(G), ENM2(G) and ENM3(G) with ξc(G) and W(G). For more delicate statistical tests, which rank the indices by their predictive power, see Table 5.

Table 1.

Eccentric neighborhood Zagreb indices with eccentric connectivity index and Wiener index of primary amines.

Compound ξc(G) W(G) ENM1(G) ENM2(G) ENM3(G)
1 n-propylamine 14 10 58 45 24
2 2-aminopropane 9 9 39 18 21
3 2-amino-2-methylpropane 12 16 56 32 36
4 2-aminobutane 19 18 101 82 40
5 2-methylpropylamine 19 18 101 82 40
6 n-butylamine 24 20 126 108 42
7 2-amino-2-methylbutane 24 28 162 131 62
8 2-aminopentane 31 32 199 174 63
9 3-methylbutylamine 31 31 199 174 63
10 2-methylbutylamine 29 32 175 162 59
11 n-pentylamine 38 35 258 225 68
12 4-methylpentylamine 47 50 379 332 95
13 n-hexylamine 54 56 442 388 98
14 3-methylpentylamine 45 50 339 318 90
15 4-aminoheptane 61 75 531 488 121
16 2-aminoheptane 65 79 623 546 131
17 n-heptylamine 74 84 722 654 136
18 n-octylamine 96 120 1078 972 178
19 n-nonylamine 122 165 1562 1425 228
20 2-aminoundecane 169 275 2687 2474 339
21 3-aminopentane 29 31 175 162 59

Table 3.

Correlation coefficient of boiling points predicted by eccentric neighborhood Zagreb indices, ξc(G) and W(G) with BP of primary amines.

BP ENM1(G) BP ENM2(G) BP ENM3(G) BP ξc(G) BP W(G)
BP 0.987 0.993 0.9814 0.99199 0.97875

Figure 1.

Figure 1

Linear fitting of BP predicted by (a) ENM1(G), (b) ENM2(G), (c) ENM3(G) with BP.

Figure 2.

Figure 2

Linear fitting of BP predicted by (a) W(G) with BP, (b) ξc(G) with BP.

Table 4.

Correlation coefficients of ENM1(G), ENM2(G) and ENM3(G) with ξc(G) and W(G).

ENM1(G) ENM2(G) ENM3(G) ξc(G) W(G)
ENM1(G) 1
ENM2(G) 0.9999 1
ENM3(G) 0.9869 0.9865 1
ξc(G) 0.9807 0.9802 0.9962 1
W(G) 0.9978 0.9979 0.994 0.9872 1

Table 5.

Some delicate statistical tests, which rank the indices by their predictive power.

Residual Standard Error on 19 degree of freedom Multiple R-Squared Adjusted R-Squared F-Statistic on 1 and 19 DF P-Value
ENM1(G) 0.09442 0.966 0.9642 539.2 2.077 × 10−15
ENM2(G) 0.05331 0.9891 0.9886 1732 <2.2 × 10−16
ENM1(G) 0.1161 0.9485 0.9458 350.1 1.064 × 10−13
ξc(G) 0.07367 0.9793 0.9782 897.9 <2.2 × 10−16
W(G) 0.1209 0.9442 0.9413 321.4 2.301 × 10−13

The non linear regression analysis equations which are used are:

ln(BP)=2.14+0.441ln(ENM1(G)),
ln(BP)=2.43+0.403ln(ENM2(G)),
ln(BP)=1.65+0.683ln(ENM3(G)),
ln(BP)=2.26+0.65ln(ξc(G)),
ln(BP)=2.578+0.55ln(W(G)).

3.2. Eccentric neighborhood Zagreb indices of graphs and graph operations

Definition 3.1

Let G=(V(G),E(G)) be a connected simple graph and δen(v)=uN(v)ε(u) be the eccentricity neighborhood degree. Then the first, second and third eccentric neighborhood Zagreb indices are defined as follows:

ENM1(G)=vV(G)δen2(v),
ENM2(G)=uvE(G)δen(u)δen(v),
ENM3(G)=uvE(G)(δen(u)+δen(v)).

Proposition 3.2

  • 1.

    For star graphSrwithr+1vertices, we haveENM1(Sr)=4r2+r,ENM2(Sr)=2r2andENM3(Sr)=2r2+r.

  • 2.

    IfGSr,swithr+s+2vertices, thenENM1(G)=9(r2+s2)2+16(r+s)+8,ENM2(G)=(2+3r)(2r+3s+2)+2s(2+3s)andENM3(G)=(4+3r)r+(3s+4)s+3(r+s)+4.

  • 3.

    SupposeGCn,n4. ThenENM1(G)=ENM2(G)={n3,if n is even;n(n1)2,if n is odd.

    ENM3(G)={2n2,if n is even;2n(n1),if n is odd.

  • 4.

    IfGWnis the wheel graph withn5vertices, thenENM1(Wn)=4n2+17n21,ENM2(Wn)=10n2+5n15, andENM3(Wn)=2n2+11n13.

Lemma 3.3

LetGPnwith vertex set{u1,u2,...,un}. Then

  • 1.

    If n is even andn4, thenδen(ui)={n2,if i=1,n;2n2i,if i=2,3,...,(n21);2i2,if i=(n2+2),...,n1;n+1,if i=n2,(n2+1).

  • 2.

    If n is odd andn3, thenδen(ui)={n2,if i=1,n;2n2i,if i=2,3,...,(n+121);2i2,if i=(n+12+1),...,n1;n+1,if i=n+12.

Proposition 3.4

  • 1.
    LetPnbe a path withn4where n is even, then
    ENM1(Pn)=13(7n327n2+38n+6),ENM3(Pn)=3n28n+8.
  • 2.
    Ifn6is even, then
    ENM2(Pn)=13(7n333n2+56n+15).
  • 3.
    LetPnbe a path withn3where n is odd, then
    ENM1(Pn)=13(7n327n2+35n+3),ENM3(Pn)=3n28n+7.
  • 4.
    If n is odd andn5, then
    ENM2(Pn)=13(7n333n2+53n+9).

An (r,s) banana tree denoted by Br,s, defined by Chan et al. [1], is a graph obtained by connecting one leaf of each of r copies of an s-star graph with a single root vertex that is different from all the stars.

Lemma 3.5

IfGBr,swithr2, ands3and w is the root vertex, then

δen(v)={5,if v is pendent vertex;4r,if v=w;6s8,if v is the center vertex;8,if v {v:vwE(Br,s)}.

Proposition 3.6

SupposeGBr,swithr2ands3. Then

ENM1(G)=16r2+36s2r71sr+78r,
ENM2(G)=32r2+30s2r52sr+16r,
ENM3(G)=4r2+6s2r9rs+14r.

Proposition 3.7

For any graph G

vV(G)δen(v)=ξc(G).

Proposition 3.8

Suppose G is a graph with diameter and radiusD(G)andr(G)respectively, then

  • r2(G)M1(G)ENM1(G)D2(G)M1(G),

  • r2(G)M2(G)ENM2(G)D2(G)M2(G),

  • r(G)M1(G)ENM3(G)D(G)M1(G).

Equality holds if and only ifD(G)=1.

3.3. Join

A join [11] G+H of two graphs G and H with V(G) and V(H) as disjoint vertex sets is the graph on the vertex set V(G)V(H) and the edge set E(G)E(H){u1u2:u1V(G),u2V(H)}.

Lemma 3.9

For any two graphs G and H

  • (a)

    IfVω(G)=Vω(H)=, thenδenG+H(u)=2dG+H(u).

  • (b)

    If|Vω(G)|=rand|Vω(H)|=ssuch that,r+s>0, then

    δenG+H(u)={2dG(u)+2|V(H)|(r+s),if uV(G),uVω(G);2dG(u)+2|V(H)|+1(r+s),if uV(G),uVω(G);2dH(u)+2|V(G)|(r+s),if uV(H),uVω(H);2dH(u)+2|V(G)|+1(r+s),if uV(H),uVω(H).

We can partition the edge set of E(G+H) as follows:

E11={uvE(G):u,vVw(G)},E12={uvE(G):u,vVw(G)},
E13={uvE(G):uVw(G),vVw(G)},E21={uvE(H):u,vVw(H)},
E22={uvE(H):u,vVw(H)},E23={uvE(H):uVw(H),vVw(H)}.

Let EuV(G),vV(H) be the set of edges connecting vertices of G with vertices of H. Then

E31={uvEuV(G),vV(H):uVw(G),vVw(H)},
E32={uvEuV(G),vV(H):uVw(G),vVw(H)},
E33={uvEuV(G),vV(H):uVw(G),vVw(H)},
E34={uvEuV(G),vV(H):uVw(G),vVw(H)}.

Theorem 3.10

Let G and H be any two graphs with|Vω(G)|=r,|Vω(H)|=sandr+s>0. Then

(a)ENM1(G+H)=4M1(G+H)8(r+s)(|E(G)|+|E(H)|)+4(uV(G)uVω(G)dG(u)+uV(H)uVω(H)dH(u))+(r+s)((r+s)22(r+s)4(r|V(H)|+s|V(G)|))+(r+s)[(r+s4|V(H)|)(|V(G)|1)+(r+s4|V(G)|)(|V(H)|s)]+(4|V(H)|+1)r+(4|V(G)|+1)s.(b)ENM2(G+H)=4(M2(G)+M2(H)+|V(H)|M1(G)+|V(G)|M1(H))+4(uV(G)vV(H)(dG(u)dH(v))+uV(G)vV(H)(|V(G)|dG(u)+|V(H)|dH(v)))2(r+s)(uvE11(dG(u)+dG(v))+uvE21(dH(u)+dH(v))+uvE31(dG(u)+dH(v)))2(r+s1)(uvE12(dG(u)+dG(v))+uvE22(dH(u)+dH(v))+uvE34(dG(u)+dH(v)))
2[uvE13uVω(G)vVω(G)((r+s1)dG(u)+(r+s)dG(v))+uvE23uVω(H)vVω(H)((r+s1)dH(u)+(r+s)dH(v))+uvE32uVω(G)vVω(H)((r+s1)dG(u)+(r+s)dH(v))+uvE33uVω(G)vVω(H)((r+s)dG(u)+(r+s1)dH(v))]+(2|V(H)|(r+s))2|E11|+(2|V(H)|(r+s1))2|E12|+(4|V(H)|22|V(H)|(2(r+s)1)+(r+s)(r+s1))|E13|+(2|V(G)|(r+s))2|E21|+(2|V(G)|(r+s1))2|E22|+(4|V(G)|22|V(G)|(2(r+s)1)+(r+s)(r+s1))|E23|+(4|V(G)||V(H)|2(r+s)(|V(G)|+|V(H)|)+(r+s)2)|E31|+(4|V(G)||V(H)|2(|V(G)|(r+s)+|V(H)|(r+s1))+(r+s)(r+s1))|E32|+(4|V(G)||V(H)|2(|V(H)|(r+s)+|V(G)|(r+s1))+(r+s)(r+s1))|E33|+(4|V(G)||V(H)|2(r+s1)(|V(G)|+|V(H)|)+(r+s1)2)|E34|.
(c)ENM3(G+H)=2(M1(G)+M1(H))+(4|V(H)|2(r+s))|E(G)|+(4|V(G)|2(r+s))|E(H)|+2(|E12|+|E22|)+|E13|+|E23|+2uV(G)vV(H)(dG(u)+dH(v))+(2(|V(G)|+|V(H)|)2(r+s))|V(G)||V(H)|+|E32|+|E33|+2|E34|.

Proof

Applying Lemma 3.9(b), we get

ENM1(G+H)=uV(G+H)δenG+H2(u)=uV(G)uVω(G)δenG+H2(u)+uV(G)uVω(G)δenG+H2(u)+uV(H)uVω(H)δenG+H2(u)+uV(H)uVω(H)δenG+H2(u)=uV(G)uVω(G)(2dG(u)+2|V(H)|(r+s))2+uV(G)uVω(G)(2dG(u)+2|V(H)|+1(r+s))2+uV(H)uVω(H)(2dH(u)+2|V(G)|(r+s))2+uV(H)uVω(H)(2dH(u)+2|V(G)|+1(r+s))2=4uV(G)uVω(G)(dG(u)+|V(H)|)24(r+s)uV(G)uVω(G)dG(u)+((r+s)24|V(H)|(r+s))(|V(G)|r)+4uV(G)uVω(G)(dG(u)+|V(H)|)2+4(1(r+s))uV(G)uVω(G)dG(u)+(4|V(H)|+1)r+((r+s)24|V(H)|)(r+s)r+4uV(H)uVω(H)(dH(u)+|V(G)|)24(r+s)uV(H)uVω(H)dH(u)+((r+s)24|V(G)|(r+s))(|V(H)|s)+4uV(H)uVω(H)(dH(u)+|V(G)|)2+4(1(r+s))uV(H)uVω(H)dH(u)+(4|V(G)|+1)s+(r+s24|V(G)|)(r+s)s=4M1(G+H)8(r+s)(|E(G)|+|E(H)|)+4(uV(G)uVω(G)dG(u)+uV(H)uVω(H)dH(u))
+(r+s)((r+s)22(r+s)4(r|V(H)|+s|V(G)|))+(r+s)[(r+s4|V(H)|)(|V(G)|1)+(r+s4|V(G)|)(|V(H)|s)]+(4|V(H)|+1)r+(4|V(G)|+1)s.

To prove (b) and (c) we use the partition of the edge set E(G+H) as mentioned earlier. Hence applying Lemma 3.9(b), we get

ENM2(G+H)=uvE(G+H)δenG+H(u)δenG+H(v)=uvE11δenG+H(u)δenG+H(v)+uvE12δenG+H(u)δenG+H(v)+uvE13uVω(G)vVω(G)δenG+H(u)δenG+H(v)+uvE21δenG+H(u)δenG+H(v)+uvE22δenG+H(u)δenG+H(v)+uvE23uVω(H)vVω(H)δenG+H(u)δenG+H(v)+uvE31δenG+H(u)δenG+H(v)+uvE32uVω(G)vVω(H)δenG+H(u)δenG+H(v)+uvE33uVω(G)vVω(H)δenG+H(u)δenG+H(v)+uvE34δenG+H(u)δenG+H(v)=uvE11((2dG(u)+2|V(H)|(r+s))(2dG(v)+2|V(H)|(r+s)))+uvE12((2dG(u)+2|V(H)|+1(r+s))(2dG(v)+2|V(H)|+1(r+s)))+uvE13uVω(G)vVω(G)((2dG(u)+2|V(H)|(r+s))(2dG(v)+2|V(H)|+1(r+s)))+uvE21((2dH(u)+2|V(G)|(r+s))(2dH(v)
+2|V(G)|(r+s)))+uvE22((2dH(u)+2|V(G)|+1(r+s))(2dH(v)+2|V(G)|+1(r+s)))+uvE23uVω(H)vVω(H)((2dH(u)+2|V(G)|(r+s))(2dH(v)+2|V(G)|+1(r+s)))+uvE31((2dG(u)+2|V(H)|(r+s))(2dH(v)+2|V(G)|(r+s)))+uvE32uVω(G)vVω(H)((2dG(u)+2|V(H)|(r+s))(2dH(v)+2|V(G)|+1(r+s)))+uvE33uVω(G)vVω(H)((2dG(u)+2|V(H)|+1(r+s))(2dH(v)+2|V(G)|(r+s)))+uvE34((2dG(u)+2|V(H)|+1(r+s))(2dH(v)+2|V(G)|+1(r+s)))=4M2(G)+(4|V(H)|2(r+s))uvE11(dG(u)+dG(v))+(2|V(H)|(r+s))2|E11|+(4|V(H)|2(r+s1))uvE12(dG(u)+dG(v))+(2|V(H)|(r+s1))2|E12|+4|V(H)|uvE13uVω(G)vVω(G)(dG(u)+dG(v))2uvE13uVω(G)vVω(G)((r+s1)dG(u)+(r+s)dG(v))+[4|V(H)|22|V(H)|(2(r+s)1)+(r+s)(r+s1)]|E13|+4M2(H)+(4|V(G)|2(r+s))uvE21(dH(u)+dH(v))+(2|V(G)|(r+s))2|E21|+(4|V(G)|2(r+s1))uvE22(dH(u)+dH(v))+(2|V(G)|(r+s1))2|E22|+4|V(G)|uvE23uVω(H)vVω(H)(dH(u)+dH(v))2uvE23uVω(H)vVω(H)((r+s1)dH(u)+(r+s)dH(v))+[4|V(G)|22|V(G)|(2(r+s)1)+(r+s)(r+s1)]|E23|+4uV(G)vV(H)(dG(u)dH(v))2(r+s)(uvE31(dG(u)+dH(v))+uvE34(dG(u)+dH(v)))
+2uvE34(dG(u)+dH(v))+4[uvE31(|V(G)|dG(u)+|V(H)|dH(v))+uvE32uVω(G)vVω(H)(|V(G)|dG(u)+|V(H)|dH(v))+uvE33uVω(G)vVω(H)(|V(G)|dG(u)+|V(H)|dH(v))+uvE34(|V(G)|dG(u)+|V(H)|dH(v))]2(uvE32uVω(G)vVω(H)((r+s1)dG(u)+(r+s)dH(v))+uvE33uVω(G)vVω(H)((r+s)dG(u)+(r+s1)dH(v)))+[4|V(G)||V(H)|2(r+s)(|V(G)|+|V(H)|)+(r+s)2]|E31|+[4|V(G)||V(H)|2(|V(G)|(r+s)+|V(H)|(r+s1))+(r+s)(r+s1)]|E32|+[4|V(G)||V(H)|2(|V(H)|(r+s)+|V(G)|(r+s1))+(r+s)(r+s1)]|E33|+[4|V(G)||V(H)|2(r+s1)(|V(G)|+|V(H)|)+(r+s1)2]|E34|=4(M2(G)+M2(H)+|V(H)|M1(G)+|V(G)|M1(H))+4(uV(G)vV(H)(dG(u)dH(v))+uV(G)vV(H)(|V(G)|dG(u)+|V(H)|dH(v)))2(r+s)(uvE11(dG(u)+dG(v))+uvE21(dH(u)+dH(v))+uvE31(dG(u)+dH(v)))2(r+s1)(uvE12(dG(u)+dG(v))+uvE22(dH(u)+dH(v))+uvE34(dG(u)+dH(v)))2[uvE13uVω(G)vVω(G)((r+s1)dG(u)+(r+s)dG(v))+uvE23uVω(H)vVω(H)((r+s1)dH(u)+(r+s)dH(v))+uvE32uVω(G)vVω(H)((r+s1)dG(u)+(r+s)dH(v))
+uvE33uVω(G)vVω(H)((r+s)dG(u)+(r+s1)dH(v))]+(2|V(H)|(r+s))2|E11|+(2|V(H)|(r+s1))2|E12|+(4|V(H)|22|V(H)|(2(r+s)1)+(r+s)(r+s1))|E13|+(2|V(G)|(r+s))2|E21|+(2|V(G)|(r+s1))2|E22|+(4|V(G)|22|V(G)|(2(r+s)1)+(r+s)(r+s1))|E23|+(4|V(G)||V(H)|2(r+s)(|V(G)|+|V(H)|)+(r+s)2)|E31|+(4|V(G)||V(H)|2(|V(G)|(r+s)+|V(H)|(r+s1))+(r+s)(r+s1))|E32|+(4|V(G)||V(H)|2(|V(H)|(r+s)+|V(G)|(r+s1))+(r+s)(r+s1))|E33|+(4|V(G)||V(H)|2(r+s1)(|V(G)|+|V(H)|)+(r+s1)2)|E34|.
ENM3(G+H)=uvE(G+H)(δenG+H(u)+δenG+H(v))=uvE11(δenG+H(u)+δenG+H(v))+uvE12(δenG+H(u)+δenG+H(v))+uvE13uVω(G)vVω(G)(δenG+H(u)+δenG+H(v))+uvE21(δenG+H(u)+δenG+H(v))+uvE22(δenG+H(u)+δenG+H(v))+uvE23uVω(H)vVω(H)(δenG+H(u)+δenG+H(v))+uvE31(δenG+H(u)+δenG+H(v))+uvE32uVω(G)vVω(H)(δenG+H(u)+δenG+H(v))+uvE33uVω(G)vVω(H)(δenG+H(u)+δenG+H(v))+uvE34(δenG+H(u)+δenG+H(v))
=uvE11((2dG(u)+2|V(H)|(r+s))+(2dG(v)+2|V(H)|(r+s)))+uvE12((2dG(u)+2|V(H)|+1(r+s))+(2dG(v)+2|V(H)|+1(r+s)))+uvE13uVω(G)vVω(G)((2dG(u)+2|V(H)|(r+s))+(2dG(v)+2|V(H)|+1(r+s)))+uvE21((2dH(u)+2|V(G)|(r+s))+(2dH(v)+2|V(G)|(r+s)))+uvE22((2dH(u)+2|V(G)|+1(r+s))+(2dH(v)+2|V(G)|+1(r+s)))+uvE23uVω(H)vVω(H)((2dH(u)+2|V(G)|(r+s))+(2dH(v)+2|V(G)|+1(r+s)))+uvE31((2dG(u)+2|V(H)|(r+s))+(2dH(v)+2|V(G)|(r+s)))+uvE32uVω(G),vVω(H)((2dG(u)+2|V(H)|(r+s))+(2dH(v)+2|V(G)|+1(r+s)))+uvE33uVω(G),vVω(H)((2dG(u)+2|V(H)|+1(r+s))+(2dH(v)+2|V(G)|(r+s)))+uvE34((2dG(u)+2|V(H)|+1(r+s))+(2dH(v)+2|V(G)|+1(r+s)))=2M1(G)+(4|V(H)|2(r+s))|E11(G)|+(4|V(H)|+22(r+s))|E12(G)|+(4|V(H)|+12(r+s))|E13(G)|+2M1(H)+(4|V(G)|2(r+s))|E21(H)|+(4|V(G)|+22(r+s))|E22(H)|+(4|V(G)|+12(r+s))|E23(H)|+2uV(G)vV(H)(dG(u)+dH(v))+(2(|V(G)|+|V(H)|)+12(r+s))(|E32|+|E33|)+(2(|V(G)|+|V(H)|)2(r+s))|E31|+(2(|V(G)|+|V(H)|)+22(r+s))|E34|
=2(M1(G)+M1(H))+(4|V(H)|2(r+s))|E(G)|+(4|V(G)|2(r+s))|E(H)|+2(|E12|+|E22|)+|E13|+|E23|+2uV(G)vV(H)(dG(u)+dH(v))+(2(|V(G)|+|V(H)|)2(r+s))|V(G)||V(H)|+|E32|+|E33|+2|E34|.

 □

Corollary 3.11

Suppose G and H are any two graphs such that,Vω(G)=Vω(H)=. Then

(a)ENM1(G+H)=4M1(G+H),ENM3(G+H)=2M1(G+H),
ENM2(G+H)=4M2(G+H).
(b)ENM3(G+H)=2(M1(G)+M1(H))+4(|V(H)||E(G)|+|V(G)|+|E(H)|)+|V(H)|(4|E(G)|+2|V(H)||V(G)|)+|V(G)|(4|E(H)|+2|V(H)||V(G)|).

Example 3.12

ENM1(Kr,s)=4(rs2+sr2), ENM2(Kr,s)=4r2s2 and ENM3(Kr,s)=2(rs2+sr2).

Example 3.13

For n4, we have

ENM1(P2+Pn)=8n2+44n38,
ENM2(P2+Pn)=28n2+36n67,
ENM3(P2+Pn)=4n2+30n22.

3.4. Disjunction

The disjunction GH [11] is the graph with vertex set V(G)×V(H) in which (x,y) is adjacent with (z,w) whenever xzE(G) or ywE(H).

Lemma 3.14

Suppose G and H are two graphs. Then

  • (a)

    If G and H are complete graphs, thenδenGH(u,v)=dGH(u,v).

  • (b)

    IfVω(G)=orVω(H)=, thenδenGH(u,v)=2dGH(u,v).

  • (c)

    IfVω(G)andVω(H)are not empty sets, such that,|Vω(G)|=r,|Vω(H)|=s, then

    δenGH(u,v)={2dGH(u,v)+1rs,if εGH(u,v)=1;2dGH(u,v)rs,otherwise.

One can partition the edges of E(GH) as: E1 be the set of edges connecting the vertices which satisfy εGH(u,v)=1, E2 be the set of edges connecting the vertices which satisfy εGH(u,v)1 and E3 be the set of edges connecting the vertices which satisfy εGH(u,v)=1 with the vertices which satisfy εGH(u,v)1.

Theorem 3.15

Suppose G and H are two graphs such that,|Vω(G)|=r,|Vω(H)|=swithrs>0. Then

(a)ENM1(GH)=4M1(GH)8rs|E(GH)|+(12rs+rs|V(GH)|)rs+4(u,v)V(GH)εGH(u,v)=1dGH(u,v).
(b)ENM2(GH)=4M2(GH)2((rs1)((a,b),(c,d))E1(dGH(a,b)+dGH(c,d))+rs((a,b),(c,d))E2(dGH(a,b)+dGH(c,d))+((a,b),(c,d))E3εGH(a,b)=1,εGH(c,d)1((rs)dGH(a,b)+(rs1)dGH(c,d)))+(rs1)2|E1|+rs(rs|E2|+(rs1)|E3|).
(c)ENM3(GH)=2M1(GH)2rs|E(GH)|+2|E1|+|E3|.

Proof

(a) Applying Lemma 3.14 (c), we have

ENM1(GH)=(u,v)V(GH)δenGH2(u,v)=(u,v)V(GH)εGH(u,v)=1δenGH2(u,v)+(u,v)V(GH)εGH(u,v)=2δenGH2(u,v)=(u,v)V(GH)εGH(u,v)=1(2dGH(u,v)+1rs)2+(u,v)V(GH)εGH(u,v)=2(2dGH(u,v)rs)2
=4(u,v)V(GH)εGH(u,v)=1dGH2(u,v)+4(1rs)(u,v)V(GH)εGH(u,v)=1dGH(u,v)+(12rs+r2s2)rs+4(u,v)V(GH)εGH(u,v)=2dGH2(u,v)4rs(u,v)V(GH)εGH(u,v)=2dGH(u,v)+r2s2(|V(GH)|rs)=4M1(GH)8rs|E(GH)|+(12rs+rs|V(GH)|)rs+4(u,v)V(GH)εGH(u,v)=1dGH(u,v).

To prove (b) and (c) we use the edge partition of E(GH) as mentioned earlier. Hence by Lemma 3.14(c), we have

(b)ENM2(GH)=((a,b),(c,d))E(GH)δenGH(a,b)δenGH(c,d)=((a,b),(c,d))E1δenGH(a,b)δenGH(c,d)+((a,b),(c,d))E2δenGH(a,b)δenGH(c,d)+((a,b),(c,d))E3εGH(a,b)=1εGH(c,d)1δenGH(a,b)δenGH(c,d)=((a,b),(c,d))E1(2dGH(a,b)+1rs)(2dGH(c,d)+1rs)+((a,b),(c,d))E2(2dGH(a,b)rs)(2dGH(c,d)rs)+((a,b),(c,d))E3εGH(a,b)=1εGH(c,d)1(2dGH(a,b)(rs1))(2dGH(c,d)rs)=4((a,b),(c,d))E1dGH(a,b)dGH(c,d)+2(1rs)((a,b),(c,d))E1(dGH(a,b)+dGH(c,d))+(1rs)2|E1|
+4((a,b),(c,d))E2dGH(a,b)dGH(c,d)2rs((a,b),(c,d))E2(dGH(a,b)+dGH(c,d))+r2s2|E2|+4((a,b),(c,d))E3εGH(a,b)=1εGH(c,d)1dGH(a,b)dGH(c,d)2((a,b),(c,d))E3εGH(a,b)=1εGH(c,d)1(rsdGH(a,b)+(rs1)dGH(c,d))+rs(rs1)|E3|=4M2(GH)2((rs1)((a,b),(c,d))E1(dGH(a,b)+dGH(c,d))+rs((a,b),(c,d))E2(dGH(a,b)+dGH(c,d))+((a,b),(c,d))E3εGH(a,b)=1εGH(c,d)1((rs)dGH(a,b)+(rs1)dGH(c,d)))+(rs1)2|E1|+rs(rs|E2|+(rs1)|E3|).
(c)ENM3(GH)=((a,b),(c,d))E(GH)δenGH(a,b)+δenGH(c,d)=((a,b),(c,d))E1δenGH(a,b)+δenGH(c,d)+((a,b),(c,d))E2δenGH(a,b)+δenGH(c,d)+((a,b),(c,d))E3εGH(a,b)=1εGH(c,d)1δenGH(a,b)+δenGH(c,d)=2M1(GH)2rs|E(GH)|+2|E1|+|E3|.

 □

Corollary 3.16

  • (a)
    IfVω(G)=orVω(H)=, then
    ENM1(GH)=4M1(GH),ENM2(GH)=4M2(GH),
    ENM3(GH)=2M1(GH).
  • (b)
    If G and H are two complete graphs, then
    ENM1(GH)=ENM3(GH)=M1(GH),ENM2(GH)=M2(GH).

Example 3.17

For n4, we have

ENM1(P2Pn)=2n3+8n212,
ENM2(P2Pn)=4n4+24n3+24n248n48,
ENM3(P2Pn)=8n3+32n248.

3.5. Composition

The composition [11] of G and H having V(G) and V(H) as vertex sets and E(G) and E(H) as edge sets is a graph G[H] containing vertex set V(G)×V(H) and (a,b) is connected to (c,d) if and only if acE(G) or a=c and bdE(H).

Lemma 3.18

For any two graphs G and H

  • (a)

    If G and H are complete graphs, thenδenG[H](u,v)=dG[H](u,v).

  • (b)

    If G has at least one vertex withε(u)=1and H does not have any vertex withε(u)=1, thenδenG[H](u,v)=2dG[H](u,v).

  • (c)

    IfVω(G)andVω(H)are not empty sets, such that,|Vω(G)|=r,|Vω(H)|=s, then

    δenG[H](u,v)={2dG[H](u,v)+1rs,if εG[H](u,v)=1;2dG[H](u,v)rs,otherwise.

Theorem 3.19

For any two graphs G and H with|Vω(G)|=r,|Vω(H)|=sandrs>0. Then

(a)ENM1(G[H])=4M1(G[H])8rs|E(G[H])|+4(u,v)V(G[H])εG[H](u,v)=1dG[H](u,v)+(12rs+rs|V(G[H])|)rs.
(b)ENM2(G[H])=4M2(G[H])2[(rs1)((a,b),(c,d))E1(dG[H](a,b)+dG[H](c,d))+rs((a,b),(c,d))E2(dG[H](a,b)+dG[H](c,d))+((a,b),(c,d))E3εG[H](a,b)=1εG[H](c,d)1((rs)dG[H](a,b)+(rs1)dG[H](c,d))]+(rs1)2|E1|+rs(rs|E2|+(rs1)|E3|).
(c)ENM3(G[H])=2M1(G[H])2rs|E(G[H])|+2|E1|+|E3|.

Proof

(a) Applying Lemma 3.18(c), we get

ENM1(G[H])=(u,v)V(G[H])δenG[H]2(u,v)=(u,v)V(G[H])εG[H](u,v)=1δenG[H]2(u,v)+(u,v)V(G[H])εG[H](u,v)1δenG[H]2(u,v)=(u,v)V(G[H])εG[H](u,v)=1(2dG[H](u,v)(rs1))2+(u,v)V(G[H])εG[H](u,v)1(2dG[H]rs)2=4(u,v)V(G[H])εG[H](u,v)=1dG[H]2(u,v)4(rs1)(u,v)V(G[H])εG[H](u,v)=1dG[H](u,v)+(rs1)2rs+4(u,v)V(G[H])εG[H](u,v)1dG[H]2(u,v)4rs(u,v)V(G[H])εG[H](u,v)1dG[H](u,v)+r2s2|V(G[H])rs|=4M1(G[H])8rs|E(G[H])|+4(u,v)V(G[H])εG[H](u,v)=1dG[H](u,v)+(12rs+rs|V(G[H]))rs.

To prove (b) and (c) we use the edge partition of E(G[H]) which is similar to the edge partition of E(GH). Hence by Lemma 3.18(c), we have

(b)ENM2(G[H])=((a,b),(c,d))E(G[H])δenG[H](a,b)δenG[H](c,d)=((a,b),(c,d))E1δenG[H](a,b)δenG[H](c,d)+((a,b),(c,d))E2δenG[H](a,b)δenG[H](c,d)
+((a,b),(c,d))E3εG[H](a,b)=1εG[H](c,d)1δenG[H](a,b)δenG[H](c,d)=((a,b),(c,d))E1(2dG[H](a,b)(rs1))(2dG[H](c,d)(rs1))+((a,b),(c,d))E2(2dG[H](a,b)rs)(2dG[H](c,d)rs)+((a,b),(c,d))E3εG[H](a,b)=1εG[H](c,d)1(2dG[H](a,b)(rs1))(2dG[H](c,d)rs)=4((a,b),(c,d))E1dG[H](a,b)dG[H](c,d)2(rs1)((a,b),(c,d))E1(dG[H](a,b)+dG[H](c,d))+(rs1)2|E1|+4((a,b),(c,d))E2dG[H](a,b)dG[H](c,d)2rs((a,b),(c,d))E2(dG[H](a,b)+dG[H](c,d))+r2s2|E2|+4((a,b),(c,d))E3εG[H](a,b)=1εG[H](c,d)1dG[H](a,b)dG[H](c,d)2((a,b),(c,d))E3εG[H](a,b)=1εG[H](c,d)1(rsdG[H](a,b)+(rs1)dG[H](c,d))+rs(rs1)|E3|=4M2(G[H])2[(rs1)((a,b),(c,d))E1(dG[H](a,b)+dG[H](c,d))+rs((a,b),(c,d))E2(dG[H](a,b)+dG[H](c,d))+((a,b),(c,d))E3εG[H](a,b)=1εG[H](c,d)1((rs)dG[H](a,b)+(rs1)dG[H](c,d))]+(rs1)2|E1|+rs(rs|E2|+(rs1)|E3|).
(c)ENM3(G[H])=((a,b),(c,d))E(G[H])δenG[H](a,b)+δenG[H](c,d)=((a,b),(c,d))E1δenG[H](a,b)+δenG[H](c,d)+((a,b),(c,d))E2δenG[H](a,b)+δenG[H](c,d)+((a,b),(c,d))E3εG[H](a,b)=1εG[H](c,d)1δenG[H](a,b)+δenG[H](c,d)=((a,b),(c,d))E1((2dG[H](a,b)(rs1))+(2dG[H](c,d)(rs1)))+((a,b),(c,d))E2((2dG[H](a,b)rs)+(2dG[H](c,d)rs))+((a,b),(c,d))E3εG[H](a,b)=1εG[H](c,d)1((2dG[H](a,b)(rs1))+(2dG[H](c,d)rs))=2((a,b),(c,d))E1(dG[H](a,b)+dG[H](c,d))2(rs1)|E1|+2((a,b),(c,d))E2(dG[H](a,b)+dG[H](c,d))2rs|E2|+((a,b),(c,d))E3εG[H](a,b)=1εG[H](c,d)1(dG[H](a,b)+dG[H](c,d))(2rs1)|E3|=2M1(G[H])2rs|E(G[H])|+2|E1|+|E3|.

 □

Corollary 3.20

If G and H are complete graphs, thenENM1(G[H])=ENM3(G[H])=M1(G[H]), andENM2(G[H])=M2(G[H]).

Corollary 3.21

If G has at least one vertex withε(u)=1and H does not have any vertex withε(u)=1, then

ENM1(G[H])=4M1(G[H]),ENM2(G[H])=4M2(G[H]),
ENM3(G[H])=2M1(G[H]).

Example 3.22

For n4, we have

ENM1(P2[Pn])=8n3+32n248,
ENM2(P2[Pn])=4n4+24n3+24n248n48,
ENM3(P2[Pn])=4n3+16n224.

3.6. Symmetric difference

The symmetric deference [11] GH is defined by V(GH)=V(G)×V(H) and E(GH)={((a,b),(c,d)):acE(G)orbdE(H)butnotboth}.

Lemma 3.23

For any two graphs G and H

δenGH(u,v)=2dGH(u,v)

Theorem 3.24

For any two graphs G and H

ENM1(GH)=4M1(GH),
ENM2(GH)=4M2(GH),
ENM3(GH)=2M1(GH).

Example 3.25

ENM3(P2Pn)=4n3,
ENM1(P2Pn)=2ENM3(P2Pn),
ENM2(P2Pn)=nENM3(P2Pn).

4. Conclusion

In this article, we've introduced new indices referred to as eccentric neighborhood Zagreb indices. These indices have been conceptualized and their discriminating power investigated with regard to the predictability of the boiling point of the chemical substances, as the correlation coefficients between 0.9814 and 0.993 were acquired greater than the ones received in the case of eccentric connectivity and Winner indices. We have calculated those indices for some graphs and additionally studied a number of their characteristics. We've got calculated the formulation for some graph operations such as join, disjunction, composition, and symmetric deference. Because these indices are appearing for the first time, we have some issues to address in the feature, such as

  • 1.

    Define some new versions of these topological indices that are parallel to the usual Zagreb topological indices.

  • 2.

    Which graphs have the highest value for those indices as well as the lowest value?

  • 3.

    The investigation of bounds is still an open area to study.

  • 4.

    The mathematical relationships between the new and prior indices.

  • 5.

    Used such indices to analyze certain significant chemical substances.

  • 6.

    Investigating the polynomials that are connected to these indices.

CRediT authorship contribution statement

Hanan Ahmed: Performed the experiments; Analyzed and interpreted the data; Wrote the paper.

Anwer Saleh: Conceived and designed the experiments.

Rashad Ismail, Ruby Salestina M, Abdu Alameri: Contributed reagents, materials, analysis tools or data.

Declaration of Competing Interest

The authors declare that they have no competing interests.

Acknowledgements

The third author expresses his appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through large group Research Project under Grant Number (R.G.P.2/163/44).

Contributor Information

Hanan Ahmed, Email: hananahmed1a@gmail.com.

Anwar Saleh, Email: math.msfs@gmail.com.

Rashad Ismail, Email: rismail@kku.edu.sa.

Ruby Salestina M, Email: ruby.salestina@gmail.com.

Abdu Alameri, Email: a.alameri.2222@gmail.com.

Data availability

Data included in article/supp.material/referenced in article

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