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Article

New Insights into Aromaticity through Novel Delta Polynomials and Delta Aromatic Indices

by
Krishnan Balasubramanian
School of Molecular Sciences, Arizona State University, Tempe, AZ 85287-1604, USA
Symmetry 2024, 16(4), 391; https://doi.org/10.3390/sym16040391
Submission received: 6 March 2024 / Revised: 19 March 2024 / Accepted: 20 March 2024 / Published: 27 March 2024
(This article belongs to the Collection Feature Papers in Chemistry)

Abstract

:
We have developed novel polynomials called delta polynomials, which are, in turn, derived from the characteristic and matching polynomials of graphs associated with polycyclic aromatic compounds. Natural logarithmic aromatic indices are derived from these delta polynomials, which are shown to provide new insights into the aromaticity of polycyclic aromatic compounds, including the highly symmetric C60 buckminsterfullerene, several other fullerenes, graphene, kekulene series and other cycloarenes, such as polycyclic circumcoronaphenes and coronoids. The newly developed aromatic index yields a value of 6.77 for graphene, 6.516865 for buckminsterfullerene C60(Ih), 5.914023 for kekulene (D6h symmetry), 6.064420 for coronene (D6h), 6.137828 for circumcoronene (D6h), 6.069668 for dicronylene and so forth. Hence, the novel scaled logarithmic aromatic delta indices developed here appear to provide good quantitative measures of aromaticity, especially when they are used in conjunction with other aromatic indicators.

1. Introduction

The concept of aromaticity has intrigued both experimental [1,2,3,4,5,6,7,8,9,10,11,12] and theoretical chemists [13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69] resulting in a plethora of publications on the topic over the decades. The landscape of aromatic compounds has dramatically metamorphosed with the advent of molecules such as the highly symmetric buckminsterfullerene [1]; various fullerenes [2]; and circumcised coronoidal polycyclic aromatics, such as kekulene [3,4,5], septulene [6], octulene [7], porous nanographenes [9,10,11,12,13,14,15,16] and so forth. Consequently, the old concepts of aromaticity that included primarily planar polycyclic compounds with 4 n + 2 π-electrons has evolved into intriguing concepts such as the 3D-aromaticity, spherical aromaticity, superaromaticity, etc., and thus encompass non-planar compounds and even compounds that do not strictly conform to the 4n + 2 π-electron rule. Circumcised coronoidal polycyclic aromatic compounds that display extended macrocyclic conjugation such as circumkekulene, non-alternant septulene [6], nanographenes [9,10,11,12,13,14,15,16] and the truncated icosahedral C60 with Ih symmetry [1,2], the cynosure of fullerenes, have all contributed to the evolution of the topics of aromaticity and superaromaticity to encompass such a large array of varied compounds in striking contrast to planar polycyclics with 4n + 2 π-electrons [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69]. Consequently, the aromaticity concept continues to challenge our understanding owing to the enhanced thermodynamic stability of several of these polycyclic compounds that can only be explained through the generalization of these concepts to encompass the phenomenon of superaromaticity and spherical aromaticity. Yet aromaticity continues to be an elusive concept, defying our established conceptual platforms and pointing to the compelling requirement for the development of novel ideas to encompass such a varied platform of polycyclic compounds that exhibit enhanced thermodynamic or kinetic stabilities.
The advent of kekulene [3,4,5], a circumcised coronene with D6h symmetry, demonstrates the existence of a structure with a cavity made possible by an assembly of angularly annulated benzene rings which arises from a combination of two interacting [4n + 2]annulenes. The enhanced thermodynamic stability of kekulene is experimentally demonstrated with the synthesis of this molecule and the observed proton NMR chemical shifts and magnetic properties—all of which suggest that the extended ring currents arise from individual benzene rings [3,4,5], as opposed to overly extended delocalizations around the entire structure. Furthermore, sister polyarene molecules with cavities such as septulene and octulene have been synthesized over the years [6,7], although septulene, with a seven-fold symmetry exhibiting the D7h point group, does not conform to the traditional notion of an alternant polycyclic aromatic compound. Notwithstanding the fact that septulene [6] is not alternant and does not conform to the typical [4n + 2] rule, it exhibits electronic and magnetic properties that are reminiscent of kekulene, provoking us to revisit our conventional notions of aromatic compounds.
Topological, group theoretical and graph theoretical techniques [13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70] have been developed and applied to a large number of polycyclic aromatic compounds, organic polymers, fullerenes, circumcised coronoidal structures with cavities, nanographenes and so forth with the objective of shedding light on their structures, spectra, combinatorial chemistry, properties, magnetic and electronic features, aromaticity and toxicity. One such technique that has enjoyed considerable success is the conjugated circuit theory [42,43,44,65], which relies on the combinatorial enumeration of inherent conjugated circuits and Clar’s aromatic sextets [19,28,40]. The technique has facilitated a reliable platform for understanding the relative stabilities, aromaticity and magnetic and electronic properties of polycyclic aromatics. Furthermore, such combinatorial and graph theoretical methods have provided significant new insights into intriguing phenomena such as superaromaticity, which is a form of macrocyclic aromaticity. These techniques have revealed that the macrocyclic conjugation inherent to these structures is the primary cause of their enhanced thermodynamic stability. Combinatorics and graph theory have been applied to the enumeration of conjugated circuits, isomers of polycyclic aromatics and their derivatives, spectral polynomials, matching polynomials, distance polynomials and a number of polycyclic aromatics and fullerene cages [13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76]. An intriguing feature of such applications is that some of these symmetry-based techniques involve such novel group theoretical techniques, such as Euler’s totient functions, Polya’s theory of enumeration, etc., to predict their polysubstituted isomers and spectra [77]. Many of these polysubstituted aromatics, macrocyclic arenes, heteropolycyclic arenes and related halocarbons have been studied owing to their significant importance as environmental pollutants, carcinogens, hepatotoxins, industrial chemicals and petroleum products. Furthermore, macrocyclic compounds find applications in the environmental remediation through the selective sequestration of metal ions, and consequently, they find important applications in the sequestration of toxic metal ions, for example, in high-level nuclear wastes. Hosoya [21] has carried out pioneering studies connecting symmetry and matchings of graphs and extensive work has been carried out by Hosoya [18,19,20,21,22,23,24], Aihara [13,23,25,26,29,30,31,32,33,35,40,49,50,51,52,53,54,55], Dias [34,35,36,37,38,39,53,56,57,58] and the author and coworkers [16,66,67,68,69,70,71,72,73,74,75,76] connecting such polynomials, graph theoretical concepts, resonance energies and so forth to gain insights into aromaticity.
The above survey of experimental and theoretical interest in aromaticity and polycyclic compounds clearly demonstrates significant interest in the topic and the somewhat elusive nature of aromaticity. Despite all these developments, aromaticity continues to baffle researchers in this field due to the varied complexity of compounds that belong to this class. Stimulated by several pioneering conceptual studies that we have cited herein, the present work extends several of these ideas to encompass both characteristic and matching polynomials to evolve into novel aromatic scaled delta and zeta indices together with delta polynomials. We have knitted many of these concepts into a novel fabric of aromaticity in order to apply these concepts to a vast array of polycyclics, including three-dimensional fullerenes and polycyclic structures containing cavities as well as conventional polycyclic aromatics. We demonstrate the utility of delta polynomials and the novel indices that we propose in this study for a variety of such compounds.

2. Delta Polynomials: Mathematical and Computational Methods

We start with the definition of the adjacency matrix of a graph:
A i j = 1   i f   v e r t i c e s   i   a n d   j   a r e   c o n n e c t e d 0   o t h e r w i s e
An important graph–theoretical invariant, although not unique, is the characteristic polynomial of the graph, denoted by PG. The characteristic or the spectral polynomial of a graph is given by:
P G x =   x I A = C n x n + C n 1 x n 1 + + C 1 x + C 0
where Ck, is the kth coefficient in the characteristic polynomial, which can be interpreted combinatorically through Sachs’ theorem:
C k = g G i ( 1 ) c ( g ) 2 r ( g )
Gis is Sachs’ subgraph of G containing k vertices; c(g) is the disconnected components in g; and r(g) is the number of cycles in the subgraph g. The related matching polynomial or the acyclic polynomial of a graph G can be defined with p(G, k), which is the number of ways to place k disjoint dimers on the graph G:
M G x = k = 0 [ n 2 ] 1 k p G , k x n 2 k
where [n/2] is the greatest integer contained in n/2. For any graph containing an even number of vertices, the coefficients of the odd terms are zero, and consequently, they are not included in the above definition of the matching polynomials. We also note that the constant coefficient in the matching polynomial enumerates the number of Kekulé structures or full coverings with matching for any graph G. Another way to express the matching polynomial that would include zero alternating coefficients is:
M G x = k = 0 n 1 k a k x n k
where ak is zero for odd terms while it is the number of dimers for even terms. Hence, ak is sometimes called the acyclic coefficient, while MG(x) is also referred to as the acyclic polynomial as it contains the acyclic components of Sachs’ subgraphs in G. The above definition is more convenient to compare the matching polynomial and the characteristic polynomial of a graph.
The spectra of a graph G are simply the eigenvalues of the adjacency matrix or the roots of the characteristic polynomial as defined above. Likewise, the roots of the matching polynomial constitute the matching spectra of G. For several graphs, the present author [74] showed that the matching spectra are the eigenvalues of complex-edge-weighted graph derived from G by assigning complex weights so that the overall adjacency matrix is hermitian. Moreover, Hosoya and the author [78,79] have shown that the matching polynomials of a number of graphs can be obtained as the characteristic polynomials of complex-edge weighted graphs, although these techniques are restricted to a few graphs and the weighting scheme becomes more complicated for larger graphs containing multiple fused cycles. As shown by Aihara [33], an important insight can be obtained into aromaticity through the concept of topological resonance energy, which is obtained as the weighted algebraic sum of the difference between graph spectral eigenvalues and the matching spectral values. Although this is an important measure of aromaticity, it is a difficult quantity to deal with as the matching spectra of graphs containing a large number of vertices with several fused cycles as in polycyclic aromatic compounds are difficult to obtain, although the graph spectra can be more readily obtained by diagonalizing the adjacency matrix by invoking symmetry or by the standard Givens–Householder tri-diagonalization technique. Even for graphs containing a very large number of vertices, it has been shown that the Hadamard transform technique can be employed to extract all eigenvalues of the adjacency matrix [80].
Consequently, the bottleneck of the topological resonance energy computation lies in the computation of matching spectra for highly clustered graphs containing large numbers of vertices. Although Aihara [33] suggested the use of bond resonance energy and circuit resonance energy to circumvent this difficulty, the quantitative measures of aromaticity continue to pose challenges for graphs containing multiple fused cycles with a large number of vertices.
Stimulated by the works of Hosoya [18,19,20,21,22,23,24] as well as Hosoya and the current author [78,79], we propose here novel polynomials which we call delta polynomials and derive natural logarithmic aromatic indices from the coefficients of delta polynomials. The delta polynomial for any graph is defined as follows:
δ G x = k = 0 n | C k   a k |   x n k = k = 0 n δ k x n k
where Ck and ak are the coefficients from the characteristic polynomial and matching polynomial, respectively. We note that the coefficients in the delta polynomial are always non-negative, and the first few terms of the delta polynomial tend to be zero. Moreover, for trees or acyclic polyenes, all coefficients in the delta polynomials are identically zero because the matching and characteristic polynomials become identical for trees. As seen from Sachs’ theorem, the coefficients of the characteristic polynomials contain both cyclic and acyclic components while the coefficients of the matching polynomials contain purely acyclic components. Consequently, delta polynomials contain all important cyclic components of various lengths together with some dimeric components, and thus include several important measures required to provide quantitative measures of aromaticity. However, as these coefficients tend to increase in magnitude sharply for larger graphs, we define two aromatic indices based on the coefficients of delta polynomials.
a = 1 n ln | δ k | ,  
w = 1 n ln k | δ k | ,
where the sum is taken over all non-zero coefficients of the delta polynomial and n is the number of vertices in the graph. The second aromatic index is considered a weighted index, as it includes the lengths of various components that are purely non-acyclic. Note that for comparison, Hosoya’s Z index [18,21,22] and the related Zc index are obtained from the coefficients of the matching and characteristic polynomials as defined by:
Z = | a k |
Z c = | C k |
As both Z and Zc grow astronomically, and in order to make them comparable to our delta aromatic indices, we introduce two indices using the scaled natural logarithmic functions as follows:
ζ M = 1 n ln | a k |
ζ C = 1 n ln | C k |
where the first zeta-index is obtained using the coefficients of the matching polynomial, while the second zeta-index is obtained from the coefficients of the characteristic polynomials. Consequently, we have four measures that can be computed and compared for different graphs. Among these, we have found that both regular and weighted delta indices are good predictors of aromaticity and the relative order of aromaticity among a variety of compounds that we compare here.
The characteristic polynomials of all structures were computed using the Frame method developed previously [71,72,73,74] while the matching polynomials were computed using a recursive pruning algorithm described in detail in previous studies [71,72,73,74]. We note that the philosophy behind the delta index in comparison to the zeta indices is that the zeta index derived from the matching polynomial includes only acyclic contributions while the zeta index obtained from the characteristic polynomial includes both cyclic and acyclic contributions without any differentiation. Therefore, the delta indices offer a compromise as they completely eliminate purely acyclic components. The other advantage of the delta indices is that unlike the topological resonance energy or bond energy or circuit energy computations that require the eigenvalues, the delta indices are easier to compute as they involve only the coefficients of the matching and characteristic polynomials. This is an advantage because for larger systems, the computations of all roots of the matching polynomials with reasonable accuracy could pose problems. It appears that the delta indices offer a reasonable comprise and yet they seem to closely mimic the aromaticity trends. It should be noted that the delta polynomials go to zero for trees or purely acyclic molecules, which is consistent with the fact that such compounds are not aromatic, and hence the delta indices are not defined for such purely acyclic molecules that are not aromatic. The next section describes the results of our computations and comparison of a number of polycyclic compounds with varied complexity, including three-dimensional structures such as fullerenes C60 and C70.

3. Results and Discussion

We considered a number of structures with varied complexities for the study of delta polynomials and the zeta and delta aromatic indices of these structures. Figure 1 shows a compilation of such structures that were considered in this study. As seen from Figure 1, we included planar polycyclic compounds and three-dimensional spherical structures such as C60, C70 and C72, as well as polycyclic structures with holes, such as kekulene, septulene and a zigzag macrocycle containing 21 rings. Consequently, these structures offer quite a varied platform for the comparison of relative aromaticity on the basis of the various computed indices.
Table 1 illustrates the computation of various aromatic indices; we have included the characteristic and matching polynomials of isomers of very simple structures with three benzene rings, that is, phenanthrene and anthracene. As can be seen from Table 1, as both are purely alternant benzenoids, as characterized by their bipartite graphs, the coefficients of the odd terms are zeroes. The constant term of the matching polynomial is simply the number of resonance structures, which is five for phenanthrene and four for anthracene, a well-known result, indicating that phenanthrene is more aromatic than anthracene. Herndon’s [81] resonance energy is simply formulated as a scaled log of the number of resonance structures multiplied with a constant. However, we note that the constant term in the matching polynomial alone does not correlate with aromaticity or the stability of a structure. One needs to consider the contributions from various circuits, which are included in the other coefficients. The coefficients of other terms in the two polynomials yield the combinatorial numbers for other Sachs’ subgraphs. The delta polynomials thus contain only non-acyclic terms enumerated among the Sachs’ subgraphs, although some of the terms contain both disjoint circuits and dimers. The last but one row in Table 1 shows the sum of the coefficients of the characteristic polynomial, the sum of the coefficients of the matching polynomial, the well-known Hosoya’s [18,22] Z index and, finally, the corresponding sums of delta polynomial coefficients. We also introduced a new weighted index concept that we designate as k δ k , which weighs over different components of the Sachs’ non-acyclic graphs. The philosophy behind this is that not all Sachs’ circuits contained in different coefficients make the same contribution, and hence one needs to introduce weights as given by the total number of vertices in these disjointed circuits or simply k. For example, k = 8 would designate a circuit of length 8, a circuit of length 6 + a dimer, and so forth. Thus, by weighting the coefficients with k, we have taken this important factor into account, that is, not all coefficients have the same circuit lengths, and thus, the weighting method provides a means for contrasting their contributions. The last row shows the scaled natural logarithmic indices derived from these sums. First, the natural logarithmic functions reduces the astronomically large combinatorial numbers for the sums of these coefficients for large polycyclics. This, combined with a scaling method, in which we divide the natural logarithm by the number of vertices, eliminates the size dependency. Thus, the scaled logarithmic index provides a uniform basis to compare and contrast the aromaticity of a large number of polycyclic compounds with varied sizes and complexities. Therefore, as can be seen from Table 1, phenanthrene has scaled zeta and delta indices of ζC: 0.5218471, ζM: 0.5083718, Δ:0.3960841 and Δw: 0.5642518, while the corresponding indices for anthracene are ζC: 0.5194570, ζM: 0.5069087, Δ: 0.3890527 and ΔW: 0.5559446. It was noted that the indices reveal a contrast between phenanthrene and anthracene and predict a correct trend of aromaticity. However, in general cases, as the Hosoya index is derived from purely acyclic or dimer terms, while aromaticity involves circuits, delta indices, especially in the weighted forms, offer a good measure of aromaticity. This is especially true when a comparison needs to be made for compounds of varied sizes and complexities. All techniques lead to the same conclusion that phenanthrene is more aromatic than anthracene, as expected. We also obtained the delta polynomials of a number of zigzag and linear polyacenes of larger sizes. The general trend is that the weighted delta index is larger for the zigzag structures compared to linear polyacenes, which is consistent with the trend that the zigzag polyacenes are more aromatic than linear polyacenes. This arises from a Fibonacci increase in the resonance count for each kink in the structure of a zigzag polyacene. This in turn translates into a larger weighted delta index for a zigzag polycyclic as compared with a linear polyacene.
The two simple cases are considered for illustrative purposes only, as we demonstrate the power of the techniques with more complex polycyclics starting with coronene and circumcoronene. The computed results for these two structures are shown in Table 2 and Table 3, respectively. As seen from these tables, the first several terms of the delta polynomials are zeroes, as these terms contain only purely acyclic contributions. For coronene, the first non-zero term in the delta polynomial corresponds to the seventh term, which contains the contributions of from a hexagon in the structure, and since there are no four-membered rings in the structure, only hexagons make contributions to this term. Starting with this term, all other subsequent terms contain various other types of circuits in the structure together with contributions from some disjoint dimers. Consequently, the unweighted delta indices computed from the coefficients of the delta polynomial are 0.4897992 and 0.5482407, respectively, clearly suggesting that circumscribing coronene results in considerably enhanced aromaticity. The constant coefficients of the two matching polynomials are given by 20 and 980, respectively, which are also the well-known Kekulé counts of the two structures. As these are purely alternant benzenoid polycyclic aromatic compounds, the square of the constant coefficients in the matching polynomials yields the constant coefficients in the characteristic polynomial. We shall discuss in a subsequent paragraph the weighted delta index together with the other indices of all polycyclics considered in this study. Table 4 shows the various polynomials obtained for kekulene together with the corresponding unweighted zeta and delta indices. Kekulene can be generated by the circumcision of the central hexagon of the coronene structure. Consequently, when one compares the unweighted delta indices of the two structures, one can infer that circumcision results in a lower delta index for kekulene compared to coronene. That is, circumcision disrupts the various circuits that were present in coronene, resulting in a lower π-electronic ring current or lower aromaticity in kekulene compared to coronene. This feature is mirrored by the delta indices of the two structures.
Table 5 and Table 6 consider three polycyclic isomers of C22H12 and the corresponding circumscribed structures of the three isomers, respectively. The three isomers have been enumerated in the handbook by Dias [57] on polycyclic aromatic compounds. The three isomers, namely, triangulene, anthanthrene and benzo[ghi]perylene, represent interesting cases for our study. Among these, triangulene exhibits a triplet electronic ground state and it is thus a diradical. We note that this is directly inferred by the zero coefficient of the constant term of the characteristic polynomial of triangulene, consistent with a doubly degenerate set of HOMOs, resulting in a triplet ground state. As seen from Table 5, the delta indices of the three structures indicate that bezo[ghi]pyrelene is the most aromatic of the three structures with triangulene being the least aromatic. Although the combinatorial numbers in Table 6 become more complex due to a greater number of various circuits in the corresponding circumscribed structures, the final delta indices are much more amenable to critical comparison and thus shed light on the potential aromaticity of these compounds. Again, comparing the delta indices of the primitive and circumscribed counterparts in Table 5 and Table 6 reveals that circumscribing results in greater aromaticity compared to the uncircumscribed structure. The gaps relative to aromaticity among the isomers are narrowed somewhat when one compares the circumscribed structures to their uncircumscribed counterparts. In particular, triangulenes obtain a greater aromaticity upon circumscribing. However, we note that better measures are obtained using the weighted delta indices which we compare in a subsequent Table and paragraph. Furthermore, as seen from Table 6, the constant coefficient of the circumscribed triangulene continues to be zero for the characteristic polynomial suggesting that circumtriangulene continues to exhibit a triplet diradical ground state although its aromaticity is enhanced relative to the primitive triangulene structure. This trend is repeated by a number of structures that we have tested and are not shown here. The general trend is that circumscribing a given structure results in enhanced aromaticity while circumcision results in lower aromaticity.
Next, we consider three-dimensional and other structures that appear to exhibit aromatic characters or unusual stabilities. The celebrated buckminsterfullerene with the icosahedral Ih group has been the cynosure of fullerenes. Table 7 displays all three polynomials of C60 together with the sums of the columns and the scaled natural log indices. There are several differences that should be noted in the polynomials for the C60 structure compared to the other polycyclics that we have considered thus far. None of the coefficients of the odd terms except the first two odd terms is zero for the characteristic and delta polynomials of C60. For example, the sixth or fifth coefficient, not counting the first term, is twenty-four for the delta polynomial and is consistent with the twelve pentagons present in the structure. Likewise, all other odd terms are non-zeroes and contribute toward the delta polynomial. This is a striking contrast compared to alternant benzenoid hydrocarbons. Furthermore, the square of the constant term in the matching polynomial does not yield the constant term of the characteristic polynomial. These features, together with several non-zero odd terms in the delta polynomials, provide C60 with some unique features. Although the sum of all the coefficients of the delta polynomial is 2508935631291784, a large number, the scaled log of the corresponding result is 0.5909773, suggesting that its unweighted delta aromaticity is much higher than the circumcoronene value of 0.5482407 and even circumcircumcoronene, circumkekulene and so forth. The weighted delta aromatic indices yield further insights, as we will now discuss. These results of C60 can also be compared with the corresponding indices of other fullerenes, such as C70(D5h) and C72(C2v), as shown below.
These computations can be extended to large macrocycles, such as the one shown in Figure 1 containing 21 hexagons arranged in a zigzag fashion with a large internal cavity. The various polynomials for such a macrocycle are shown in Table 8. As this is an alternant benzenoid hydrocarbon, we show only the coefficients of the even terms as all odd terms have zero coefficients for all three polynomials. This macrocycle with a zigzag structure has a delta index of 0.5352335, making it comparable to circumcoronene, which has a delta index of 0.5482407. This implies that the zigzag macrocycle with 21 rings less aromatic compared to circumcoronene but more aromatic compared to kekulene with a delta index of 0.5203879. We note that the weighted delta index appears to provide yet another reliable way to compare different structures, although any of these indices should be used in conjunction with other parameters, such as the HOMO-LUMO gap or electronic or magnetic parameters derived from quantum chemical computations.
Table 9 shows a cumulative across-board comparison of all four indices of all structures that are considered in the present study. As both delta and zeta indices are derived from scaled natural log values, we uniformly multiplied the indices by a factor of 10 in Table 9 for comparison. It can be seen from Table 9 that the weighted delta index appears to provide one of the best measures of aromaticity and stability. For example, the weighted delta index of buckminsterfullerene stands out as 6.516865, a maximum among all structures considered here with the exception of graphene. In fact, while the weighted delta index of buckminsterfullerene is higher than both C70(D5h) and C72(C2v), this trend is not reproduced by any of the other indices shown in Table 9. We note that both C72(C2v) and C72(D6d) structures have been found to be stable isomers [82,83]. Moreover, we note that as the weighted delta indices do not vary in large magnitude, and small changes should be considered important as the weighted indices are subtle in their variations. As seen from Table 9, circumcoronene is more aromatic than coronene as well as hexbenzcoronene. Polycyclic structures with cavities, such as coronaphene, circumcoronaphene, kekulene, etc., are less aromatic compared to their parent structures prior to circumcision. On the other hand, kekulene and septulene have a remarkably similar aromaticity, as inferred from their weighted delta indices of 5.914023 and 5.884901, respectively. Of the three C22H12 isomers, triangulene exhibits the least aromaticity while benzo[ghi]perylene exhibits the greatest aromaticity. We also note a few variations in trends, for example, ovalene is predicted to be much less aromatic compared to circumovalene on the basis of zeta and unweighted delta index but the weighted delta index exhibits the same trend but with a smaller contrast. While circumpyrene is predicted to be less aromatic compared to circumovalene on the basis of the zeta and unweighted delta indices, the weighted delta index predicts the opposite trend with a smaller contrast.
Kekulene and septulene are virtually identical relative to the zeta indices, as can be seen from Table 9. The identical values of the scaled Hosoya index require further inquiry. Moreover, the delta index suggests an opposite trend, in that it predicts septulene to be slightly more aromatic compared to kekulene, although the weighted delta index predicts kekulene to be slightly more aromatic than septulene. The sum of the coefficients of the three polynomials and the weighted sum for kekulene are given as 170396692000, 99914817684, 70481874316 and 2130357387264, respectively. The corresponding values for septulene are 12686887009024, 6806150529706, 5880736479318 and 205289991176192, respectively. Consequently, although these numbers are quite different for kekulene and septulene, when they are scaled by the number of vertices after taking log of these values, accidental degeneracy is reached for kekulene relative to Hosoya’s Z index while the Zc index is almost the same. Thus, these two indices fail to differentiate septulene and kekulene while the weighted delta index appears to provide the correct trend.
We were able to obtain an estimate of the aromaticity delta index for graphene using an extrapolation scheme by using the results of coronene, circumcoronene and circumcircumcoronene. A previous study on the degree-based topological indices of series of polycyclic aromatics [69] has revealed that if one extrapolates the results of known circumcoronene series with the order of circumscribing as n~6.4, one obtains the results converging to graphene. By using the same extrapolation scheme with the results obtained for coronene, circumcoronene and circumcircumcoronene, we obtain the weighted and unweighted delta indices for graphene converging to 6.77. Consequently, one can compare this value to C60 value of 6.5116865 and conclude that the correct trend is predicted by the newly formulated delta aromatic indices and delta polynomials. Indeed, the highly symmetric buckminsterfullerene is confirmed to be the most stable species among small molecules, fullerenes, and clusters, which corroborates with experimental observations. Furthermore, we note that other topological indices have been applied to different forms of carbon and other complex networks such as diamond and other metal organic frameworks [84,85].

4. Conclusions

In this study, we proposed hybrid polynomials called delta polynomials and created two scaled logarithmic indices, which we called delta aromatic indices. These indices combined with the zeta indices, which are also scaled versions, were evaluated for a number of polycyclic structures, including fullerenes, kekulenes, septulene, circumcoronene, circumcoronaphene, dicronylene, macrocycles and different isomers of polycyclic compounds. It was shown that the delta indices, especially the weighted delta indices, appear to conform closely with the aromaticity trends of the investigated compounds. We suggest that these newly proposed delta indices can be used in conjunction with other topological, electronic, magnetic and quantum chemical parameters to gain considerable insights into the longstanding phenomenon of aromaticity, superaromaticity and spherical aromaticity.

Funding

This research received no external funding.

Data Availability Statement

All data used in this manuscript are contained in the manuscript.

Conflicts of Interest

The author declares no conflicts of interest.

References

  1. Kroto, H.W.; Heath, J.R.; O’Brien, S.C.; Curl, R.F.; Smalley, R.E. C60: Buckminsterfullerene. Nature 1985, 318, 162–163. [Google Scholar] [CrossRef]
  2. Smalley, R.E. Discovering the fullerenes. Rev. Mod. Phys. 1997, 69, 723–730. [Google Scholar] [CrossRef]
  3. Diederich, F.; Staab, H.A. Benzenoid versus Annulenoid Aromaticity: Synthesis and Properties of Kekulene. Angew. Chem. Int. Ed. Engl. 1978, 17, 372. [Google Scholar] [CrossRef]
  4. Schweitzer, D.; Hausser, K.H.; Vogler, H.; Diederich, F.; Staab, H. Electronic Properties of Kekulene. Mol. Phys. 1982, 46, 1141–1153. [Google Scholar] [CrossRef]
  5. Staab, H.A.; Diederich, F.; Krieger, C.; Schweitzer, D. Cycloarenes, a New Class of Aromatic Compounds, I. Synthesis of Kekulene. Chem. Ber. 1983, 116, 3. [Google Scholar] [CrossRef]
  6. Kumar, B.; Viboh, R.L.; Bonifacio, M.C.; Thompson, W.B.; Buttrick, J.C.; Westlake, B.C.; Kim, M.; Zoellner, R.W.; Varganov, S.A.; Mörschel, P.; et al. Septulene: The heptagonal homologue of kekulenes. Angew. Chem. Int. Ed. 2012, 51, 12795–12800. [Google Scholar] [CrossRef] [PubMed]
  7. Majewski, M.A.; Hong, Y.; Lis, T.; Gregoliński, J.; Chmielewski, P.J.; Cybińska, J.; Kim, D.; Stępień, M. Octulene: A Hyperbolic Molecular Belt that Binds Chloride Anions. Angew. Chem. Int. Ed. 2016, 55, 14072–14076. [Google Scholar] [CrossRef] [PubMed]
  8. Wu, J.; Watson, M.D.; Zhang, L.; Wang, Z.; Müllen, K. Hexakis(4-iodophenyl)-peri-hexabenzocoronene-A Versatile Building Block for Highly Ordered Discotic Liquid Crystalline Materials. J. Am. Chem. Soc. 2004, 126, 177–186. [Google Scholar] [CrossRef] [PubMed]
  9. Beser, U.; Kastler, M.; Maghsoumi, A.; Wagner, M.; Castiglioni, C.; Tommasini, M.; Narita, A.; Feng, X.; Müllen, K. A C216-nanographene molecule with defined cavity as extended coronoid. J. Am. Chem. Soc. 2016, 138, 4322–4325. [Google Scholar] [CrossRef]
  10. Xu, K.; Urgel, J.I.; Eimre, K.; Di Giovannantonio, M.; Keerthi, A.; Komber, H.; Wang, S.; Narita, A.; Berger, R.; Ruffieux, P.; et al. On-surface synthesis of a nonplanar porous nanographene. J. Am. Chem. Soc. 2019, 141, 7726–7730. [Google Scholar] [CrossRef]
  11. Kato, K.; Takaba, K.; Maki-Yonekura, S.; Mitoma, N.; Nakanishi, Y.; Nishihara, T.; Hatakeyama, T.; Kawada, T.; Hijikata, Y.; Pirillo, J.; et al. Double-helix supramolecular nanofibers assembled from negatively curved nanographenes. J. Am. Chem. Soc. 2021, 143, 5465–5469. [Google Scholar] [CrossRef]
  12. Zhu, X.; Liu, Y.; Pu, W.; Liu, F.-Z.; Xue, Z.; Sun, Z.; Yan, K.; Yu, P. On-Surface Synthesis of C144 Hexagonal Coronoid with Zigzag Edges. ACS Nano 2022, 16, 10600–10607. [Google Scholar] [CrossRef] [PubMed]
  13. Sakamoto, K.; Nishina, N.; Enoki, T.; Aihara, J.-I. Aromatic character of nanographene model compounds. J. Phys. Chem. A 2014, 118, 3014–3025. [Google Scholar] [CrossRef]
  14. Jorner, K. Revisiting the superaromatic stabilization energy as a local aromaticity index for excited states. J. Phys. Org. Chem. 2022, 36, e4460. [Google Scholar] [CrossRef]
  15. Li, D.; Yang, J.; Cheng, L. A unified superatomic-molecule theory for local aromaticity in π-conjugated systems. Natl. Sci. Rev. 2022, 10, nwac216. [Google Scholar] [CrossRef] [PubMed]
  16. Balasubramanian, K. Density functional and graph theory computations of vibrational, electronic, and topological properties of porous nanographenes. J. Phys. Org. Chem. 2022, 36, e4435. [Google Scholar] [CrossRef]
  17. Vivas-Reyes, R.; Martínez-Santiago, O.; Marrero-Ponce, Y. Graph derivative indices interpretation from the quantum mechanics perspective. J. Math. Chem. 2023, 61, 1739–1757. [Google Scholar] [CrossRef]
  18. Hosoya, H. Aromaticity index can predict and explain the stability of polycyclic conjugated hydrocarbons. Monatshefte Fuer Chem./Chem. Mon. 2005, 136, 1037–1054. [Google Scholar] [CrossRef]
  19. Hosoya, H. Clar’s aromatic sextet and sextet polynomial. In Advances in the Theory of Benzenoid Hydrocarbons; Springer: Berlin/Heidelberg, Germany, 2005; pp. 255–272. [Google Scholar]
  20. Hosoya, H. Cross-conjugation at the heart of understanding the electronic theory of organic chemistry. Curr. Org. Chem. 2015, 19, 293–310. [Google Scholar] [CrossRef]
  21. Hosoya, H. Matching and Symmetry of Graphs. Comp. Maths. Appl. 1986, 12, 271–290. [Google Scholar] [CrossRef]
  22. Hosoya, H.; Hosoi, K.; Gutman, I. A Topological Index for the total π-electron Energy. Theor. Chim. Acta 1975, 38, 37–47. [Google Scholar] [CrossRef]
  23. Aihara, J.-I.; Yamabe, T.; Hosoya, H. Aromatic character of graphite and carbon nanotubes. Synth. Met. 1994, 64, 309–313. [Google Scholar] [CrossRef]
  24. Hosoya, H. Genealogy of Conjugated Acyclic Polyenes. Molecules 2017, 22, 896. [Google Scholar] [CrossRef]
  25. Aihara, J.-I. Graph Theory of Ring-Current Diamagnetism. Bull. Chem. Soc. Jpn. 2017, 91, 274–303. [Google Scholar] [CrossRef]
  26. Aihara, J.-I. Graph Theory of Aromatic Stabilization. Bull. Chem. Soc. Jpn. 2016, 89, 1425–1454. [Google Scholar] [CrossRef]
  27. Balaban, A.T.; Oniciu, D.C.; Katritzky, A.R. Aromaticity as a cornerstone of heterocyclic chemistry. Chem. Rev. 2004, 104, 2777–2812. [Google Scholar] [CrossRef] [PubMed]
  28. Randić, M.; Balaban, A.T. Local aromaticity and aromatic sextet theory beyond Clar. Int. J. Quantum Chem. 2018, 118, e25657. [Google Scholar] [CrossRef]
  29. Aihara, J.-I.; Horikawa, T. Graph-Theoretical Formula for Ring Currents Induced in a Polycyclic Conjugated System. Bull. Chem. Soc. Jpn. 1983, 56, 1853–1854. [Google Scholar] [CrossRef]
  30. Aihara, J. Magnetotropism of biphenylene and related hydrocarbons. A circuit current analysis. J. Am. Chem. Soc. 1985, 107, 298–302. [Google Scholar] [CrossRef]
  31. Aihara, J.-I. Circuit Resonance Energy: A Key Quantity That Links Energetic and Magnetic Criteria of Aromaticity. J. Am. Chem. Soc. 2006, 128, 2873–2879. [Google Scholar] [CrossRef]
  32. Aihara, J.-I.; Kanno, H.; Ishida, T. Magnetic resonance energies of heterocyclic conjugated molecules. J. Phys. Chem. A 2007, 111, 8873–8876. [Google Scholar] [CrossRef] [PubMed]
  33. Aihara, J. Topological resonance energy, bond resonance energy, and circuit resonance energy. J. Phys. Org. Chem. 2007, 21, 79–85. [Google Scholar] [CrossRef]
  34. Dias, J.R. Valence-Bond Determination of Diradical Character of Polycyclic Aromatic Hydrocarbons: From Acenes to Rectangular Benzenoids. J. Phys. Chem. A 2013, 117, 4716–4725. [Google Scholar] [CrossRef] [PubMed]
  35. Aihara, J.-I.; Makino, M.; Ishida, T.; Dias, J.R. Analytical study of superaromaticity in cycloarenes and related coronoid hydrocarbons. J. Phys. Chem. A 2013, 117, 4688–4697. [Google Scholar] [CrossRef]
  36. Dias, J.R. Search for singlet-triplet bistability or biradicaloid properties in polycyclic conjugated hydrocarbons: A valence-bond analysis. Mol. Phys. 2012, 111, 735–751. [Google Scholar] [CrossRef]
  37. Dias, J.R. What Do We Know about C24H14 Benzenoid, Fluoranthenoid, and Indacenoid Compounds? Polycycl. Aromat. Comp. 2014, 34, 177–190. [Google Scholar] [CrossRef]
  38. Dias, J.R. Nonplanarity Index for Fused Benzenoid Hydrocarbons. Polycycl. Aromat. Compd. 2014, 34, 161–176. [Google Scholar] [CrossRef]
  39. Dias, J.R. Perimeter topology of benzenoid polycyclic hydrocarbons. J. Chem. Inf. Model. 2005, 45, 562–571. [Google Scholar] [CrossRef] [PubMed]
  40. Aihara, J.-I. On the Number of Aromatic Sextets in a Benzenoid Hydrocarbon. Bull. Chem. Soc. Jpn. 1976, 49, 1429–1430. [Google Scholar] [CrossRef]
  41. Balaban, A.T. To be or not to be Aromatic. Rec. Roum. Chimie 2015, 60, 121–140. [Google Scholar]
  42. Randić, M. On the role of Kekulé valence structures. Pure Appl. Chem. 1983, 55, 347–354. [Google Scholar] [CrossRef]
  43. Randić, M. Aromaticity and Conjugation. J. Am. Chem. Soc. 1977, 99, 444–450. [Google Scholar] [CrossRef]
  44. Randić, M. Aromaticity of Polycyclic Conjugated Hydrocarbons. Chem. Rev. 2003, 103, 3449–3606. [Google Scholar] [CrossRef] [PubMed]
  45. Vogler, H. Structures and 1H-chemical shifts of conjugation deficient hydrocarbons. Int. J. Quantum Chem. 1986, 30, 97. [Google Scholar] [CrossRef]
  46. Aihara, J. Is superaromaticity a fact or an artifact? The Kekulene Problem. J. Am. Chem. Soc. 1992, 114, 865–868. [Google Scholar] [CrossRef]
  47. Clar, E. The Aromatic Sextet; Wiley: London, UK, 1972. [Google Scholar]
  48. Aihara, J.-I. Aromaticity and superaromaticity in cyclopolyacenes. J. Chem. Soc. Perkin Trans. 1994, 2, 971–974. [Google Scholar] [CrossRef]
  49. Aihara, J. Lack of Superaromaticity in Cabon Nanotubes. J. Phys. Chem. 1994, 98, 9773. [Google Scholar] [CrossRef]
  50. Aihara, J.-I. Hückel-like rule of superaromaticity for charged paracyclophanes. Chem. Phys. Lett. 2003, 381, 147–153. [Google Scholar] [CrossRef]
  51. Aihara, J.-I. A Simple Method for Estimating the Superaromatic Stabilization Energy of a Super-Ring Molecule. J. Phys. Chem. A 2008, 112, 4382–4385. [Google Scholar] [CrossRef]
  52. Aihara, J. Macrocyclic Conjugation Pathways in Porphyrins. J. Phys. Chem. A 2008, 112, 5305. [Google Scholar] [CrossRef]
  53. Dias, J.R.; Aihara, J.-I. Antiaromatic holes in graphene and related graphite defects. Mol. Phys. 2009, 107, 71–80. [Google Scholar] [CrossRef]
  54. Makino, M.; Aihara, J. Macrocyclic aromaticity of porphyrin units in fully conjugated oligoporphyrins. J. Phys. Chem. A 2012, 116, 8074. [Google Scholar] [CrossRef]
  55. Aihara, J.-I.; Nakagami, Y.; Sekine, R.; Makino, M. Validity and Limitations of the Bridged Annulene Model for Porphyrins. J. Phys. Chem. A 2012, 116, 11718–11730. [Google Scholar] [CrossRef]
  56. Dias, J.R. Structure and Electronic Characteristics of Coronoid Polycyclic Aromatic Hydrocarbons as Potential Models of Graphite Layers with Hole Defects. J. Phys. Chem. A 2008, 112, 12281–12292. [Google Scholar] [CrossRef]
  57. Dias, J.R. A formula periodic table for benzenoid hydrocarbons and the aufbau and excised internal structure concepts in benzenoid enumerations. Z. für Natur. A 1989, 44, 765–772. [Google Scholar] [CrossRef]
  58. Dias, J.R. Concealed Coronoid Hydrocarbons with Enhanced Antiaromatic Circuit Contributions as Models for Schottky Defects in Graphenes. Open Ophthalmol. J. 2011, 5, 112–116. [Google Scholar] [CrossRef]
  59. Cyvin, S.J.; Brunvoll, J.; Cyvin, B.N. Theory of Coronoid Hydrocarbons. In Lecture Notes in Chemistry; Springer: Berlin, Germany, 1991. [Google Scholar]
  60. Cyvin, S.J.; Brunvoll, J.; Chen, R.S.; Cyvin, B.N.; Zhang, F.J. Theory of Coronoid Hydrocarbons II. In Lecture Notes in Chemistry; Springer: Berlin, Germany, 1994; Volume 62. [Google Scholar]
  61. Gutman, I.; Milun, M.; Trinajstić, N. Graph theory and molecular orbitals. 19. Nonparametric resonance energies of arbitrary conjugated systems. J. Am. Chem. Soc. 1977, 99, 1692. [Google Scholar] [CrossRef]
  62. Aihara, J.-I.; Kanno, H. Local Aromaticities in Large Polyacene Molecules. J. Phys. Chem. A 2005, 109, 3717–3721. [Google Scholar] [CrossRef]
  63. Sekine, R.; Nakagami, Y.; Aihara, J. Aromatic Character of Polycyclic π Systems Formed by Fusion of Two or More Rings of the Same Size. J. Phys. Chem. A 2011, 115, 6724. [Google Scholar] [CrossRef] [PubMed]
  64. Saito, S.; Osuka, A. Expanded Porphyrins: Intriguing Structures, Electronic Properties, and Reactivities. Angew. Chem. Int. Ed. 2011, 50, 4342–4373. [Google Scholar] [CrossRef]
  65. Randić, M.; Balaban, A.T.; Plavšić, D. Applying the conjugated circuits method to Clar structures of [n]phenylenes for determining resonance energies. Phys. Chem. Chem. Phys. 2011, 13, 20644–20648. [Google Scholar] [CrossRef] [PubMed]
  66. Balasubramanian, K.; Kaufman, J.J.; Koski, W.S.; Balaban, A.T. Graph theoretical characterization and computer generation of certain carcinogenic benzenoid hydrocarbons and identification of bay regions. J. Comput. Chem. 1980, 1, 149–157. [Google Scholar] [CrossRef]
  67. Balasubramanian, K. Graph-Theoretical Characterization of Fullerene Cages. Polycycl. Aromat. Compd. 1993, 3, 247–259. [Google Scholar] [CrossRef]
  68. Arockiaraj, M.; Clement, J.; Balasubramanian, K. Topological Indices and Their Applications to Circumcised Donut Benzenoid Systems, Kekulenes and Drugs. Polycycl. Aromat. Compd. 2018, 40, 280–303. [Google Scholar] [CrossRef]
  69. Arockiaraj, M.; Paul, D.; Clement, J.; Tigga, S.; Jacob, K.; Balasubramanian, K. Novel molecular hybrid geometric-harmonic-Zagreb degree based descriptors and their efficacy in QSPR studies of polycyclic aromatic hydrocarbons. SAR QSAR Environ. Res. 2023, 34, 569–589. [Google Scholar] [CrossRef] [PubMed]
  70. Balasubramanian, K. Applications of Combinatorics and Graph Theory to Quantum Chemistry & Spectroscopy. Chem. Rev. 1985, 85, 599–618. [Google Scholar]
  71. Ramaraj, R.; Balasubramanian, K. Computer Generation of Matching Polynomials of Graphs and Lattices. J. Comput. Chem. 1985, 6, 122–141. [Google Scholar] [CrossRef]
  72. Balasubramanian, K.; Randić, M. Characteristic Polynomials of Structures with Pending Bonds. Theor. Chim. Acta 1982, 61, 307–323. [Google Scholar] [CrossRef]
  73. Balasubramanian, K. Characteristic polynomials of organic polymers and periodic structures. J. Comput. Chem. 1985, 6, 656–661. [Google Scholar] [CrossRef]
  74. Balasubramanian, K. Spectra of matching polynomials. Chem. Phys. Lett. 1993, 208, 219–224. [Google Scholar] [CrossRef]
  75. Manoharan, M.; Balakrishnarajan, M.; Venuvanalingam, P.; Balasubramanian, K. Topological resonance energy predictions of the stability of fullerene Clusters. Chem. Phys. Lett. 1994, 222, 95–100. [Google Scholar] [CrossRef]
  76. Balasubramanian, K. Matching Polynomials of Fullerene Clusters. Chem. Phys. Lett. 1993, 201, 306–314. [Google Scholar] [CrossRef]
  77. Balasubramanian, K. Symmetry and Combinatorial Concepts for Cyclopolyarenes, Nanotubes and 2D-Sheets: Enumerations, Isomers, Structures Spectra & Properties. Symmetry 2021, 14, 34. [Google Scholar] [CrossRef]
  78. Hosoya, H.; Balasubramanian, K. Computational Algorithms for Matching Polynomials of Graphs from the Characteristic Polynomials of Edge-Weighted Graphs. J. Comput. Chem. 1989, 10, 698–710. [Google Scholar] [CrossRef]
  79. Hosoya, H.; Balasubramanian, K. Exact Dimer Statistics and Characteristic-Polynomials of Cacti Lattices. Theor. Chim. Acta 1989, 76, 315–329. [Google Scholar] [CrossRef]
  80. Balasubramanian, K. Symmetry, Combinatorics, Artificial Intelligence, Music and Spectroscopy. Symmetry 2021, 13, 1850. [Google Scholar] [CrossRef]
  81. Herndon, W.C. Resonance energies of aromatic hydrocarbons. Quantitative test of resonance theory. J. Am. Chem. Soc. 1973, 95, 2404–2406. [Google Scholar] [CrossRef]
  82. Moreno-Vicente, A.; Abella, L.; Azmani, K.; Rodriguez-Fortea, A.; Poblet, J.M. Formation of C2v-C72 (11188)Cl4: A Particularly Stable Non-IPR Fullerene. J. Phys. Chem. A 2018, 122, 2288–2296. [Google Scholar] [CrossRef] [PubMed]
  83. Chen, Z.; Cioslowski, J.; Rao, N.; Moncrieff, D.; Bühl, M.; Hirsch, A.; Thiel, W. Endohedral chemical shifts in higher fullerenes with 72-86 carbon atoms. Theor. Chem. Accounts 2001, 106, 364–368. [Google Scholar] [CrossRef]
  84. Ishfaq, F.; Nadeem, M.F.; El-Bahy, Z.M. On topological indices and entropies of diamond structure. Int. J. Quantum Chem. 2023, 123, e27207. [Google Scholar] [CrossRef]
  85. Al-Dayel, I.; Nadeem, M.F.; Khan, M.A. Topological analysis of tetracyanobenzene metal–organic framework. Sci. Rep. 2024, 14, 1789. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Structures of polycyclic compounds considered in this study. Not all displayed structures are meant to show any particular resonance/Clar’s structure; the structures simply show the relationships and connectivities of various hexagonal rings.
Figure 1. Structures of polycyclic compounds considered in this study. Not all displayed structures are meant to show any particular resonance/Clar’s structure; the structures simply show the relationships and connectivities of various hexagonal rings.
Symmetry 16 00391 g001aSymmetry 16 00391 g001bSymmetry 16 00391 g001cSymmetry 16 00391 g001dSymmetry 16 00391 g001e
Table 1. Characteristic, matching and delta polynomials of phenanthrene and the derived Z, zeta and delta indices.
Table 1. Characteristic, matching and delta polynomials of phenanthrene and the derived Z, zeta and delta indices.
Phenanthrene
n − kCharacteristic
Polynomial
Matching
Polynomial
Delta
Polynomial
141.01.00.0
130.00.00.0
12−16.0−16.00.0
110.00.00.0
1098.098.00.0
90.00.00.0
8−297.0−291.06.0
70.00.00.0
6479.0435.044.0
50.00.00.0
4−407.0−305.0102.0
30.00.00.0
2166.082.084.0
10.00.00.0
0−25.0−5.020.0
ZC: 1489Z: 1233 δ k = 256 k δ k = 2696
ζC: 0.5218471ζM: 0.5083718Δ: 0.3960841ΔW: 0.5642518
Anthracene
n − kCharacteristic
Polynomial
Matching
Polynomial
Delta
Polynomial
14110
13000
12−16−160
11000
1098980
9000
8−296−2906
7000
647342944
5000
4−392−29498
3000
21487672
1000
0−16−412
ZC: 1440Z: 1208 δ k = 232 k δ k = 2400
ζC: 0.5194570ζM: 0.5069087Δ: 0.3890527ΔW: 0.5559446
Table 2. Characteristic, matching and delta polynomials of coronene.
Table 2. Characteristic, matching and delta polynomials of coronene.
n − kChar.
Poly.
Match.
Poly.
Delta
Poly.
24110
23000
22−30−300
21000
203873870
19000
18−2832−281814
17000
161305912783276
15000
14−39858−376202238
13000
1282281725859696
11000
10−115272−9079224480
9000
81081927125636936
7000
6−65864−3296832896
5000
424432801616416
3000
2−4896−8164080
1000
040020380
| x k |  a457504330092127412
1 n ln ( | x k | ) 0.54306420.52946360.4897992
a xk designates the coefficient in the respective polynomial (characteristic or matching or delta polynomial) of the corresponding column.
Table 3. Characteristic, matching and delta polynomials of circumcoronene.
Table 3. Characteristic, matching and delta polynomials of circumcoronene.
n − kChar. Poly.Match. Poly.Delta Poly.
54110
53000
52−72−720
51000
50243024300
49000
48−51152−5111438
47000
467538677515512316
45000
44−8277552−821187665676
43000
4270356380692045801151800
41000
40−474823692−46081711214006580
39000
3825896153332464100913125514420
37000
36−11556300564−10696440044859860520
35000
3442569538372379581657004611372672
33000
32−130222965528−11055708953419665875994
31000
3033206914645326468731148567381834968
29000
28−707192500956−520523395944186669105012
27000
261257989920284838506886932419483033352
25000
24−1866287443412−1101123547848765163895564
23000
22230154559633511705422442311131003352104
21000
20−2347222219224−9978486451081349373574116
19000
1819651053361026738091993421291296136760
17000
16−1337106330756−354768478638982337852118
15000
14729597602706142707108690586890494016
13000
12−313604239964−42704574172270899665792
11000
10103654073940917305234894481021592
9000
8−25479629340−134558605824134043282
7000
644388324811252247334313607748
5000
4−508728588−6568740502159848
3000
23369651615614433540372
1000
0−960400−980959420
| x k | 1347932894240062800868163207199242126080
1 n ln ( | x k | ) 0.55985520.54571120.5482407
Table 4. Characteristic, matching and delta polynomials of kekulene.
Table 4. Characteristic, matching and delta polynomials of kekulene.
n − kChar. Poly.Match. Poly.Delta Poly.
48110
47000
46−60−600
45000
44167416740
43000
42−28874−28850−24
41000
403453273441271200
39000
38−3044574−301699827576
37000
362053868920152013386676
35000
34−108618240−1049134923704748
33000
3245770724943196943325737816
31000
30−1553676412−1419382254134294158
29000
2842779760003740060904537915096
27000
26−9591327648−79147187881676608860
25000
2417529851809134316392054098212604
23000
22−26083608096−182009820247882626072
21000
20314797179691955277264911926945320
19000
18−30623699358−1647966065414144038704
17000
16237974313751074331629913054115076
15000
14−14592392910−53152197249277173186
13000
12694715008219456802625001469820
11000
10−2513544072−5091727022004371370
9000
867154984190806961580742880
7000
6−127206956−10292946116914010
5000
41603598466513615370848
3000
2−1198800−203281178472
1000
04000020039800
| x k | 1703966920009991481768470481874316
1 n ln ( | x k | ) 0.53877910.52765800.5203879
Table 5. Characteristic, matching and delta polynomials of three polycyclic isomers of C22H12.
Table 5. Characteristic, matching and delta polynomials of three polycyclic isomers of C22H12.
Characteristic PolynomialsMatching PolynomialsDelta Polynomials
n − kTrianguleneAnthanthreneBezo[ghi] PeryleneTrianguleneAnthanthreneBezo[ghi] PeryleneTrianguleneAnthanthreneBezo[ghi] Perylene
22111111000
21000000000
20−27−27−27−27−2727000
19000000000
18309309309309309309000
17000000000
16−1973−1973−1974−1961−196119621212−12
15000000000
14778277837800757875797596204204204
13000000000
12−19818−19831−19953−18426−184411855713921390−1396
11000000000
10330273311033580281272821828624490048924956
9000000000
8−35619−35902−36968−26079−263542712695409548−9842
7000000000
6238532440025864136591408614866101941031410998
5000000000
4−8987−9609−10796−3491−3817420254965792−6594
3000000000
2145218402360306414490114614261870
1000000000
00−100−1960−1014090−182
| x k | 13284813488513982899964101217103774328843366836054
1 n ln ( | x k | ) 0.53622550.53691720.53855310.52329840.52386460.52499870.47276100.47383200.4769442
Table 6. Characteristic, matching and delta polynomials of three circumscribed isomers: C52H17, circumtriangulene, circumanthanthrene and Circumbezo[ghi] perylene.
Table 6. Characteristic, matching and delta polynomials of three circumscribed isomers: C52H17, circumtriangulene, circumanthanthrene and Circumbezo[ghi] perylene.
Circumtriangulene Circumanthanthrene Circumbezo[ghi] Perylene
n − kCharacteristic
Polynomial
Matching
Polynomial
Delta
Polynomial
n − kCharacteristic
Polynomial
Matching
Polynomial
Delta
Polynomial
n − kCharacteristic
Polynomial
Matching
Polynomial
Delta
Polynomial
521105211052110
510005100051000
50−69−69050−69−69050−69−690
490004900049000
482226222604822262226048222622260
470004700047000
46−44668−446323646−44668−446323646−44669−4463336
450004500045000
446257136236252088446257136236252088446257726236842088
430004300043000
42−6509829−64536635616642−6509829−64536635616642−6511448−645527656172
410004100041000
405225121651320120931096405225121751320121931096405227869051347258931432
390003900039000
38−331796412−3211345741066183838−331796457−3211346251066183238−332119812−32144931810670494
370003700037000
361695928914160634221889586696361695929871160634341789586454361698736514160901357689722938
350003500035000
34−7062439782−648963648057280330234−7062452491−648965368357279880834−7081100003−6506829077574270926
330003300033000
322416268900121310401549285228745232241628068222131056975828522370643224259975217213962001352863775082
310003100031000
30−68292453531−570628740511122957948030−68293262612−570640602121122920240030−68696889063−5739959770111297291362
290002900029000
281599622553771246699681353529228724228159966519220124676198180352903210402816131774016512571805033335599689832
270002700027000
26−310866022785−2218360723838902995040226−310883651811−2218609055038902274630826−314554717782−22443429900890120418774
250002500025000
245008424661183201626657701806798003482450090043487132023855120918066188366224509025810275325296517073183729293202
230002300023000
22−667151021522−37233624208429481477943822−667303817619−37251471669929478910092022−681972062692−380402520082301569542610
210002100021000
207312417442673457208331333855209111342073156573244134604356160138552217084020753133601175355744657295397388943880
190001900019000
18−654769892103−25315306235740161682974618−655322555267−25359932212340172323314418−681052897827−262920853285418132044542
170001700017000
164741411186031438358454373303052731661647489713963414430316412233059397551216499638000612151208688842348429311770
150001500015000
14−273813286767−6207715679721173612997014−274637349199−6244249642121219485277814−293623626123−66316204751227307421372
130001300013000
121236962118721978199923210391421264012124404621068199910500461044135710221213587279153321597079779114275711754
110001100011000
10−42539488824−44774600403806202878410−43012391338−45626863583844970498010−48360491101−503887403143321617070
900090009000
810698149700680855244100172944568109375603497046967451023286360481281157167280112519812010446474
700070007000
6−1845219852−6383708417813827686−1933743487−6816682318655766646−2408005299−806283392327376960
500050005000
419406822431775101908907144216497569364456521285300442979603174566433293393884
300030003000
2−9335088−5988692752022−12786256−85352127009042−21276306−11732621158980
100010001000
000002401004902396100648025805647220
| x k | 405337502246419556480683002097726954164 | x k | 405760072220519578594522692099741269936 | x k | 419621948438820068557455342189363738854
1 n ln ( | x k | ) 0.55828020.54426430.5456130 1 n ln ( | x k | ) 0.55830020.54428600.5456314 1 n ln ( | x k | ) 0.55894630.54476140.5464352
Table 7. Characteristic, matching and delta polynomials of C60 buckminsterfullerene.
Table 7. Characteristic, matching and delta polynomials of C60 buckminsterfullerene.
n − kCharacteristic
Polynomial
Matching
Polynomial
Delta
Polynomial
60110
59−000
58−90−900
57−000
56382538250
55−24024
54−102160−10212040
53192001920
52192516019220403120
51−72240072240
50−27244512−27130596113916
49170064001700640
483009063802983178602588520
47−28113600028113600
46−2661033600−261998046041053140
453472088960347208896
441918083402018697786680483047340
43−332762568003327625680
42−114118295000−1097428312604375463740
4125376437920025376437920
4056540746514453416254438031244920764
39−1566525754400156652575440
38−2346799508400−2168137517940178661990460
377921754275200792175427520
3681891169553507362904561730826212393620
35−330817311590403308173115904
34−24056403184260−209492862021603107116982100
3311466942645600011466942645600
3259443188508110499248898888509518298619260
31−33076275953760033076275953760
30−123163094844616−9946345724484423699637599772
2979417625268960079417625268960
2821271222182084016507485163230047637370188540
27−1584127192762400158412719276240
26−303315997028160−22704312627426076272870753900
252613590906706240261359090670624
2435186138931678025696761445432094893774862460
23−3541451951472000354145195147200
22−324375523213200−23713586768898087239655524220
213900550747622400390055074762240
2022822703104088417634554011929651881490921588
19−3441859065967200344185906596720
18−112654402736360−1041135679371408540834799220
172385530910552000238553091055200
16296170036669204788382697658018266823309660
15−1264288825362400126428882536240
144679380503120−1674248629134012063105788220
1349433493646080049433493646080
12−813142939713543107182276853820711169450
11−13627897407360013627897407360
103576552321006−7830473124062793505008600
9252736561712002527365617120
8−83161653109594541532165737074998930
7−3100650670800310065067080
6108565938200−6946574300101619363900
526034025632026034025632
4−74407125602692726207171439940
3−156650112001566501120
2186416640−4202760182213880
154743040054743040
02985984125002973484
| x k | 386531240763951214170366345434882508935631291784
1 n ln ( | x k | ) 0.5981803 0.5814557 0.5909773
Table 8. Characteristic, matching and delta polynomials of the zigzag macrocycle-21 together with their indices.
Table 8. Characteristic, matching and delta polynomials of the zigzag macrocycle-21 together with their indices.
n − kCkMkδk
84110
82−105−1050
80529252920
78−170552−17051042
76395062939466393990
74−70093203−69911859181344
729912827499860311435251606
70−11482348005−11373459253108888752
681110900871761093679378241722149352
66−910947963808−88933453179621613432012
6464029254392876181826617949221098821338
62−38919293230683−370400112620251879281968658
6020601390439711519255148833699513462416060120
58−955002794104467−87283912945266982163664651798
5638943362173411213463521386236771430814831104350
54−14019373614031827−120660342714678271953339342564000
5244678801369930336369815488101478487697252559782488
50−126321154074068661−9985711419381111526464039880257546
4831733868579532412323772004256025436379618643235069760
46−709062372660591571−499006339626984227210056033033607344
441409909022006755539923239449763670729486669572243084810
42−2495016469484972200−1504059185145959400990957284339012800
40392796330386606947321542249428790369511773738360987032522
38−5496873577643855036−27069364818727459142789937095771109122
36682911101661576402929761169603729988973852994056242765132
34−7518883235006766618−28533110586531277104665572176353638908
32731990238417814197223757868685959468404944115515582195132
30−6283532923932044803−17096559144726948954573877009459349908
28473988586781379118710571533351340414673682732532679749720
26−3129063398676383265−5578490019751671712571214396701216094
2417989113216783870992491822672861445411549729054392242558
22−895371948756710388−93314898694188010802057050062522378
2038312204984544351928961471055606009354160578789837510
18−139739031770502510−7347157054733772132391874715768738
1642996786829876846149815525291115641498631576965690
14−11017873944937905−24053205995113110777341884986774
122313181667668728296331108683322283548556800396
10−389499119207522−2710827868354386788291339168
85109541574487617638021070850919035534168
6−5008008625962−76974424725000311183490
4343396584009206946163343189637846
2−14620716108−298291614617733192
028934010017014289323086
| x k | 53640581451802650405 2008911443293582676333551467018866823642
1 n ln ( | x k | ) 0.54081950.52912750.5352335
Table 9. Computed zeta and delta aromatic indices of polycyclic compounds.
Table 9. Computed zeta and delta aromatic indices of polycyclic compounds.
SystemζC × 10−1ζM × 10−1Δ × 10−1ΔW × 10−1
Coronene5.4306425.2946364.8979926.064420
Circumcoronene5.5985525.4571125.4824076.137828
Hexbencoronene5.5201975.3758055.3325576.120283
Ovalene5.4898045.3533475.1651186.119007
Circumovalene5.6306565.4874185.5561266.121432
Circumpyrene5.5476695.4089865.3529996.139214
Circumcircumpyrene5.6613995.5161155.6145136.104184
Coronaphene5.3945105.2817985.0895065.963508
Circumcoronaphene5.5135835.4522795.3717235.903852
C60 (Ih)5.9818035.8145575.9097736.516865
C70 (D5h)5.9850285.8149035.9345086.476662
C72 (C2v)5.9862155.8149665.9396046.470739
Kekulene 5.387791 5.276580 5.203879 5.914023
Septulene5.3877845.2765805.2504835.884901
Dicronylene5.5100415.3747435.3561106.069668
Triangulene (C22H12)5.3622555.2329844.7276105.958243
Anthanthrene (C22H12)5.3691725.2386464.7383205.971711
Bezo[ghi]perylene (C22H12)5.3855315.2499874.7694426.007196
Circumtriangulene (C52H18)5.5828025.4426435.4561306.129567
Circumanthanthrene (C52H18)5.5830025.4428605.4563146.129790
Circumbezo[ghi]perylene (C52H18)5.5894635.4476145.4643526.138383
Macro-zig-215.4081955.2912755.3523355.822065
Graphene [6.771][6.77]
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Balasubramanian, K. New Insights into Aromaticity through Novel Delta Polynomials and Delta Aromatic Indices. Symmetry 2024, 16, 391. https://doi.org/10.3390/sym16040391

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Balasubramanian K. New Insights into Aromaticity through Novel Delta Polynomials and Delta Aromatic Indices. Symmetry. 2024; 16(4):391. https://doi.org/10.3390/sym16040391

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Balasubramanian, Krishnan. 2024. "New Insights into Aromaticity through Novel Delta Polynomials and Delta Aromatic Indices" Symmetry 16, no. 4: 391. https://doi.org/10.3390/sym16040391

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