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ORIGINAL RESEARCH article

Front. Chem., 02 January 2026

Sec. Theoretical and Computational Chemistry

Volume 13 - 2025 | https://doi.org/10.3389/fchem.2025.1704165

Entropy comparison of benzothiadiazole-based covalent-organic frameworks

  • Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore, India

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Abstract

Covalent Organic Frameworks (COFs) are popular photocatalysts that utilize solar energy to generate hydrogen peroxide and evolve hydrogen because of their intrinsic porosity, robust framework, and excellent structural regularity. Benzothiadiazole-based donor-acceptor type COFs, PC-NB and PC-NPB, having distinct -bridges, influence electron transport and photocatalytic efficiency. Using degree-based topological indices and their entropy analysis, this study attempts to theoretically investigate the covalent organic frameworks PC-NB and PC-NPB to evaluate the structural complexity and stability. By offering an organized method for analyzing molecular graph features, edge partition facilitates the computation of topological indices. The calculated topological indices of the COFs are compared in detail and presented graphically. PC-NPB consistently shows higher values across nearly all degree-based topological indices, suggesting that it has a more connected structure. Additionally, lower entropy values in PC-NB indicate a higher degree of topological regularity and symmetry, which are traits frequently associated with enhanced rigidity, crystallinity, and thermodynamic stability.

1 Introduction

Covalent organic frameworks (COFs) are novel porous materials created by covalent bonding of light elements such as carbon, hydrogen, nitrogen, sulfur, and oxygen (Xia et al., 2023). They hold great potential for gas adsorption, molecule separation, drug delivery, catalysis, energy storage, and conversion, because of their high crystallinity, wide surface area, superior stability, and ease of functionalization. For photocatalytic hydrogen peroxide production and water splitting, hundreds of COFs have been designed and synthesized (Huang et al., 2025). Donor-Acceptor (D-A) type COFs are a relatively special class of members within the broad family of COF-based photocatalysts because of the electron donor-acceptor units in their skeleton (Wang et al., 2023). D and A units are arranged alternately in D-A type polymers (Wang et al., 2024). Building a D-A COF can be done in two main ways: either by designing a covalent link with a polar orientation or by including donor and acceptor units into the polymeric backbone. According to recent studies, the photocatalytic efficacy of D-A COFs produced is significantly impacted by both linker composition and linkage orientation. D-C N-A and D-N C-A are two types of imine linkage orientations found in D-A-type COFs. The D-C N-A COFs exhibit better photocatalytic activity compared to the D-NC-A COFs. Using chromophores such as benzothiadiazole and pyrene as building blocks for COFs enhances the band-gap structure and light absorption (Li et al., 2021; Nagar et al., 2025).

For the study, we consider two benzothiadiazole-based covalent organic frameworks. PC-NB and PC-NPB are two benzothiadiazole-based covalent organic frameworks synthesized via a Schiff base condensation reaction, with benzothiadiazole serving as the acceptor and pyrene as the donor. Since the imine linkage (C N) is polar, connecting the carbon atom of the imine linkage to the donor pyrene unit allows better electron delocalization. Thus, this orientation of the imine bond helps in the good photocatalytic performance of PC-NB and PC-NPB. If the connection is flipped, then performance will drop. The benzene ring in the -bridge between pyrene and benzothiadiazole is what distinguishes PC-NB from PC-NPB. In PC-NB, benzothiadiazole was directly linked to imine linkages, in contrast to PC-NPB, which has additional benzene on the -bridge. This enhances electron mobility in PC-NPB, which supports the hydrogen () production process but hinders the production of hydrogen peroxide. The hydrogen evolution rate was 4.4 times higher in PC-NPB with the diphenyl benzothiadiazole building block () than in PC-NB with non-phenyl-substituted benzothiadiazole. With a hydrogen peroxide generation rate of , PC-NB outperformed PC-NPB by a factor of 2.8 (Waller et al., 2015; Wang et al., 2020; Zhao et al., 2025).

Despite increasing interest in D-A type COFs, a comprehensive investigation comparing the topological indices and entropy of PC-NB and PC-NPB structures has yet to be conducted, which could elucidate structure-property correlations relevant to their photocatalytic performance. The topological index of a molecular structure is a numerical value that shows the branching pattern and molecular structure in a non-empirical manner. It is related to chemical composition, which demonstrates how chemical structures correlate with a variety of physical, chemical, and biological aspects (Manzoor et al., 2020). Due to the interpretability and simplicity of the calculation, degree-based indices were popular among various topological descriptors. Degree-based indices are useful for differentiating structurally similar molecules and provide insightful information about the underlying molecular complexity. Besides these descriptors, the concept of topological entropy has attracted a great deal of interest as a quantitative indicator of the structural uncertainty of molecular graphs. Entropy calculation of molecular graphs is one of the major approaches to measuring the complexity of rational structures. Such metrics have their roots in Rashevsky, who first proposed the idea of topological information content (Manzoor et al., 2020; Rashevsky, 1961). Combining entropy-based research with topological indices can yield more complex knowledge of molecular topology and how it affects compound behavior.

In this paper, the molecular structures of PC-NB and PC-NPB are translated into molecular graphs, where the atoms are treated as vertices and the bonds between them as edges. A number of degree-based topological indices are then calculated to quantitatively capture key molecular features, including branching patterns, connectivity, and overall structural complexity (Kuzmin and Konovorotskii, 1985). In addition, the corresponding topological entropy values are evaluated, which function as quantitative measures of the inherent uncertainty within the molecular structure. The internal structural organization of PC-NB and PC-NPB can be measured quantitatively and comparably using entropy and topological indices. Furthermore, this work shows how chemical graph theory can be utilized to predict and explain molecular properties performance, in addition to being a tool for defining molecular systems (Augustine and Roy, 2022).

2 Materials and methods

In this study, we have considered only simple, connected, and undirected graphs represented by , where is the vertex set and is the edge set of graph . The degree of vertex , denoted by , is the number of edges connected to . Degree-based topological indices are numerical invariants of molecular graphs that are calculated on the basis of the degree of vertex (Jyothish and Santiago, 2025). Some degree-based topological indices are given in Table 1.

TABLE 1

Index Formula
Randić
Reciprocal randić
Reduced reciprocal randić
First zagreb
Second zagreb
Reduced second zagreb
Hyper zagreb
Augmented zagreb
Harmonic
Sum connectivity
Geometric arithmetic
Inverse sum
Albertson
Symmetric division
Atom bond connectivity

Degree-based topological indices.

Three primary steps comprise our study: (i) building PC-NB and PC-NPB molecular graphs, (ii) using edge partition to calculate degree-based topological indices, and (iii) applying Shannon’s method to calculate entropy values from these indices. A molecular graph is a simple graph that graphically depicts a molecule. Figures 1, 2 depict schematic representations of molecular graphs of the donor-acceptor type covalent organic frameworks PC-NB and PC-NPB, respectively. These graphs provide the foundation for computing degree-based topological indices and entropy metrics. We have used analytical approaches, specifically employing the edge partition methodology for the calculation of topological indices. This partitioning enables a systematic analysis of the graph structure by focusing on different types of connections (Gutman, 2015; Trinajstic, 2018).

FIGURE 1

Molecular structure diagram featuring hexagonal carbon rings interconnected in a symmetrical pattern. Four central rings are highlighted in orange, creating a cross-like design with black lines and dots connecting various sections.

Molecular Structure of PC-NB unit cell.

FIGURE 2

Chemical structure diagram showing a diamond-shaped network of interconnected benzene rings. Blue hexagons highlight specific benzene rings within the network, emphasizing a repeating pattern. The structure is symmetrical around its center.

Molecular Structure of PC-NPB unit cell.

Topological indices characterize the topological structure of the molecules to a certain extent. The calculated topological indices of these chemical structures were then thoroughly compared. Entropy is a parameter that measures the structural complexity and stability within the systems. To calculate entropy, we use Shannon’s method by creating the probability function using degree-based topological indices. Entropy measured using the topological index is given by:where is the set of all edges in the graph and is the local value of the index at edge . Connectivity properties are quantified by degree-based topological indices, and entropy measures derived from these indices offer additional information on the regularity, disorder, or complexity of molecular graphs (Jyothish et al., 2025). Molecular structures were described using KingDraw, while calculations and plotting were done using MATLAB software.

3 Results

We consider two benzothiadiazole-based COFs, namely PC-NB, which is directly linked to the imine linkage, and PC-NPB, which has additional benzene in the -bridge between the imine linkage and the benzothiadiazole unit. The basic unit cells are merged into a rectangular mesh with rows and columns to form the 2D COF sheets. In this section, generalized formulations of several degree-based topological indices will be constructed using the edge partition approach. Edge partitions of a molecular graph are done on the basis of the degrees of the end vertices of each edge of (Gayathri and Roy, 2025; Govardhan et al., 2024). The PC-NB and PC-NPB sheets with rows and columns are denoted by and , respectively, where . consists of vertices and edges, and comprises vertices and edges. The edge partitions of the COFs are given in Table 2.

TABLE 2

Edge-partition
(1, 3)
(2, 2)
(2, 3)
(3, 3)

Edge-partitions of PC-NB and PC-NPB structures.

3.1 Degree-based topological indices of COFs: computation and comparison

This section presents and analyzes the computed degree-based topological indices for the molecular graphs of the covalent organic frameworks PC-NB and PC-NPB. We formulate expressions for each index corresponding to each structure using the edge partitions described in Table 2, which we articulate as Theorems.

Theorem 3.1

Let

be the molecular graph of the PC-NB structure with dimensions m and n, where

. Then,

Proof. Let

be the molecular graph of the covalent organic framework PC-NB with

and

. Then by using the edge partitions given in

Table 2

in the definitions of degree-based topological indices in

Table 1

, we get the following results.

Theorem 3.2

Let

be the molecular graph of the PC-NPB structure with dimensions m and n, where

. Then,

Proof. Let

be the molecular graph of the covalent organic framework PC-NPB with

and

. Then by using the edge partitions given in

Table 2

in the definitions of degree-based topological indices in

Table 1

, we get the following results.

3.2 Numerical and graphical analysis of topological indices of COFs

This section presents the numerical values of the degree-based topological indices for PC-NB and PC-NPB, with variables and varying from 1 to 10. Then the obtained data are analyzed comprehensively. The results are summarized in Tables 3, 4 and presented in Figures 3, 4 as three-dimensional bar plots for ease of comparison. The resultant numerical values provide an evaluation of how structural alterations between the two COF structures influence index magnitude and distribution, and these 3D diagrams show the difference between each topological index for a certain structure. The intensity of each value of the topological indices is represented using color mapping.

TABLE 3

(1, 1) (2, 2) (3, 3) (4, 4) (5, 5) (6,6) (7,7) (8,8) (9,9) (10,10)
108.2079 347.0689 716.5829 1,216.75 1,847.5702 2,609.0434 3,501.1697 4,523.949 5,677.3814 6,961.4669
639.3911 2,058.7005 4,257.9284 7,237.0745 10,996.1391 15,535.1219 20,854.0232 26,952.8428 33,831.5808 41,490.2371
369.0193 1,196.3128 2,481.8805 4,225.7224 6,427.8384 9,088.2286 12,206.8929 15,783.8315 19,819.0441 24,312.531
1,296 4,168 8,616 14,640 22,240 31,416 42,168 54,496 68,400 83,880
1,608 5,180 10,716 18,216 27,680 39,108 52,500 67,856 85,176 104,460
572 1,848 3,828 6,512 9,900 13,992 18,788 24,288 30,492 37,400
6592 21,200 43,824 74,464 113,120 159,792 214,480 277,184 347,904 426,640
2,260 7,305.6875 15,137.0625 25,754.125 39,156.875 55,345.3125 74,319.4375 96,079.25 120,624.75 147,955.9375
106.5333 342.4 707.6 1,202.1333 1,826 2,579.2 3,461.7333 4,473.6 5614.8 6,885.3333
117.3712 377.3235 779.8568 1,324.9712 2,012.6666 2,842.9431 3,815.8006 4,931.2391 6,189.2587 7,589.8593
256.3421 825.4515 1707.3283 2901.9724 4409.3838 6229.5626 8362.5088 10,808.2222 13,566.7031 16,637.9512
315.6 1,017.2 2,104.8 3,578.4 5,438 7,683.6 10,315.2 13,332.8 16,736.4 20,526
144 448 912 1,536 2,320 3,264 4,368 5,632 7,056 8,640
552 1762.6667 3632 61,660 9346.6667 13,192 17,696 22,858.6667 28,680 35,160
182.1347 584.6417 1,207.521 2,050.7726 3,114.3965 4,398.3927 5,902.7612 7,627.5019 9,572.615 11,738.1004

Numerical values of degree based topological indices of PC-NB.

TABLE 4

(1, 1) (2, 2) (3, 3) (4, 4) (5, 5) (6,6) (7,7) (8,8) (9,9) (10,10)
131.9385 441.9913 930.1584 1,596.4398 2,440.8355 3,463.3454 4,663.9697 6,042.7082 7,599.561 9,334.5281
773.7748 2,596.2352 5,467.3814 9,387.2133 14,355.7309 20,372.9341 27,438.8231 35,553.3978 44,716.6582 54,928.6043
446.2742 1,505.3322 3,177.174 5,461.7997 8,359.2092 11,869.4026 15,992.3798 20,728.1408 26,076.6857 32,038.0144
1568 5256 11,064 18,992 29,040 41,208 55,496 71,904 90,432 111,080
1936 6492 13,668 23,464 35,880 50,916 68,572 88,848 111,744 137,260
684 2,296 4,836 8,304 12,700 18,024 24,276 31,456 39,564 48,600
7,936 26,576 55,920 95,968 146,720 208,176 280,336 363,200 456,768 561,040
2,735.125 9,206.1875 19,413.1875 33,356.125 51,035 72,449.8125 97,600.5625 126,487.25 159,109.875 195,468.4375
130 436.2667 918.8 1,577.6 2,412.6667 3,424 4,611.6 5,975.4667 7,515.6 9,232
142.9481 479.6308 1,010.0482 1,734.2003 2,652.0871 3,763.7086 5,069.0648 6,568.1557 8,260.9812 10,147.5415
311.6955 1,046.8654 2,205.5095 3,787.6279 5,793.2205 8,222.2875 11,074.8287 14,350.8442 18,050.334 22,173.2981
382 1,282.8 2,702.4 4,640.8 7,098 10,074 13,568.8 17,582.4 22,114.8 27,166
176 576 1200 2048 3120 4416 5936 7680 9648 11,840
669.3333 2,232 4,688 8,037.3333 12,280 17,416 23,445.3333 30,368 38,184 46,893.3333
221.4092 741.7396 1,560.9912 2,679.164 4,096.258 5,812.2732 7,827.2097 10,141.0673 12,753.8462 15,665.5463

Numerical values of degree based topological indices of PC-NPB.

FIGURE 3

Three-dimensional bar chart displaying a color gradient from blue to red. The x-axis is labeled with pairs from (1,1) to (10,10), the y-axis with categories from H to HM, and the z-axis labeled as TI Value, ranging up to five hundred thousand. The bars increase in height from front left (blue, lowest) to back right (red, highest), indicating a trend of increasing TI values.

Graphical representation of numerical values of topological indices of PC-NB.

FIGURE 4

Three-dimensional bar chart showing TI values ranging from zero to six times ten to the fifth power. Bars are color-coded from blue to red, indicating a gradient increase from coordinates labeled (1,1) to (10,10) and variables H to HM. The most significant values are at HM.

Graphical representation of numerical values of topological indices of PC-NPB.

It is evident from examining the Tables 3, 4 that as and increase, so do the topological indices. Across almost all indices, PC-NPB consistently exhibits higher values than PC-NB for corresponding values. The Randić index for PC-NPB ranges from 131.9385 at (1, 1) to 9334.5281 at (10, 10), while PC-NB has a narrower range from 108.2079 to 6,961.4669. This trend is shared by all topological indices, including and . Among the fifteen degree-based topological indices of covalent organic frameworks (PC-NB and PC-NPB) studied, for every and spanning from 1 to 10, the index displays the greatest value, while the index displays the lowest. In 3D plots, Figures 3, 4, the horizontal axis corresponds to values and distinct topological indices, and the vertical axis depicts the associated numerical values. The change in color from blue to red signifies an increase in index values.

4 Discussion

4.1 Degree-based entropy of COFs

In this section, we describe the calculation of entropy measures. The entropies of the corresponding molecular graphs are determined using Equation 1. Here, we have demonstrated the computation of the entropy values of COFs PC-NB and PC-NPB using the First Zagreb Index.

Using the procedures described above, the remaining degree-based entropies corresponding to each topological index of PC-NB and PC-NPB are obtained.

4.2 Structural complexity and stability of PC-NB and PC-NPB COFs through entropy analysis

We conducted a graph-theoretical analysis employing Shannon entropy as a quantitative descriptor to assess the structural complexity and stability of the covalent organic frameworks PC-NB and PC-NPB. Figures 5, 6 show the entropies of PC-NB and PC-NPB graphically. In this context, entropy provides insight into the extent of topological order or disorder within the molecular architecture. Entropy values were assessed for various topological indices across ten different dimensional configurations, indicating successive iterations or depths of structural connectivity (Ezhilan and Varadhan, 2024).

FIGURE 5

Three-dimensional bar graph showing entropy values for various combinations, with bars colored from blue to yellow. The x-axis displays labels like EAlb, ERM2, and ERR, and the y-axis lists numeric pairs like (1,1) to (10,10). Bars increase in height and change color along the axes.

Graphical representation of numerical values of Entropies of PC-NB.

FIGURE 6

3D bar chart displaying entropy values across two axes. The X-axis represents categorical variables labeled such as "EAIb", "ERM2", and "EGA", while the Y-axis shows numerical pairs from "(1,1)" to "(10,10)". Bars transition from blue to yellow, indicating varying entropy levels.

Graphical representation of numerical values of Entropies of PC-NPB.

The entropy values for PC-NPB are consistently greater than those for PC-NB across all the entropy values based on different indices and stages of graph structure. In the entropy based on the randić index, PC-NPB shows entropy values between 5.7446 at the (1, 1) iteration and 10.0078 at (10, 10), whereas PC-NB presents a more limited range from 5.5489 to 9.7200. This trend is consistent across all the entropy values based on different indices, including the and . Lower entropy values in PC-NB indicate a higher degree of topological regularity and symmetry, which are characteristics commonly linked to improved thermodynamic stability, rigidity, and crystallinity. This indicates that PC-NB may create more uniform frameworks characterized by well-defined pore channels and predictable stacking interactions. The uniformity of atomic environments in the graph structure suggests enhanced -electron delocalization, which may lead to improved electronic stability (Mowshowitz and Dehmer, 2012).

The elevated entropy profile of PC-NPB suggests a more irregular and topologically diverse structure, likely due to asymmetric connectivity or a non-uniform distribution of subgraphs. Although these features may compromise overall framework stability, they can also improve functional versatility, such as increased porosity, surface heterogeneity. PC-NPB demonstrates potential for applications that necessitate dynamic host-guest interactions, including molecular sensing, catalysis, and selective adsorption. The entropy analysis indicates a distinct topological difference: PC-NB is characterized by a structurally ordered and potentially more stable framework, whereas PC-NPB displays increased configurational complexity, suggesting improved functional responsiveness. The findings demonstrate the significance of entropy-based metrics in offering an additional viewpoint on structure–property relationships in the rational design of COFs (Shannon, 1948; Vijay et al., 2023).

5 Conclusion

This study used topological indices to characterize the covalent organic frameworks, PC-NB and PC-NPB, based on their vertex degrees. Using Shannon’s approach, their entropy values were evaluated for a range of topological indices across ten distinct dimensional configurations. Our calculations reveal that PC-NB is more topologically regular and symmetric than PC-NPB. According to this, PC-NB might provide more homogeneous frameworks with distinct pore channels and consistent stacking interactions, which could result in better electronic stability by enhancing -electron delocalization. Additionally, the properties of PC-NPB, such as higher porosity and surface heterogeneity, may undermine the overall stability of the framework, but they also offer improved functional adaptability. In the rational design of COFs, the results show the importance of entropy-based metrics in providing an extra perspective on structure–property connections. Hence, the graph-theoretical analysis provides significant insights into the stabilities of the PC-NB and PC-NPB covalent organic frameworks.

Statements

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Author contributions

SK: Conceptualization, Formal Analysis, Software, Writing – original draft. SR: Supervision, Writing – review and editing, Validation. KG: Formal Analysis, Software, Visualization, Writing – review and editing. KJ: Formal Analysis, Methodology, Software, Writing – review and editing.

Funding

The authors declare that financial support was received for the research and/or publication of this article. The authors wish to express their gratitude to Vellore Institute of Technology, Vellore, for providing the financial support.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The authors declare that no Generative AI was used in the creation of this manuscript.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

Publisher’s note

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Summary

Keywords

covalent organic framework, molecular graph, benzothiadiazole, topological indices, entropy

Citation

Kurian S, Roy S, Gayathri KB and Jyothish K (2026) Entropy comparison of benzothiadiazole-based covalent-organic frameworks. Front. Chem. 13:1704165. doi: 10.3389/fchem.2025.1704165

Received

12 September 2025

Revised

13 November 2025

Accepted

19 November 2025

Published

02 January 2026

Volume

13 - 2025

Edited by

Leonardo Bernasconi, University of Pittsburgh, United States

Reviewed by

Aggelos Avramopoulos, University of Thessaly, Greece

Janani Ezhilan, Joy University, India

Updates

Copyright

*Correspondence: S. Roy,

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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