Topological Insights into Nanostar Dendrimers by Computing the Augmented Zagreb Index.

BACKGROUND: The field of nanobiotechnology uses precise nanofabrication techniques to advance our understanding and control of biological systems. Due to their remarkable properties, dendrimers, which are hyperbranched macromolecular structures with distinct and well-defined architectures, have emerged as pivotal entities within this field. They are gaining increasing attention for their potential to catalyze a paradigm shift in medical therapeutics, biotechnological applications, and advanced material sciences. OBJECTIVE: This paper focuses on a novel analytical expression and determines the precise value of the augmented Zagreb index, a topological descriptor, for eight classes of nanostar dendrimers. METHODS: The Zagreb index is a topological invariant to predict molecular behaviour and reactivity. In this paper, we have explored its application in characterizing the branching of nanostar dendrimers through computational modelling and mathematical rigor. RESULTS: Our research has measured the augmented Zagreb index for nanostar dendrimers, which fall into eight distinct classes. The results better explain the relationship between the dendrimers' topology and chemical properties. This correlation has implications for their structural stability and reactivity, potentially leading to new applications. CONCLUSION: Developing the augmented Zagreb index for nanostar dendrimers is a significant breakthrough in nanobiotechnology. Based on the correlation between the calculated topological index and the corresponding molecular attributes, our analytical approach has opened up new possibilities for designing and synthesizing dendrimers tailored to specific functions in medical and material science applications. This precise topological quantification could significantly enhance the utility and functionalization of dendrimers in cutting-edge nanotechnological applications.

Fundamental aspects of the molecular topology of fuchsine acid dye with connection numbers.

Fuchsine acid serves as a supramolecular dye in Masson's trichrome stain, finding extensive applications in histology. It is also utilized with picric acid in Van Gieson's method to reveal red collagen fibers and in Masson's trichrome to highlight smooth muscle in contrast to collagen. Beyond these applications, it plays a crucial role in electronic fields and photonic devices as an organic semiconductor. Therefore, investigating and predicting the complex molecular structure of fuchsine acid becomes essential, serving as the foundation for understanding its physicochemical features. This article employs topological modeling, specifically a connection number edge partition, to explore the supramolecular nature of fuchsine acid. Closed formulae for key degree-based molecular descriptors are derived, aiming to illuminate the effectiveness of these descriptors for QSAR and QSPR analyses.

Connection number topological aspect for backbone DNA networks.

The present study investigates the complex topological characteristics of DNA networks, with a specific emphasis on the innovative metric known as Connection Number (CN) as a key factor in determining network structure. The Connection Number, represented as CN(v) for a vertex v, measures the count of unique paths that link v to every other vertex in the network. By employing rigorous mathematical modeling and analysis techniques, we are able to reveal the profound implications of CN (complex networks) in characterizing the structural robustness and dynamics of information flow within DNA networks. The study of how the theory of graphs and chemicals interact is known as chemical graph theory. This paper, computing the hyper Zagreb connection index, augmented connection index, inverse sum connection index, harmonic connection index, symmetric division connection index, geometric arithmetic connection index, and atom bond connectivity connection index, of two significant types of backbone DNA and Barycentric subdivision of backbone DNA networks. Direct method computation is used to produce these Connection-based topological descriptors.