Molecular Descriptors of Porphyrin-based Dendrimer

Liu, Jia‐Bao; Xavier, D. Antony; Varghese, Eddith Sarah; Baby, Annmaria; Mathew, Deepa

doi:10.1080/10406638.2022.2112714

Cited by 8 publications

(1 citation statement)

References 41 publications

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“…Mondal and Das [23] explored the application of degree‐based graph entropy in structure‐property modeling, shedding light on the intricate relationships between graph structures and molecular properties. Liu et al [24] presented a comprehensive study on computing entropy based molecular descriptors for Polyphenylene Dendrimers, contributing to the understanding of these complex molecular structures. Dong et al [25] investigated the impact of graph operations on degree‐based entropy, providing valuable insights into the behavior of graph structures under various operations.…”

Section: Introductionmentioning

confidence: 99%

On distance dependent entropy measures of poly propylene imine and zinc porphyrin dendrimers

Wei,

Fahad,

Raza

et al. 2024

Int J of Quantum Chemistry

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A key paradigm in contemporary research is the use of graphs to represent physical systems, molecular structures, or particularly metal frameworks. Graphs are increasingly widely used in a variety of fields, including the study of quantum and molecular systems, macromolecules and their interactions, socioeconomic and ecological systems, and technical and infra‐structural systems. Understanding how these systems function, are robust, and are stable begins with structural characterization. The use of entropies and entropy‐like measurements of graphs/structures of molecules/networks is crucial from both a mathematical and physical standpoint. Several entropy measures of graphs have been defined and studied extensively during the last few decades. The current paper is devoted to investigation of distance dependent entropy measures of Poly Propylene Imine (PPI) dendrimers and Zinc Porphyrin dendrimers. The analytical formulae of distance dependent entropy measures have been developed and their patterns have been presented through graphical tools.

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Section: Introductionmentioning

confidence: 99%