TY - JOUR
T1 - Computing Molecular Topological Descriptors of Polymeric Networks Modeled by Sierpinski Networks
AU - Iqbal, Muhamamd Azhar
AU - Imran, Muhammad
AU - Siddiqui, Muhammad Kamran
AU - Zaighum, Muhammad Asad
N1 - Publisher Copyright:
© 2020, © 2020 Taylor & Francis Group, LLC.
PY - 2020
Y1 - 2020
N2 - Sierpinski networks constitute an extensively studied class of graphs of fractal nature applicable in topology, mathematics of Tower of Hanoi, computer science, and Chemical graph theory. Recently the properties of Sierpinski networks have been studied like physico-chemical properties, thermodynamic properties, chemical activity, biological activity, metric dimension and degree based topological indices. In this paper, we further extend the study of Sierpinski networks and computed Zagreb types molecular descriptors (molecular topological indices) and their variants.
AB - Sierpinski networks constitute an extensively studied class of graphs of fractal nature applicable in topology, mathematics of Tower of Hanoi, computer science, and Chemical graph theory. Recently the properties of Sierpinski networks have been studied like physico-chemical properties, thermodynamic properties, chemical activity, biological activity, metric dimension and degree based topological indices. In this paper, we further extend the study of Sierpinski networks and computed Zagreb types molecular descriptors (molecular topological indices) and their variants.
KW - Balaban index
KW - Sanskruti index
KW - Sierpinski networks
KW - Zagreb indices
KW - forgotten topological index
KW - molecular descriptors
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U2 - 10.1080/10406638.2020.1783331
DO - 10.1080/10406638.2020.1783331
M3 - Article
AN - SCOPUS:85087632319
SN - 1040-6638
JO - Polycyclic Aromatic Compounds
JF - Polycyclic Aromatic Compounds
ER -