Browsing by Author "Alharbi, Fahad M."

Now showing 1 - 2 of 2

Characterizations of Chemical Networks Entropies by K-Banhatii Topological Indices
(Mdpi, 2023) Ghani, Muhammad Usman; Campena, Francis Joseph H.; Ali, Shahbaz; Dehraj, Sanaullah; Cancan, Murat; Alharbi, Fahad M.; Galal, Ahmed M.
Entropy is a thermodynamic function in physics that measures the randomness and disorder of molecules in a particular system or process based on the diversity of configurations that molecules might take. Distance-based entropy is used to address a wide range of problems in the domains of mathematics, biology, chemical graph theory, organic and inorganic chemistry, and other disciplines. We explain the basic applications of distance-based entropy to chemical phenomena. These applications include signal processing, structural studies on crystals, molecular ensembles, and quantifying the chemical and electrical structures of molecules. In this study, we examine the characterisation of polyphenylenes and boron (B-12) using a line of symmetry. Our ability to quickly ascertain the valences of each atom, and the total number of atom bonds is made possible by the symmetrical chemical structures of polyphenylenes and boron B-12. By constructing these structures with degree-based indices, namely the K Banhatti indices, ReZG(1)-index, ReZG(2)-index, and ReZG(3)-index, we are able to determine their respective entropies.
Entropy Related To K-Banhatti Indices Via Valency Based on the Presence of C6h6 in Various Molecules
(Mdpi, 2023) Ghani, Muhammad Usman; Campena, Francis Joseph H.; Maqbool, Muhammad Kashif; Liu, Jia-Bao; Dehraj, Sanaullah; Cancan, Murat; Alharbi, Fahad M.
Entropy is a measure of a system's molecular disorder or unpredictability since work is produced by organized molecular motion. Shannon's entropy metric is applied to represent a random graph's variability. Entropy is a thermodynamic function in physics that, based on the variety of possible configurations for molecules to take, describes the randomness and disorder of molecules in a given system or process. Numerous issues in the fields of mathematics, biology, chemical graph theory, organic and inorganic chemistry, and other disciplines are resolved using distance-based entropy. These applications cover quantifying molecules' chemical and electrical structures, signal processing, structural investigations on crystals, and molecular ensembles. In this paper, we look at K-Banhatti entropies using K-Banhatti indices for C6H6 embedded in different chemical networks. Our goal is to investigate the valency-based molecular invariants and K-Banhatti entropies for three chemical networks: the circumnaphthalene (CNBn), the honeycomb (HBn), and the pyrene (PYn). In order to reach conclusions, we apply the method of atom-bond partitioning based on valences, which is an application of spectral graph theory. We obtain the precise values of the first K-Banhatti entropy, the second K-Banhatti entropy, the first hyper K-Banhatti entropy, and the second hyper K-Banhatti entropy for the three chemical networks in the main results and conclusion.