Dr. Suliman Khan
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Academic Career Length
7Years (2020-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications25 May 2020 in Polycyclic Aromatic Compounds
Journal Article
In this article, the efficiency of all the well-known valency-based molecular descriptors has been measured using certain comparative testing. Importantly, we use a computational technique for hexagonal systems to generate regression models to determine the correlation of valency-based molecular descriptors with the π-electronic energies for polycyclic aromatic hydrocarbons. The study implicates some favorable outcomes as the sum-connectivity index and certain Randić index have correlation coefficient of 0.9999. To ensure the applicability of our proposed study, we compute analytically explicit expressions for efficient valency-based molecular descriptors for certain infinite families of carbon nanotubes and carbon nanocones. Our results assist in correlating the π-electronic energies of underlying chemical structures of these nanotubes and nanocones.
1 March 2021 in Journal of Molecular Structure
Journal Article
SHSakander Hayat
Sakander HayatSuliman Khan1 December 2020 in Journal of Molecular Structure
Journal Article
SHSakander Hayat
Sakander HayatSuliman Khan
Muhammad Imran
Jia-Bao Liu8 July 2020 in Mathematical Methods in the Applied Sciences
Journal Article
SHSakander Hayat
Sakander HayatSuliman KhanAKAsad Khan
Asad Khan
Muhammad Imran1 March 2021 in Arabian Journal of Chemistry
Journal Article
21 January 2021 in IEEE Access
Journal Article
Graph signal processing deals with signals whose domain, defined by a graph, is irregular. The total $\pi $ -electron energy or simply the $\pi $ -electronic energy, as calculated within the Hückel tight-binding molecular orbital approximation, is one of the important quantum-theoretical characteristic of conjugated molecules. In this paper, we propose an efficient computer-assisted computational method to determine eigenvalues-based distance descriptors for chemical compounds which are then used to learn to quantitative relationship between the activity/property and the structure (QSAR/QSPR) of compound. Comparisons with other similar methods show that our proposed method possesses less algorithmic and computational complexities and is more computationally diverse. The proposed method is used to determine predictive potential of eigenvalues-based distance descriptors for measuring the $\pi $ -electronic energy of benzenoid hydrocarbons. Importantly, we propose three new chemical matrices and, unexpectedly, results show that the spectral descriptors defined based on new chemical matrices outperform all the well-known descriptors in the literature. Specifically, our proposed second atom-bond connectivity Estrada index show the best correlation coefficient of 0.9997. Applications of our computational method to certain infinite families of carbon nanotubes and carbon nanocones are presented. The obtained results can potentially be used to determine the $\pi $ -electronic energy of these nanotubes and nanocones theoretically with higher accuracy and negligible error.
About Me
Dr. Suliman Khan completed his Ph.D. in Mathematics at the Department of Mathematics and Physics, University of Campania Luigi Vanvitelli, Italy, where he was admitted in February 2022 under the Italian Government Scholarship. His doctoral research focused on spectral graph theory, discrete mathematics, and combinatorics, with particular emphasis on signed graphs and gain graphs and their applications to structural and spectral properties of graphs.
He obtained his M.S. degree in Applied Mathematics from the GIK Institute of Engineering Sciences and Technology, Topi, Pakistan, where he achieved outstanding academic distinction by winning the University Gold Medal across all sciences.
Dr. Khan has published more than 20 research articles in reputable international journals. His main research interests include graph theory, spectral graph theory, chemical graph theory, signed graphs, and gain graphs. He is also an active reviewer for several international journals, including Linear Algebra and its Applications, Journal of Graph Theory, Discrete Mathematics, Scientific Reports, AIP Advances, International Journal of Modern Physics B, TWMS Journal of Applied and Engineering Mathematics, Journal of King Saud University – Science, Arabian Journal of Chemistry, and Polycyclic Aromatic Compounds etc.