Work

Data-driven approaches to study the spectral properties of chemical structures

Year: 2024

Type: article

Abstract: The molecular energy, which is the sum of all eigenvalues, is crucial in determining the total π-electron energy of conjugated hydrocarbon molecules. We used machine learning techniques to calculate the energy, inertia, nullity, signature, and Estrada index of molecular graphs for bismuth tri-iodide and benzene rings embedded in P-type surfaces within 2D networks. We applied MATLAB to extract the actual eigenvalues from the data and developed general equations for these molecular properties. We then used these equations to estimate the values and compared them to the actual values through graphical analysis. Our results demonstrate the potential of data-driven techniques in predicting molecular properties and enhancing our understanding of spectral theory.

Source: Heliyon

DOI: 10.1016/j.heliyon.2024.e37459

Authors: Ibtisam Masmali, Muhammad Faisal Nadeem, Zeeshan Saleem Mufti, Ali Ahmad, Ali N.A. Koam, Haleemah Ghazwani

Institutions: Jazan University, COMSATS University Islamabad, University of Lahore

Language: English

Topic: Graph theory and applications

Subfield: Geometry and Topology

Field: Mathematics

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,100

Funders: Jazan University, Ministry of Education – Kingdom of Saudi Arabi