4.6 Article

Statistical-mechanical theory of topological indices

Journal

Publisher

ELSEVIER
DOI: 10.1016/j.physa.2022.127612

Keywords

Topological indices; Partition function; Tight-binding Hamiltonian; Graph theory; Statistical mechanics

Funding

  1. MCIN/AEI/10.13039/501100011033/ [PID2019-107603GB-I00]

Ask authors/readers for more resources

This paper proves that topological indices can serve as partition functions for molecules and proposes a statistical-mechanical theory to describe them. Molecular electronic properties are described using tight-binding Hamiltonians, and it is shown that these Hamiltonians can be simplified to symmetric ones. The theory is further validated by deriving various topological indices.
Topological indices (TI) are algebraic invariants of molecular graphs representing the topology of a molecule, which are very valuable in quantitative structure-property relations (QSPR). Here we prove that TI are the partition functions of such molecules when the temperature of the thermal bath at which they are submerged is very high. These partition functions are obtained by describing molecular electronic properties through tight-binding Hamiltonians (TBH), where the hopping parameters are topological properties describing atom-atom interactions. We prove that the TBH proposed here are non-Hermitian diagonalizable Hamiltonians which can be replaced by symmetric ones. In this way we propose a statistical-mechanical theory for TI, which is exemplified by deriving the Randic, Zagreb, Balaban, Wiener and ABC indices. The work also illuminates how to improve QSPR models using the current theoretical framework as well as how to derive statistical-mechanical parameters of molecular graphs. (C) 2022 Elsevier B.V. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available