Predictive modeling of thermochemical stability of hydrogen boride via reverse topological indices and curve fitting techniques

The present work explores the correlation between the values of the heat of formation (HOF) and topological indices of hydrogen boride (B 2 H 6 ), which is a compound having an unique electron-deficient molecular structure. Topological indices play a significant role in mathematical chemistry by providing numerical descriptors that reflect the structural characteristics of molecular networks and their physicochemical behavior. The current study applies sophisticated curve fitting algorithms to quantitatively assess reverse degree-based topological indices and their correlation with the heat of formation HOF for the hydrogen boride network (B 2 H 6 ). To find out how well they predicted thermochemical stability, a number of reverse indices were calculated, such as the reverse Zagreb indices, reverse Balaban index, and reverse forgotten index. To construct precise mathematical correlations between each topological index and the related HOF values, nonlinear curve fitting models were created. Additionally, the combination of statistical and computational methods offers a dependable and effective framework for investigating structure-property connections in boron-based nano structures. This approach can be expanded to additional molecular systems to improve materials science and chemical graph theory predictive modeling.