Investigating hexagonal closed packed crystal lattice through QSPR modeling via linear regression analysis and Topsis

Abstract

sThis research work covers three highly dominating reverse degree-based topological descriptors evaluated for the three-dimensional hexagonal close-packed (HCP) crystal structure lattice. HCP crystal lattice has a highly symmetrical and elegant crystal structure, and we have observed that results obtained from symmetrical structures draw symmetry in the numerical formulation obtained from topological descriptors. For this purpose, we will investigate whether the HCP lattice formed by an odd pair of unit cells is the best or an even pair of unit cells forming the lattice and how they behave in a dominating sense when investigated through the conclusions obtained from QSPR modeling. The QSPR model has been proposed to check the efficiency of each specified topological descriptor for five highly commendable physio-chemical properties: melting or boiling point, density, molar heat capacity, and enthalpy. Further, we have discovered the ideology to obtain the best possible structure when investigated and established on a statistically and mathematically strong proving and to what extent we can extract from QSPR to implement MCDM techniques, here considering TOPSIS that provide the best HCP structure lattice rankings. The obtained results may be helpful for researchers to better understand the structure and studying different physical/chemical properties of HCP crystal lattice.