Big-Data Analysis of Geometric Descriptors as Efficient Predictors of Energetic Stability in Nonplanar Polycyclic Aromatic Hydrocarbons.

ABSTRACT: Accurate, efficient stability predictors are essential for understanding isomer formation in polycyclic aromatic hydrocarbons (PAHs), with implications for pollution toxicity and carbon-material design, holding broad environmental and technological significance. Recently, a benchmark study demonstrated that PBE0-D4 reproduces CCSD(T)-level isomerization energies for 335 PAHs with a mean absolute deviation (MAD) of 0.67 kcal mol^-1. Here, we apply the PBE0-D4/6-31G(2df,p) level of theory to 38,264 PAH isomers from the COMPAS-3x database and identify fast, geometry-based parameters that predict isomer stability. The total dihedral deviation (Σ_Dihedral) provides a cost-free nonplanarity metric yielding a mean absolute deviation (MAD) of 3.6 kcal mol^-1, outperfo

SUBMITTER: Gregory KP 

PROVIDER: S-EPMC12315058 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature