How reliable is DFT in predicting relative energies of polycyclic aromatic hydrocarbon isomers? comparison of functionals from different rungs of jacob's ladder.

Density functional theory (DFT) is the only quantum-chemical avenue for calculating thermochemical/kinetic properties of large polycyclic aromatic hydrocarbons (PAHs) such as graphene nanoflakes. Using CCSD(T)/CBS PAH isomerization energies, we find that all generalized gradient approximation (GGA) and meta GGA DFT functionals have severe difficulties in describing isomerization energies in PAHs. The poor performance of these functionals is demonstrated by the following root-mean-square deviations (RMSDs) obtained for a database of C14 H10 and C18 H12 isomerization energies. The RMSDs for the GGAs range between 6.0 (BP86-D3) and 23.0 (SOGGA11) and for the meta GGAs they range between 3.5 (MN12-L) and 11.9 (τ-HCTH) kJ mol-1 . These functionals (including the dispersion-corrected methods) systematically and significantly underestimate the isomerization energies. A consequence of this behavior is that they all predict that chrysene (rather than triphenylene) is the most stable C18 H12 isomer. A general improvement in performance is observed along the rungs of Jacob's Ladder; however, only a handful of functionals from rung four give good performance for PAH isomerization energies. These include functionals with high percentages (40-50%) of exact Hartree-Fock exchange such as the hybrid GGA SOGGA11-X (RMSD = 1.7 kJ mol-1 ) and the hybrid-meta GGA BMK (RMSD = 1.3 kJ mol-1 ). Alternatively, the inclusion of lower percentages (20-30%) of exact exchange in conjunction with an empirical dispersion correction results in good performance. For example, the hybrid GGA PBE0-D3 attains an RMSD of 1.5 kJ mol-1 , and the hybrid-meta GGAs PW6B95-D3 and B1B95-D3 result in RMSDs below 1 kJ mol-1 .