Benchmarking Isomerization Energies for C5$$ {\mathrm{C}}_5 $$–C7$$ {\mathrm{C}}_7 $$ Hydrocarbons: The ISOC7 Database

ABSTRACT Highly accurate benchmark databases are critical for the development of robust and computationally efficient electronic structure methods. We introduce the ISOC7 database, a diverse collection of 1308 unique constitutional isomers of – saturated and unsaturated hydrocarbons with reference isomerization energies at the CCSD(T)/CBS level of theory, obtained via the W1‐F12 thermochemical protocol. The isomerization energies in this dataset span over 146 . This database was used to conduct a rigorous benchmark assessment of a wide hierarchy of computational methods. The performance of 40 contemporary density functional theory (DFT) functionals reveals a general, albeit not monotonic, improvement along the rungs of Jacob's Ladder, with lower‐rung GGA and MGGA functionals providing generally poor performance. The range‐separated hybrid‐meta‐GGA functional B97M‐D4 emerges as the top DFT performer with a root‐mean‐square deviation (RMSD) of 1.62 . We also evaluated computationally economical semiempirical and tight‐binding methods. While traditional semiempirical approaches are inadequate, the modern g‐xTB tight‐binding method achieves a respectable RMSD of 4.14 . Remarkably, the machine‐learned neural network potential AIMNet2 delivers exceptional accuracy, achieving an RMSD of 1.67 , rivaling the performance of the best DFT functional at a fraction of the computational cost. The ISOC7 database provides a challenging benchmark for advancing the development and validation of both quantum chemical and machine learning methods.