CYCLO70: A New Challenging Pericyclic Benchmarking Set for Kinetics and Thermochemistry Evaluation

Here, a new challenging benchmarking dataset for cycloaddition reactions, CYCLO70, is presented and analyzed. CYCL70 has been generated with the specific aim of being representative of the most challenging regions of the chemical reaction space surrounding Diels-Alder, dipolar cycloadditions, and (sigmatropic) rearrangement reactions with the help of an active learning approach. Testing 93 different functionals, spanning from spin-local density approximation to the most recent double-hybrid functionals, we observe that the errors on CYCLO70 are significantly bigger than those on the cycloaddition subset of BH9, the most popular benchmarking dataset for this reaction class. Furthermore, we observe that only one functional, the range-separated hybrid $\omega$B97M-V, reaches the desirable "chemical accuracy" to model barrier heights and reaction energies; among the double hybrids, PBE-QIDH performs best, and among the hybrids, it is M06-2X and r$^2$SCAN50 that exhibit the lowest errors. Lastly, we perform a principal component analysis for the errors across the dataset, and demonstrate not only that the errors across different functional approximations correlate to a significant extent (the first two components explain 98\% of the variance), but we also observe that functionals belonging to the same rung of Jacob's ladder cluster together in the constructed two dimensional plot.