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

Here, a new challenging benchmarking data set for cycloaddition reactions, CYCLO70, is presented and analyzed. CYCLO70 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 data set for this reaction class. Furthermore, we observe that the range-separated hybrid ωB97M-V is the best performing functional to model barrier heights and reaction energies, with a deviation closest to the desirable "chemical accuracy"; among the double hybrids, PBE-QIDH performs best, and among the fixed-range hybrids, M06-2X and r²SCAN0 emerge as the most balanced in terms of simultaneously reproducing both properties. Next, we perform a principal component analysis on the errors across the data set 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. These results were further validated on a set of Diels-Alder reactions relevant to self-healing polymer design, reinforcing the practical relevance of CYCLO70.