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Abstract High-level quantum mechanical (QM) calculations are indispensable for accurate explanation of natural phenomena on the atomistic level. Their staggering computational cost, however, poses great limitations, which luckily can be lifted to a great extent by exploiting advances in artificial intelligence (AI). Here we introduce the general-purpose, highly transferable artificial intelligence–quantum mechanical method 1 (AIQM1). It approaches the accuracy of the gold-standard coupled cluster QM method with high computational speed of the approximate low-level semiempirical QM methods for the neutral, closed-shell species in the ground state. AIQM1 can provide accurate ground-state energies for diverse organic compounds as well as geometries for even challenging systems such as large conjugated compounds (fullerene C 60 ) close to experiment. This opens an opportunity to investigate chemical compounds with previously unattainable speed and accuracy as we demonstrate by determining geometries of polyyne molecules—the task difficult for both experiment and theory. Noteworthy, our method’s accuracy is also good for ions and excited-state properties, although the neural network part of AIQM1 was never fitted to these properties. 

Deriving diverse compound libraries from a single substrate in high yields remains to be a challenge in cycloparaphenylene chemistry. In here, a strategy for the late‐stage functionalization of shape‐persistent alkyne‐containing cycloparaphenylene has been explored using readily available azides. The copper‐free [3+2]azide‐alkyne cycloaddition provided high yields (>90 %) in a single reaction step. Systematic variation of the azides from electron‐rich to ‐deficient shines light on how peripheral substitution influences the characteristics of the resulting adducts. We find that among the most affected properties are the molecular shape, the oxidation potential, excited state features, and affinities towards different fullerenes. Joint experimental and theoretical results are presented including calculations with the state‐of‐the‐art, artificial intelligence‐enhanced quantum mechanical method 1 (AIQM1).