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Ring-Polymer Instanton Tunneling Splittings of Tropolone and Isotopomers using a Δ-Machine Learned CCSD(T) Potential: Theory and Experiment Shake Hands

Apurba Nandi, Gabriel Laude, Subodh S. Khire, Nalini D. Gurav, Chen Qu, Riccardo Conte, Qi Yu, Shuhang Li, Paul L. Houston, Shridhar R. Gadre, Jeremy O. Richardson, Francesco A. Evangelista, Joel M. Bowman

2023Journal of the American Chemical Society35 citationsDOIOpen Access PDF

Abstract

Tropolone, a 15-atom cyclic molecule, has received much interest both experimentally and theoretically due to its H-transfer tunneling dynamics. An accurate theoretical description is challenging owing to the need to develop a high-level potential energy surface (PES) and then to simulate quantum-mechanical tunneling on this PES in full dimensionality. Here, we tackle both aspects of this challenge and make detailed comparisons with experiments for numerous isotopomers. The PES, of near CCSD(T)-quality, is obtained using a Δ-machine learning approach starting from a pre-existing low-level DFT PES and corrected by a small number of approximate CCSD(T) energies obtained using the fragmentation-based molecular tailoring approach. The resulting PES is benchmarked against DF-FNO-CCSD(T) and CCSD(T)-F12 calculations. Ring-polymer instanton calculations of the splittings, obtained with the Δ-corrected PES are in good agreement with previously reported experiments and a significant improvement over those obtained using the low-level DFT PES. The instanton path includes heavy-atom tunneling effects and cuts the corner, thereby avoiding passing through the conventional saddle-point transition state. This is in contradistinction with typical approaches based on the minimum-energy reaction path. Finally, the subtle changes in the splittings for some of the heavy-atom isotopomers seen experimentally are reproduced and explained.

Topics & Concepts

InstantonChemistryIsotopomersTropoloneQuantum tunnellingPotential energy surfaceSaddle pointPotential energyAtom (system on chip)Path (computing)Curse of dimensionalityComputational chemistryAtomic physicsQuantum mechanicsMoleculePhysicsProgramming languageGeometryComputer scienceOrganic chemistryEmbedded systemMathematicsMachine learningAdvanced Chemical Physics StudiesMolecular Junctions and NanostructuresSpectroscopy and Quantum Chemical Studies