Ring-Polymer Instanton Tunneling Splittings of Tropolone and Isotopomers using a Δ-Machine Learned CCSD(T) Potential: Theory and Experiment Shake Hands.
| Title: | Ring-Polymer Instanton Tunneling Splittings of Tropolone and Isotopomers using a Δ-Machine Learned CCSD(T) Potential: Theory and Experiment Shake Hands. |
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| Authors: | Nandi A; Department of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, United States.; Laude G; Laboratory of Physical Chemistry, ETH Zürich, 8093 Zürich, Switzerland.; Khire SS; RIKEN Center for Computational Science, Kobe 650-0047, Japan.; Gurav ND; Organisch-Chemisches Institut, University of Münster, 48149 Münster, Germany.; Qu C; Independent Researcher, Toronto M9B0E3, Canada.; Conte R; Dipartimento di Chimica, Università Degli Studi di Milano, Via Golgi 19, 20133 Milano, Italy.; Yu Q; Department of Chemistry, Yale University, New Haven, Connecticut 06520, United States.; Li S; Department of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, United States.; Houston PL; Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States.; Department of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.; Gadre SR; Department of Scientific Computing, Modelling and Simulation, Savitribai Phule Pune University, Pune 411 007, India.; Richardson JO; Laboratory of Physical Chemistry, ETH Zürich, 8093 Zürich, Switzerland.; Evangelista FA; Department of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, United States.; Bowman JM; Department of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, United States. |
| Source: | Journal of the American Chemical Society [J Am Chem Soc] 2023 May 03; Vol. 145 (17), pp. 9655-9664. Date of Electronic Publication: 2023 Apr 20. |
| Publication Type: | Journal Article |
| Language: | English |
| Journal Info: | Publisher: American Chemical Society Country of Publication: United States NLM ID: 7503056 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1520-5126 (Electronic) Linking ISSN: 00027863 NLM ISO Abbreviation: J Am Chem Soc Subsets: MEDLINE; PubMed not MEDLINE |
| Imprint Name(s): | Publication: Washington, DC : American Chemical Society; Original Publication: Easton, Pa. [etc.] |
| 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. |
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| Entry Date(s): | Date Created: 20230420 Date Completed: 20230503 Latest Revision: 20230508 |
| Update Code: | 20260130 |
| PubMed Central ID: | PMC10161208 |
| DOI: | 10.1021/jacs.3c00769 |
| PMID: | 37078852 |
| Database: | MEDLINE |
Journal Article