{"url":"/dataset/machine-learning-quantum-reaction-rate","name":"Machine Learning Quantum Reaction Rate Constants","full_name":"Evan Komp and Stephanie Valleau","description_markdown":"Dataset of 1,517,419 quantum reaction rate constant products kQM(T)QR(T) computed from the transmission coefficient for model single and double barrier minimum energy paths. Here kQM(T) is the quantum reaction rate constant at temperature T and QR(T) is the reactant partition function computed with the rigid rotor and harmonic oscillator approximations.This dataset was created for Ref [1] where it was used to train and test a DNN to predict logkQM(T)QR(T).\r\n\r\nSee zenodo webpage for details and dataset\r\nhttps://zenodo.org/record/5510392#.YUkbjWZKhOc","description_withheld":null,"homepage":"https://zenodo.org/record/5510392#.YUkbjWZKhOc","introduced_date":"2020-07-16","introduced_date_note":null,"introduced_by":{"paper":null,"title":"Machine Learning Quantum Reaction Rate Constants","first_author":null,"url":null},"license":{"name":"Creative Commons Attribution 4.0 International","url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"modalities":[],"tasks":[],"languages":[],"variants":["Machine Learning Quantum Reaction Rate Constants"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}