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BorylXAT-DB: an IRC-validated transition-state database for machine-learning prediction of Lewis base-boryl radical C-Cl XAT barriers

BorylXAT-DB is an IRC-validated quantum-chemical transition-state database for Lewis base-coordinated boryl-radical mediated C-Cl halogen-atom transfer (XAT). It was constructed from a reaction space comprising 55 boryl radicals, 386 Lewis bases, and 179 chlorinated substrates. Thermodynamic filt

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CreatorLi, Jia-Qi
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Published2026-07-13
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DOI10.5281/zenodo.21330198
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Downloads142
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Licensecc-by-4.0
File Size704.6 MB
Data TypeDataset
Published2026
Licensecc-by-4.0
Total Views66
Total Downloads142

BorylXAT-DB is an IRC-validated quantum-chemical transition-state database for Lewis base-coordinated boryl-radical mediated C-Cl halogen-atom transfer (XAT). It was constructed from a reaction space comprising 55 boryl radicals, 386 Lewis bases, and 179 chlorinated substrates. Thermodynamic filtering, automated transition-state searches, frequency analysis, and bidirectional IRC validation produced 9,237 validated transition states with complete reactant-transition-state-product mappings.

The release includes two complementary data products: BorylXAT-DB.db, an ASE SQLite database for atomistic inspection and reaction-path reconstruction, and BorylXAT-DB.parquet, a flattened Parquet table for statistical analysis and machine-learning workflows. The dataset contains 50,057 ASE structures, including boryl radicals, Lewis bases, chlorinated substrates, reactant complexes, product complexes, carbon-radical products, and IRC-validated transition states.

Each transition-state entry stores component identifiers, reactant and product mapping keys, activation free energy, reaction free energy, imaginary-frequency information, and IRC endpoint data. The release also includes metadata, checksum information, a schema summary, a minimal Python requirements file, and an example loading script.

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BorylXAT-DB: an IRC-validated transition-state database for machine-learning prediction… (Full Dataset)704.6 MB
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Files are hosted on the source repository. Click download to access the full dataset.

Li, Jia-Qi (2026). BorylXAT-DB: an IRC-validated transition-state database for machine-learning prediction of Lewis base-boryl radical C-Cl XAT barriers. https://doi.org/10.5281/zenodo.21330198