QuantumPioneer: Scalable generation of quantum chemical data for solution-phase hydrogen transfer reactions

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Authors: Haoyang Wu, Jonathan Wenyuan Zheng, Hao‐Wei Pang, Yu-Chi Kao, Akshat Shirish Zalte, Charlles R. A. Abreu, Emad Al Ibrahim, Sayandeep Biswas, Chansup Byun, Jackson W. Burns, Chuangchuang Cao, Yunsie Chung
+15 more Xiaorui Dong, Anna C. Doner, Jeremy Kepner, Bonhyeok Koo, Shih‐Cheng Li, Angiras Menon, Lauren Milechin, Nathan Morgan, Kariana Moreno Sader, Kevin Spiekermann, Florence H. Vermeire, Bryan Wang, Markus Kraft, Connor W. Coley, William H. Green
Cited by: 1

Abstract

High-fidelity quantum chemical (QM) datasets that jointly resolve reaction thermochemistry, kinetics, and solvation at scale remain scarce, especially for radical chemistry. We introduce QuantumPioneer, an open-access reaction-centered QM database and workflow for small organic molecules, focused on peroxyl-mediated hydrogen atom transfer (HAT) and the corresponding homolytic bond dissociation reactions. QuantumPioneer contains 348,258 species (2–21 heavy atoms), 167,237 validated HAT transition states (TS) with corresponding reaction energies and homolytic bond dissociation energies (BDEs), and over 100 million COSMO-RS solvation free energies (∆Go_solv) and enthalpies (∆Ho_solv) across 295 solvents. The workflow uses ωB97X-D/def2-SVP geometries, DLPNO-CCSD(T)-F12d/def2-TZVP single-point energies, empirical thermochemical corrections, transition-state theory, and COSMORS BP-TZVPD-FINE solvation in a single high-throughput pipeline. Our benchmarks show reliable accuracy, with mean absolute errors compared to experimental data of 0.82 kcal/mol for gas-phase enthalpies of formation, 1.60 kcal/mol for C–H BDEs, 1.45 kcal/mol for HAT barriers, and 0.57 kcal/mol for ∆Go_solv values. We demonstrate two predictive applications. First, we show that a combined BDE and HAT-barrier model identifies experimentally observed oxidative degradation sites in drug-like molecules with a 91% top-5 hit rate and 80% site-level recall. Second, a QM-parameterized Abraham model enables rapid solvation energy estimates at near-COSMO-RS accuracy within its training domain, reproducing ∆Go_solv and ∆Ho_solv values with MAEs of 0.16 kcal/mol and 0.18 kcal/mol, respectively, though performance on experimental ΔGo_solv values for unseen solutes was worse, with MAEs of 1.32 kcal/mol, providing a scalable template for other reaction families, unifying equilibrium species, validated TS, thermochemistry, kinetics, and solvation into one workflow.

Fields of Study & Subjects

Metal-Catalyzed Oxygenation Mechanisms Machine Learning in Materials Science Free Radicals and Antioxidants

Publication details

Journal / source
ChemRxiv
Publisher
American Chemical Society (ACS)
Publication date
12 July 2026
Document type
Preprint