ArticleScientific data2022
High accuracy barrier heights, enthalpies, and rate coefficients for chemical reactions.
Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Methods for the establishment of enzymatic mechanisms - from QM to ML.Chemical science · 2026Review
- Chalcogen Impurity Barriers in 2D Systems via Semi-Empirical/Machine Learning Modeling: A Survey of 4000 Materials.Journal of chemical theory and computation · 2026Article
- Reactive Chemistry at the Unrestricted Coupled Cluster Level: High-Throughput Calculations for Training Machine Learning Potentials.Journal of chemical theory and computation · 2026Article
- SynRXN: An Open Benchmark and Curated Dataset for Computational Reaction Modeling.Scientific data · 2026Article
- ChemTorch: A Deep Learning Framework for Benchmarking and Developing Chemical Reaction Property Prediction Models.Journal of chemical information and modeling · 2026Article
- Rapid Generation of Transition-State Conformer Ensembles via Constrained Distance Geometry.Journal of chemical information and modeling · 2026Article
- Foundation models for atomistic simulation of chemistry and materials.Nature reviews. Chemistry · 2026Review
- The consolidation of open-source computer-assisted chemical synthesis data into a comprehensive database.Journal of cheminformatics · 2025Article
- GoFlow: efficient transition state geometry prediction with flow matching and E(3)-equivariant neural networks.Digital discovery · 2025Article
- Graph-based prediction of reaction barrier heights with on-the-fly prediction of transition states.Digital discovery · 2025Article
- A Deep Learning-Augmented Density Functional Framework for Reaction Modeling with Chemical Accuracy.JACS Au · 2025Article
- Machine learning applications for thermochemical and kinetic property prediction.Reviews in chemical engineering · 2025Review
- Enhancing Activation Energy Predictions under Data Constraints Using Graph Neural Networks.Journal of chemical information and modeling · 2025Article
- Data Generation for Machine Learning Interatomic Potentials and Beyond.Chemical reviews · 2024Review
- 3DReact: Geometric Deep Learning for Chemical Reactions.Journal of chemical information and modeling · 2024Article
- Benchmarking machine-readable vectors of chemical reactions on computed activation barriers.Digital discovery · 2024Article
- Machine learning from quantum chemistry to predict experimental solvent effects on reaction rates.Chemical science · 2024Article
- Barrier Height Prediction by Machine Learning Correction of Semiempirical Calculations.The journal of physical chemistry. A · 2023Article
- High accuracy barrier heights, enthalpies, and rate coefficients for chemical reactions.Scientific data · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Quantitative chemical reaction data, including activation energies and reaction rates, are crucial for developing detailed kinetic mechanisms and accurately predicting reaction outcomes. However, such data are often difficult to find, and high-quality datasets are especially rare. Here, we use CCSD(T)-F12a/cc-pVDZ-F12//ωB97X-D3/def2-TZVP to obtain high-quality single point calculations for nearly 22,000 unique stable species and transition states. We report the results from these quantum chemistry calculations and extract the barrier heights and reaction enthalpies to create a kinetics dataset of nearly 12,000 gas-phase reactions. These reactions involve H, C, N, and O, contain up to seven heavy atoms, and have cleaned atom-mapped SMILES. Our higher-accuracy coupled-cluster barrier heights differ significantly (RMSE of ∼5 kcal mol
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.