Buchwald Hartwig: High-Throughput C-N Cross-Coupling Reaction Yields

High-throughput experimentation data for palladium-catalyzed Buchwald-Hartwig C-N cross-coupling reactions, curated by the jablonkagroup. The dataset includes reaction yields and is associated with a 2018 publication on predicting reaction performance using machine learning. It was last updated on the Hugging Face platform in May 2025.

Use Cases

• Predicting reaction yields based on high-throughput experimental conditions.
• Training machine learning models for reaction performance as described in the associated publication.
• Analyzing structure-property relationships in palladium-catalyzed cross-coupling reactions.
• Benchmarking computational chemistry models against experimental yield data.

Strengths

• Data originates from high-throughput experimentation, suggesting systematic coverage of reaction space.
• Associated with a peer-reviewed 2018 publication on machine learning in chemistry.
• Explicitly includes reaction yields, a key performance metric.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

jablonkagroup on Hugging Face, associated with the publication 'Predicting reaction performance in C--N cross-coupling using machine learning' (Ahneman et al., 2018).

Collection Method

High-throughput experimentation for palladium-catalyzed reactions.

Freshness

Last updated 2025-05-06 06:31:50; freshness should be verified.