Alchemical Predictions for 14-Electron Diatomic Molecules Across Basis Sets

A database of alchemical predictions for a series of 14-electron diatomic molecules, published as supplementary information to a research paper. The data were calculated using eight different basis sets. The dataset was authored by Giorgio Domenichini from the University of Basel.

Use Cases

• Benchmarking alchemical prediction accuracy based on data calculated with eight different basis sets.
• Analyzing the effect of basis set choice on alchemical predictions for diatomic molecules.
• Training or validating machine learning models for quantum chemical property prediction based on alchemical perturbation data.

Strengths

• Data is directly linked to a published research paper, providing academic context.
• Calculations were performed for eight different basis sets, allowing for comparative analysis.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

University of Basel

Collection Method

Calculated quantum chemical data published as supplementary information.