S66-BSIE: Benchmark Molecular Energies and Geometries for Non-Covalent Interactions

S66-BSIE contains energies and geometries for molecular complexes from the S66x8 and S66x100 datasets. The S66x100 dataset provides one hundred geometries per complex across a range of separation distances, with energies computed using the Psi4 package at RHF or B3LYP theory levels with multiple basis sets. The dataset was created by Søren Holm of Stanford University, extending the original S66x8 work by Goerigk, Kruse, and Grimme.

Use Cases

• Benchmarking quantum chemistry methods based on interaction energies for non-covalent complexes.
• Training machine learning potentials based on high-level reference energies for diverse molecular geometries.
• Studying potential energy surfaces based on geometries sampled at varying separation distances.
• Comparing the performance of different basis sets (STO-3G to cc-pV5Z) for non-covalent interaction calculations.

Strengths

• Extends the original S66x8 dataset from eight to one hundred geometries per complex.
• Geometries are systematically sampled at specific separation distances relative to equilibrium, from 0.7r_e to 100.0r_e.
• Energies are computed using a standardized computational chemistry package (Psi4) at defined theory levels and five basis sets.

Limitations

• Row count and dataset size are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

Stanford University (Søren Holm), extending work by Goerigk, Kruse, and Grimme.

Collection Method

Computational generation using the Psi4 quantum chemistry package.