NablaDFT: Large-Scale Conformational Energy and Hamiltonian Benchmark

NablaDFT provides conformational energy and Hamiltonian matrix data for quantum chemistry research, developed by the AIRI-Institute. Updated in December 2025, it serves as a large-scale benchmark for Density Functional Theory (DFT) calculations.

Use Cases

• Predicting conformational energy for molecular geometry optimization
• Learning Hamiltonian matrix representations for quantum property prediction
• Evaluating the accuracy of machine learning force fields against DFT benchmarks

Strengths

• Provides Hamiltonian matrices for fundamental quantum modeling
• Large-scale benchmark scope for molecular conformation tasks
• MIT license allows for unrestricted academic and commercial use

Limitations

• Metadata does not specify the exact number of molecular records
• Requires significant computational domain knowledge to utilize Hamiltonian features

Provenance

Source

AIRI-Institute

Collection Method

synthetic

Freshness

Last updated December 2025.