mat-db-mp

You query crystal structures and properties from the Materials Project by searching with a chemical system or formula, applying filters like energy above hull, and exporting the requested values and structure content as JSON outputs.

Yes, you can retrieve elasticity and magnetism datasets by pulling bulk and shear moduli, full elastic tensors, magnetic ordering, and magnetic moments with optional property-range filters for inorganic crystals.

The best way to find structurally similar materials is using CrystalNN-based fingerprinting, which calculates and returns ranked dissimilarity scores for exploration across different chemical systems.

Yes, you need an authenticated MP_API_KEY to access Materials Project data and retrieve candidate inorganic crystals and their computed properties for materials discovery workflows.

Yes, it works with ASE and pymatgen to filter stable inorganic crystals by querying selectable summary and thermo endpoints for targeted stability metrics and computed properties.

CrystalNN-based similarity search is limited to ranking structural dissimilarity scores and requires optional post-filtering by chemical system, meaning it does not directly compute properties or guarantee structural uniqueness.