Phase Identification
Overview
Automatically match your experimental diffraction pattern against crystallographic reference databases. MatPilot searches both the Crystallography Open Database (COD) API and a curated local database to identify crystalline phases present in your sample.
Scientific Background
Phase identification in XRD relies on matching the observed peak positions and relative intensities against reference patterns from known crystalline materials. Each crystal structure produces a unique diffraction fingerprint determined by its unit cell dimensions, space group, and atomic positions. MatPilot uses multiple similarity metrics including cosine similarity, figure of merit (FOM), and RMSE of peak positions to rank candidate phases.
Workflow
Run the analysis pipeline to detect peaks from your experimental pattern
Configure search parameters: query text, element constraints, database selection
Search the COD API for formula or element matches across 500,000+ structures
Query the local reference database for common materials
Generate theoretical diffraction patterns from CIF crystal data using pymatgen
Compare theoretical patterns against experimental data using cosine similarity
Rank candidates by match score, confidence, and number of matched peaks