This meta-skill orchestrates a computational materials screening pipeline by combining database querying, property-based filtering, structural analysis, and multi-criteria ranking. It coordinates three specialized skills to systematically identify and evaluate candidate materials for target applications.
Workflow
Step 1: Database Search and Candidate Retrieval
Query the Materials Project API to build an initial candidate pool based on application-specific criteria:
- Chemical system constraints (e.g., Li-containing oxides for battery cathodes)
- Space group or crystal system requirements
- Elemental composition filters (include/exclude specific elements)
- Property range pre-filters (band gap, formation energy, density)
Retrieve structural data (CIF files), computed properties, and literature references for each candidate material.
Step 2: Property-Based Filtering
Apply quantitative property thresholds to narrow the candidate pool:
- Electronic: Band gap range for semiconductors, metals, or insulators
- Thermodynamic: Formation energy cutoffs for synthesizability
- Mechanical: Bulk/shear modulus for structural applications
- Physical: Density, volume per atom, coordination preferences
- Magnetic: Magnetic ordering for spintronic applications
Define application-specific filter chains (e.g., for photovoltaics: band gap 1.0-1.8 eV, direct gap preferred, low effective mass).
Step 3: Structure Analysis with Pymatgen
Perform detailed structural characterization on filtered candidates:
- Symmetry analysis: space group verification, site symmetries
- Bonding analysis: coordination environments, bond lengths and angles
- Defect tolerance: vacancy formation energies, anti-site energies
- Surface analysis: slab models, surface energy estimation
- Structural similarity: comparison across candidates using fingerprints
Step 4: Stability Assessment
Evaluate thermodynamic and dynamic stability of remaining candidates:
- Thermodynamic: Energy above the convex hull (Ehull < 25 meV/atom typical)
- Phase stability: Competing phases, decomposition products
- Phonon stability: Check for imaginary frequencies indicating dynamic instability
- Aqueous stability: Pourbaix diagram analysis for electrochemical applications
- Thermal stability: Estimated decomposition temperatures
Flag materials with marginal stability for experimental verification.
Step 5: Multi-Criteria Ranking and Selection
Use scipy optimization to rank candidates through weighted scoring:
- Define objective function combining normalized property values
- Apply Pareto front analysis for multi-objective screening
- Weight criteria by application importance (user-configurable)
- Calculate composite figure of merit for final ranking
- Sensitivity analysis on weight choices to assess ranking robustness
Output a ranked shortlist with property cards and selection rationale.
Integration Points
- materials-project -- Database queries, computed properties, phase diagrams, crystal structures
- pymatgen-materials -- Structure manipulation, symmetry, bonding, surface analysis, fingerprints
- scipy-analysis -- Optimization, Pareto analysis, statistical ranking, sensitivity analysis
Output Formats
- Candidate table: Formula, space group, key properties, stability metrics
- Property cards: Per-material summary with structure visualization description
- Ranking report: Ordered list with composite scores and contributing factors
- Stability summary: Ehull values, competing phases, phonon stability flags
- Comparison matrix: Side-by-side property comparison of top candidates
Best Practices
- Define the target application clearly before constructing filter chains
- Start with broad chemical systems and narrow progressively to avoid missing candidates
- Use energy above hull as a primary stability filter before detailed analysis
- Validate database-computed properties against experimental values when available
- Consider synthesizability alongside thermodynamic stability
- Apply cost and toxicity filters for practical applications
- Use multiple ranking weight schemes to test sensitivity of the final shortlist
- Cross-reference with ICSD or experimental databases for synthesis precedent
- Document all filter thresholds and ranking weights for reproducibility
- Flag materials requiring experimental validation of computed properties