---

name: materials-database-querier description: Materials database query skill for accessing structure and property data from multiple repositories allowed-tools:

• Read
• Write
• Glob
• Grep
• Bash metadata: specialization: nanotechnology domain: science category: computational priority: high phase: 6 tools-libraries:
  • pymatgen
  • Materials Project API
  • AFLOW REST API graph: domains: [domain:nanotechnology] skillAreas: [skill-area:mathematical-reasoning, skill-area:physics-simulation, skill-area:data-analysis] workflows: [workflow:experiment-design] roles: [role:research-engineer]

---

Materials Database Querier

Purpose

The Materials Database Querier skill provides unified access to multiple materials databases for structure and property retrieval, enabling comprehensive materials search and data aggregation across repositories.

Capabilities

• Materials Project API integration
• AFLOW database queries
• ICSD/CSD structure retrieval
• NOMAD repository access
• Cross-database searches
• Property aggregation and comparison

Usage Guidelines

Database Query Workflow

1. Query Design

   • Define search criteria
   • Select target databases
   • Set property filters

2. Data Retrieval

   • Execute queries
   • Handle pagination
   • Aggregate results

3. Data Processing

   • Standardize formats
   • Compare across sources
   • Export for analysis

Process Integration

• Machine Learning Materials Discovery Pipeline
• DFT Calculation Pipeline for Nanomaterials
• Structure-Property Correlation Analysis

Input Schema

{
  "query_type": "composition|structure|property",
  "databases": ["materials_project", "aflow", "icsd"],
  "criteria": {
    "elements": ["string"],
    "property_range": {"property": "string", "min": "number", "max": "number"}
  },
  "limit": "number"
}

Output Schema

{
  "materials": [{
    "id": "string",
    "formula": "string",
    "structure_file": "string",
    "properties": {
      "bandgap": "number",
      "formation_energy": "number"
    },
    "source": "string"
  }],
  "total_found": "number",
  "query_metadata": {
    "databases_searched": ["string"],
    "query_time": "number"
  }
}