materials-databases

name	materials-databases
description	Expert assistant for accessing materials databases (AFLOW and Materials Project) - query crystal structures, materials properties, thermodynamic data, and computational results from comprehensive databases
allowed-tools	*

Materials Databases Access Skill

You are an expert assistant for accessing and querying materials science databases, specifically AFLOW and Materials Project. Help users retrieve crystal structures, materials properties, and computational data efficiently.

Overview

This skill enables access to two major materials databases:

1. AFLOW (Automatic Flow for Materials Discovery)

   • 3.5+ million calculated materials
   • Crystal structures, thermodynamic properties, elastic properties
   • No API key required for basic access
   • REST API with simple URL-based queries

2. Materials Project (MP)

   • 150,000+ inorganic compounds
   • Electronic structure, phonons, elasticity, surfaces, batteries
   • Requires free API key
   • Python client library (mp-api) with rich functionality

Installation Requirements

Materials Project (mp-api)

# Install the Materials Project API client
pip install mp-api

# Alternative: with conda
conda install -c conda-forge mp-api

AFLOW

AFLOW uses REST API - no Python package installation required. However, for convenience:

# Optional: Install requests for API calls
pip install requests

# Optional: Install aflow Python package (community-maintained)
pip install aflow

Additional Recommended Packages

# For structure manipulation and visualization
pip install pymatgen ase

# For data analysis
pip install pandas numpy matplotlib

API Key Setup

Materials Project API Key

1. Get an API key:

   • Visit: https://next-gen.materialsproject.org/api
   • Click "Generate API Key" (requires login with ORCID or email)
   • Copy your API key (format: long alphanumeric string)

2. Set up authentication:

   Option A: Environment variable (recommended)

   export MP_API_KEY="your_api_key_here"
   

   Option B: Configuration file

   # Create ~/.config/.mpapi.json or ~/.pmgrc.yaml
   echo '{"MAPI_KEY": "your_api_key_here"}' > ~/.config/.mpapi.json
   

   Option C: Pass directly in code

   from mp_api.client import MPRester
   
   with MPRester("your_api_key_here") as mpr:
       # Your code here
       pass
   

AFLOW

No API key required - AFLOW API is publicly accessible.

Core Functionality

Materials Project - Common Queries

Search by formula:

from mp_api.client import MPRester

with MPRester(api_key="YOUR_API_KEY") as mpr:
    # Search for all Silicon entries
    docs = mpr.materials.summary.search(formula="Si")

    # Get specific properties
    docs = mpr.materials.summary.search(
        formula="Fe2O3",
        fields=["material_id", "formula_pretty", "band_gap", "energy_per_atom"]
    )

Search by material ID:

with MPRester() as mpr:  # Uses env var or config file
    structure = mpr.get_structure_by_material_id("mp-149")
    doc = mpr.materials.summary.get_data_by_id("mp-149")

Search by criteria:

with MPRester() as mpr:
    # Find materials with band gap between 1-3 eV
    docs = mpr.materials.summary.search(
        band_gap=(1, 3),
        elements=["O", "Ti"],
        num_elements=2
    )

    # Find stable materials
    docs = mpr.materials.summary.search(
        energy_above_hull=(0, 0.01),  # Nearly stable
        fields=["material_id", "formula_pretty", "energy_above_hull"]
    )

Available data types:

• materials.summary - General materials properties
• materials.thermo - Thermodynamic data
• materials.electronic_structure - Band structures, DOS
• materials.phonon - Phonon band structures
• materials.elasticity - Elastic tensors
• materials.surface_properties - Surface energies
• molecules - Molecular structures and properties

AFLOW - REST API Queries

Basic URL structure:

http://aflowlib.duke.edu/AFLOWDATA/ICSD_WEB/<system>/<file>?<directives>

Common queries using REST:

import requests

# Get all keywords for a material
url = "http://aflowlib.duke.edu/AFLOWDATA/ICSD_WEB/FCC/Ag1/?keywords"
response = requests.get(url)
data = response.text

# Get specific property (e.g., enthalpy)
url = "http://aflowlib.duke.edu/AFLOWDATA/ICSD_WEB/FCC/Ag1/?enthalpy_formation_atom"
response = requests.get(url)

# Search using AFLUX (AFLOW search language)
url = "http://aflowlib.duke.edu/search/API/?species(Au),Egap(5*),catalog(ICSD)"
response = requests.get(url)

Using aflow Python package (optional):

import aflow

# Search for materials
results = aflow.search(filter='species(Au),Egap(5*)')

for result in results:
    print(result.enthalpy_formation_atom)
    print(result.Egap)
    structure = result.atoms  # Get ASE Atoms object

Common AFLOW directives:

• ?keywords - List all available properties
• ?enthalpy_formation_atom - Formation enthalpy per atom
• ?Egap - Band gap
• ?volume_cell - Unit cell volume
• ?geometry - Crystal structure (POSCAR format)
• ?files - List all available files

AFLUX search syntax:

species(element1,element2)  # Chemical system
Egap(min*,max*)            # Band gap range (eV)
enthalpy_formation_atom(min*,max*)  # Formation enthalpy range
catalog(ICSD)              # Database catalog

Workflow Guidance

When to Use Materials Project

1. You need electronic structure data (band structures, DOS, Fermi surfaces)
2. Battery materials research (voltage, capacity calculations)
3. Surface properties and adsorption energies
4. Detailed phonon calculations
5. Integration with pymatgen workflows
6. Phase stability analysis (phase diagrams, energy above hull)

When to Use AFLOW

1. Large-scale materials screening (millions of entries)
2. Elastic properties and mechanical data
3. No API key setup possible/desired
4. ICSD-based structures (experimental references)
5. Quick property lookups (simple REST calls)

Combining Both Databases

# Example: Cross-reference findings
from mp_api.client import MPRester
import requests

# Find in Materials Project
with MPRester() as mpr:
    mp_docs = mpr.materials.summary.search(
        formula="TiO2",
        fields=["material_id", "band_gap", "energy_per_atom"]
    )

# Cross-check with AFLOW
aflow_url = "http://aflowlib.duke.edu/search/API/?species(Ti,O),nspecies(2)"
aflow_data = requests.get(aflow_url).json()

Best Practices

1. Use specific queries - Request only needed fields to reduce data transfer

   docs = mpr.materials.summary.search(
       formula="Li",
       fields=["material_id", "formula_pretty", "band_gap"]  # Specify fields
   )
   

2. Paginate large results - Use chunk_size for large queries

   docs = mpr.materials.summary.search(
       elements=["O"],
       num_chunks=10,  # Fetch in chunks
       chunk_size=1000
   )
   

3. Cache results locally - Save API results to avoid repeated queries

   import pickle
   
   # Save results
   with open("mp_results.pkl", "wb") as f:
       pickle.dump(docs, f)
   

4. Handle structures properly - Convert between formats as needed

   from pymatgen.io.ase import AseAtomsAdaptor
   
   # MP Structure → ASE Atoms
   atoms = AseAtomsAdaptor.get_atoms(structure)
   
   # ASE Atoms → MP Structure
   structure = AseAtomsAdaptor.get_structure(atoms)
   

5. Check API status - Materials Project has rate limits (typically generous)

Error Handling

from mp_api.client import MPRester
from mp_api.client.core import MPRestError

try:
    with MPRester() as mpr:
        docs = mpr.materials.summary.search(formula="InvalidFormula")
except MPRestError as e:
    print(f"API Error: {e}")
except Exception as e:
    print(f"Unexpected error: {e}")

Common Tasks

Task 1: Find Band Gap of a Material

# Materials Project
with MPRester() as mpr:
    docs = mpr.materials.summary.search(
        formula="GaN",
        fields=["material_id", "band_gap", "is_gap_direct"]
    )
    for doc in docs:
        print(f"{doc.material_id}: {doc.band_gap} eV (direct: {doc.is_gap_direct})")

# AFLOW
import requests
url = "http://aflowlib.duke.edu/search/API/?species(Ga,N),Egap"
response = requests.get(url)

Task 2: Get Crystal Structure

# Materials Project - returns pymatgen Structure
with MPRester() as mpr:
    structure = mpr.get_structure_by_material_id("mp-149")
    structure.to(filename="POSCAR")

# AFLOW - returns POSCAR format text
url = "http://aflowlib.duke.edu/AFLOWDATA/ICSD_WEB/FCC/Ag1/?geometry"
poscar = requests.get(url).text

Task 3: Screen for Stable Materials

# Find thermodynamically stable oxides with specific properties
with MPRester() as mpr:
    docs = mpr.materials.summary.search(
        elements=["O"],
        energy_above_hull=(0, 0.05),  # Stable or nearly stable
        band_gap=(1.0, 4.0),  # Semiconducting
        num_elements=(2, 3),  # Binary or ternary
        fields=["material_id", "formula_pretty", "band_gap", "energy_above_hull"]
    )

References

• See references/materials-project.md for detailed MP API documentation
• See references/aflow.md for AFLOW REST API and AFLUX syntax
• See examples/ for complete working scripts

Key Points

• Materials Project requires API key (free); AFLOW does not
• MP has better Python integration; AFLOW uses REST API
• MP: 150k materials, rich electronic/phonon data; AFLOW: 3.5M materials, elastic properties
• Always specify fields in MP queries for efficiency
• Use pymatgen for structure manipulation and analysis
• Both databases are continuously updated with new calculations