Chapter 5: Practical Crystallographic Computing with pymatgen

From Materials Project Integration to Practical Workflows

📖 Reading Time: 30-36 minutes 📊 Difficulty: Intermediate 💻 Code Examples: 8 📝 Exercises: 0

🌐 EN | 🇯🇵 JP | Last sync: 2025-11-16

AI Terakoya Top > MS Dojo > Introduction to Crystallography > Chapter 5

Learning Objectives

By completing this final chapter, you will acquire the following practical skills:

1. Overview of pymatgen and Environment Setup

1.1 What is pymatgen?

pymatgen (Python Materials Genomics) is a comprehensive Python library for materials science. Developed by the MIT Materials Project research group, it is widely used in crystal structure analysis, first-principles calculations, and Materials Informatics research.

Key Features of pymatgen

1.2 Installation and Setup

Installation Procedure

# Execute in terminal/command prompt
# Basic installation
pip install pymatgen

# For Materials Project API integration (recommended)
pip install mp-api

# Install visualization libraries together
pip install matplotlib numpy scipy plotly

# Verify installation
python -c "import pymatgen; print(pymatgen.__version__)"
# Example output: 2024.10.3

Obtaining a Materials Project API Key

To access the Materials Project database, you need a free API key:

  1. Visit the Materials Project official site
  2. Create a free account via “Sign Up” in the upper right
  3. After logging in, navigate to the “API” section
  4. Click “Generate API Key” to create a new API key
  5. Copy the displayed API key (e.g., abc123xyz...)
  6. Set it as an environment variable or use in your script

Security Note : Your API key is confidential information. Do not commit it to GitHub or other repositories.

2. Basic Operations with Structure Objects

2.1 Creating Crystal Structures and Retrieving Information

Code Example 1: Basic Structure Object Operations

Create the diamond structure of silicon (Si) and retrieve basic information:

from pymatgen.core import Structure, Lattice
import numpy as np

# Create silicon with diamond structure
# Define lattice vectors (cubic, a = 5.43 Å)
a = 5.43
lattice = Lattice.cubic(a)

# Atom species and fractional coordinates
species = ['Si'] * 8
coords = [
    [0.00, 0.00, 0.00],  # FCC lattice points
    [0.50, 0.50, 0.00],
    [0.50, 0.00, 0.50],
    [0.00, 0.50, 0.50],
    [0.25, 0.25, 0.25],  # Tetrahedral interstices
    [0.75, 0.75, 0.25],
    [0.75, 0.25, 0.75],
    [0.25, 0.75, 0.75]
]

# Create Structure object
si_structure = Structure(lattice, species, coords)

print("=== Silicon (Si) Crystal Structure Information ===\n")

# Retrieve basic information
print(f"Composition: {si_structure.composition}")
print(f"Formula: {si_structure.formula}")
print(f"Unit cell volume: {si_structure.volume:.4f} ų")
print(f"Density: {si_structure.density:.4f} g/cm³")
print(f"Number of atoms: {len(si_structure)}")

# Retrieve lattice parameters
print(f"\nLattice parameters:")
print(f"  a = {si_structure.lattice.a:.4f} Å")
print(f"  b = {si_structure.lattice.b:.4f} Å")
print(f"  c = {si_structure.lattice.c:.4f} Å")
print(f"  α = {si_structure.lattice.alpha:.2f}°")
print(f"  β = {si_structure.lattice.beta:.2f}°")
print(f"  γ = {si_structure.lattice.gamma:.2f}°")

# Information for each atom
print(f"\nAtomic coordinates:")
print(f"{'Atom':<8} {'Fractional coords (x, y, z)':<30} {'Cartesian coords (Å)':<25}")
print("-" * 65)

for i, site in enumerate(si_structure):
    species = site.species_string
    frac_coords = site.frac_coords
    cart_coords = site.coords

    print(f"{species:<8} ({frac_coords[0]:6.3f}, {frac_coords[1]:6.3f}, {frac_coords[2]:6.3f})    "
          f"({cart_coords[0]:6.3f}, {cart_coords[1]:6.3f}, {cart_coords[2]:6.3f})")

# Nearest neighbor distances
print(f"\nNearest neighbor distances:")
neighbors = si_structure.get_neighbors(si_structure[0], 3.0)
for neighbor, distance in neighbors:
    print(f"  {distance:.4f} Å")

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