pymatgen

pymatgen

Overview

pymatgen is the standard Python library for materials science computation. Its core data model — Structure (periodic crystalline materials) and Molecule (non-periodic) — provides a unified representation for input/output across 30+ file formats (CIF, POSCAR/CONTCAR, XYZ, PDB, Gaussian, VASP). The library integrates with the Materials Project REST API (mp_api) to retrieve 150,000+ DFT-computed structures with band gaps, formation energies, and elastic constants. pymatgen is the foundation of the atomate2 and Custodian workflow frameworks for high-throughput DFT.

When to Use

• Parsing and converting crystal structure files between CIF, POSCAR, XYZ, and other formats
• Querying the Materials Project API for computed band gaps, formation energies, and stability data
• Constructing and analyzing phase diagrams and Pourbaix diagrams for thermodynamic stability
• Generating VASP, Quantum ESPRESSO, or CP2K input files from structure objects
• Computing X-ray diffraction (XRD) and neutron diffraction patterns for comparison with experiment
• Analyzing symmetry, space groups, and Wyckoff positions of crystal structures
• Use ASE when running molecular dynamics or interfacing with multiple MD/DFT codes via a unified runner

Prerequisites

• Python packages: pymatgen, mp-api (Materials Project client)
• Data requirements: structure files (CIF, POSCAR) or Materials Project API key
• API key: free at materialsproject.org — set PMG_MAPI_KEY env var

pip install pymatgen mp-api
# Set API key
export PMG_MAPI_KEY="your_api_key_here"
# Or via pymatgen config
python -c "from pymatgen.core import SETTINGS; SETTINGS['PMG_MAPI_KEY'] = 'your_key'"

Quick Start

from pymatgen.core import Structure, Lattice, Species

# Build silicon diamond cubic structure from scratch
a = 5.431  # Angstroms
lattice = Lattice.cubic(a)
silicon = Structure(
    lattice=lattice,
    species=["Si", "Si"],
    coords=[[0, 0, 0], [0.25, 0.25, 0.25]],
)
print(f"Silicon: {silicon.formula}, {silicon.volume:.2f} ų")
print(f"Space group: {silicon.get_space_group_info()}")
# Silicon: Si2, 40.89 ų
# Space group: ('Fd-3m', 227)

Core API

Module 1: Structure and Lattice

Core data structures for periodic crystals.

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

# From lattice parameters
lattice = Lattice.from_parameters(a=4.05, b=4.05, c=4.05,
                                   alpha=90, beta=90, gamma=90)

# Build FCC aluminum
al_fcc = Structure(lattice, ["Al", "Al", "Al", "Al"],
                   [[0, 0, 0], [0.5, 0.5, 0], [0.5, 0, 0.5], [0, 0.5, 0.5]])

print(f"Formula: {al_fcc.formula}")
print(f"Sites: {len(al_fcc)}")
print(f"Volume: {al_fcc.volume:.3f} ų")
print(f"Density: {al_fcc.density:.3f} g/cm³")

# Access sites
for site in al_fcc:
    print(f"  {site.species_string} at {site.frac_coords}")

# Load from file
from pymatgen.core import Structure

# From CIF (most common exchange format)
struct = Structure.from_file("material.cif")

# From POSCAR (VASP format)
struct_vasp = Structure.from_file("POSCAR")

# Get neighbors within cutoff
site = struct[0]
neighbors = struct.get_neighbors(site, r=3.0)
print(f"Neighbors within 3 Å: {len(neighbors)}")
for nn in neighbors[:3]:
    print(f"  {nn.species_string}: {nn.nn_distance:.3f} Å")

Module 2: Materials Project API Query

Retrieve DFT-computed properties for 150,000+ materials.

from mp_api.client import MPRester
import os

api_key = os.environ.get("PMG_MAPI_KEY", "your_key")

with MPRester(api_key) as mpr:
    # Search by chemical system
    docs = mpr.materials.summary.search(
        chemsys=["Li-Fe-O"],
        fields=["material_id", "formula_pretty", "energy_above_hull",
                "band_gap", "is_stable"]
    )
    print(f"Li-Fe-O materials: {len(docs)}")
    for d in docs[:5]:
        print(f"  {d.material_id}: {d.formula_pretty}, "
              f"Eg={d.band_gap:.2f} eV, above_hull={d.energy_above_hull:.3f} eV/atom")

# Get specific material by MP ID
with MPRester(api_key) as mpr:
    doc = mpr.materials.summary.get_data_by_id(
        "mp-149",  # Silicon
        fields=["structure", "band_gap", "formation_energy_per_atom",
                "density", "is_stable", "symmetry"]
    )
    struct = doc.structure
    print(f"Si mp-149: band_gap={doc.band_gap:.3f} eV, "
          f"density={doc.density:.3f} g/cm³")
    print(f"Space group: {doc.symmetry.symbol}")

Module 3: Symmetry Analysis

from pymatgen.symmetry.analyzer import SpacegroupAnalyzer
from pymatgen.core import Structure

struct = Structure.from_file("material.cif")

# Symmetry analysis
sga = SpacegroupAnalyzer(struct, symprec=0.1)

print(f"Space group: {sga.get_space_group_symbol()} ({sga.get_space_group_number()})")
print(f"Crystal system: {sga.get_crystal_system()}")
print(f"Point group: {sga.get_point_group_symbol()}")

# Get conventional / primitive cell
primitive = sga.get_primitive_standard_structure()
conventional = sga.get_conventional_standard_structure()
print(f"Primitive: {len(primitive)} sites | Conventional: {len(conventional)} sites")

# Wyckoff positions
sym_dataset = sga.get_symmetry_dataset()
print(f"Wyckoff letters: {set(sym_dataset['wyckoffs'])}")

Module 4: Phase Diagrams

Thermodynamic stability and phase boundary analysis.

from pymatgen.analysis.phase_diagram import PhaseDiagram, PDPlotter
from mp_api.client import MPRester
import os

api_key = os.environ.get("PMG_MAPI_KEY", "your_key")

with MPRester(api_key) as mpr:
    # Get all entries in the Li-Fe-P-O chemical system
    entries = mpr.get_pourbaix_entries(["Li", "Fe"])

# For phase diagram, use computed entries
with MPRester(api_key) as mpr:
    entries = mpr.get_entries_in_chemsys(["Li", "Fe", "O"])

pd = PhaseDiagram(entries)
print(f"Stable phases: {len(pd.stable_entries)}")

# Check stability of a specific composition
from pymatgen.core import Composition
comp = Composition("LiFeO2")
e_hull = pd.get_e_above_hull(pd.qhull_entries[0])
print(f"E above hull: {e_hull:.3f} eV/atom")

# Plot (requires matplotlib)
plotter = PDPlotter(pd, backend="matplotlib")
plotter.show()

Module 5: XRD Pattern Simulation

from pymatgen.analysis.diffraction.xrd import XRDCalculator
from pymatgen.core import Structure
import matplotlib.pyplot as plt

struct = Structure.from_file("material.cif")  # or build programmatically

# Calculate XRD pattern (Cu Kα radiation, λ = 1.5406 Å)
calculator = XRDCalculator(wavelength="CuKa")
pattern = calculator.get_pattern(struct, two_theta_range=(10, 80))

print(f"Diffraction peaks: {len(pattern.x)}")
for two_theta, intensity, hkl in zip(pattern.x[:5], pattern.y[:5], pattern.hkls[:5]):
    print(f"  2θ={two_theta:.2f}°, I={intensity:.1f}, hkl={hkl}")

# Plot
fig, ax = plt.subplots(figsize=(10, 4))
ax.bar(pattern.x, pattern.y, width=0.3, color="black")
ax.set_xlabel("2θ (degrees)")
ax.set_ylabel("Intensity (arb. units)")
ax.set_title(f"XRD Pattern — {struct.formula}")
plt.tight_layout()
plt.savefig("xrd_pattern.pdf", bbox_inches="tight")

Module 6: DFT Input File Generation

Generate VASP input sets for DFT calculations.

from pymatgen.io.vasp.sets import MPRelaxSet, MPStaticSet
from pymatgen.core import Structure

struct = Structure.from_file("material.cif")

# Generate VASP relaxation input set (Materials Project standard)
relax_set = MPRelaxSet(struct)

# Write to directory
import os
os.makedirs("vasp_relax", exist_ok=True)
relax_set.write_input("vasp_relax")
print("Generated: POSCAR, INCAR, KPOINTS, POTCAR (requires VASP pseudopotentials)")

# Inspect key INCAR settings
incar = relax_set.incar
print(f"ENCUT: {incar.get('ENCUT')} eV")
print(f"KPOINTS: {relax_set.kpoints}")

# For static calculation after relaxation
static_set = MPStaticSet.from_prev_calc(prev_calc_dir="vasp_relax")
static_set.write_i