pymatgen

name	pymatgen
description	Materials science toolkit. Crystal structures (CIF, POSCAR), phase diagrams, band structure, DOS, Materials Project integration, format conversion, for computational materials science.

Pymatgen - Python Materials Genomics

Overview

Pymatgen is a comprehensive Python library for materials analysis that powers the Materials Project. Create, analyze, and manipulate crystal structures and molecules, compute phase diagrams and thermodynamic properties, analyze electronic structure (band structures, DOS), generate surfaces and interfaces, and access Materials Project's database of computed materials. Supports 100+ file formats from various computational codes.

When to Use This Skill

This skill should be used when:

• Working with crystal structures or molecular systems in materials science
• Converting between structure file formats (CIF, POSCAR, XYZ, etc.)
• Analyzing symmetry, space groups, or coordination environments
• Computing phase diagrams or assessing thermodynamic stability
• Analyzing electronic structure data (band gaps, DOS, band structures)
• Generating surfaces, slabs, or studying interfaces
• Accessing the Materials Project database programmatically
• Setting up high-throughput computational workflows
• Analyzing diffusion, magnetism, or mechanical properties
• Working with VASP, Gaussian, Quantum ESPRESSO, or other computational codes

Quick Start Guide

Installation

# Core pymatgen
uv pip install pymatgen

# With Materials Project API access
uv pip install pymatgen mp-api

# Optional dependencies for extended functionality
uv pip install pymatgen[analysis]  # Additional analysis tools
uv pip install pymatgen[vis]       # Visualization tools

Basic Structure Operations

from pymatgen.core import Structure, Lattice

# Read structure from file (automatic format detection)
struct = Structure.from_file("POSCAR")

# Create structure from scratch
lattice = Lattice.cubic(3.84)
struct = Structure(lattice, ["Si", "Si"], [[0,0,0], [0.25,0.25,0.25]])

# Write to different format
struct.to(filename="structure.cif")

# Basic properties
print(f"Formula: {struct.composition.reduced_formula}")
print(f"Space group: {struct.get_space_group_info()}")
print(f"Density: {struct.density:.2f} g/cm³")

Materials Project Integration

# Set up API key
export MP_API_KEY="your_api_key_here"

from mp_api.client import MPRester

with MPRester() as mpr:
    # Get structure by material ID
    struct = mpr.get_structure_by_material_id("mp-149")

    # Search for materials
    materials = mpr.materials.summary.search(
        formula="Fe2O3",
        energy_above_hull=(0, 0.05)
    )

Core Capabilities

1. Structure Creation and Manipulation

Create structures using various methods and perform transformations.

From files:

# Automatic format detection
struct = Structure.from_file("structure.cif")
struct = Structure.from_file("POSCAR")
mol = Molecule.from_file("molecule.xyz")

From scratch:

from pymatgen.core import Structure, Lattice

# Using lattice parameters
lattice = Lattice.from_parameters(a=3.84, b=3.84, c=3.84,
                                  alpha=120, beta=90, gamma=60)
coords = [[0, 0, 0], [0.75, 0.5, 0.75]]
struct = Structure(lattice, ["Si", "Si"], coords)

# From space group
struct = Structure.from_spacegroup(
    "Fm-3m",
    Lattice.cubic(3.5),
    ["Si"],
    [[0, 0, 0]]
)

Transformations:

from pymatgen.transformations.standard_transformations import (
    SupercellTransformation,
    SubstitutionTransformation,
    PrimitiveCellTransformation
)

# Create supercell
trans = SupercellTransformation([[2,0,0],[0,2,0],[0,0,2]])
supercell = trans.apply_transformation(struct)

# Substitute elements
trans = SubstitutionTransformation({"Fe": "Mn"})
new_struct = trans.apply_transformation(struct)

# Get primitive cell
trans = PrimitiveCellTransformation()
primitive = trans.apply_transformation(struct)

Reference: See references/core_classes.md for comprehensive documentation of Structure, Lattice, Molecule, and related classes.

2. File Format Conversion

Convert between 100+ file formats with automatic format detection.

Using convenience methods:

# Read any format
struct = Structure.from_file("input_file")

# Write to any format
struct.to(filename="output.cif")
struct.to(filename="POSCAR")
struct.to(filename="output.xyz")

Using the conversion script:

# Single file conversion
python scripts/structure_converter.py POSCAR structure.cif

# Batch conversion
python scripts/structure_converter.py *.cif --output-dir ./poscar_files --format poscar

Reference: See references/io_formats.md for detailed documentation of all supported formats and code integrations.

3. Structure Analysis and Symmetry

Analyze structures for symmetry, coordination, and other properties.

Symmetry analysis:

from pymatgen.symmetry.analyzer import SpacegroupAnalyzer

sga = SpacegroupAnalyzer(struct)

# Get space group information
print(f"Space group: {sga.get_space_group_symbol()}")
print(f"Number: {sga.get_space_group_number()}")
print(f"Crystal system: {sga.get_crystal_system()}")

# Get conventional/primitive cells
conventional = sga.get_conventional_standard_structure()
primitive = sga.get_primitive_standard_structure()

Coordination environment:

from pymatgen.analysis.local_env import CrystalNN

cnn = CrystalNN()
neighbors = cnn.get_nn_info(struct, n=0)  # Neighbors of site 0

print(f"Coordination number: {len(neighbors)}")
for neighbor in neighbors:
    site = struct[neighbor['site_index']]
    print(f"  {site.species_string} at {neighbor['weight']:.3f} Å")

Using the analysis script:

# Comprehensive analysis
python scripts/structure_analyzer.py POSCAR --symmetry --neighbors

# Export results
python scripts/structure_analyzer.py structure.cif --symmetry --export json

Reference: See references/analysis_modules.md for detailed documentation of all analysis capabilities.

4. Phase Diagrams and Thermodynamics

Construct phase diagrams and analyze thermodynamic stability.

Phase diagram construction:

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

# Get entries from Materials Project
with MPRester() as mpr:
    entries = mpr.get_entries_in_chemsys("Li-Fe-O")

# Build phase diagram
pd = PhaseDiagram(entries)

# Check stability
from pymatgen.core import Composition
comp = Composition("LiFeO2")

# Find entry for composition
for entry in entries:
    if entry.composition.reduced_formula == comp.reduced_formula:
        e_above_hull = pd.get_e_above_hull(entry)
        print(f"Energy above hull: {e_above_hull:.4f} eV/atom")

        if e_above_hull > 0.001:
            # Get decomposition
            decomp = pd.get_decomposition(comp)
            print("Decomposes to:", decomp)

# Plot
plotter = PDPlotter(pd)
plotter.show()

Using the phase diagram script:

# Generate phase diagram
python scripts/phase_diagram_generator.py Li-Fe-O --output li_fe_o.png

# Analyze specific composition
python scripts/phase_diagram_generator.py Li-Fe-O --analyze "LiFeO2" --show

Reference: See references/analysis_modules.md (Phase Diagrams section) and references/transformations_workflows.md (Workflow 2) for detailed examples.

5. Electronic Structure Analysis

Analyze band structures, density of states, and electronic properties.

Band structure:

from pymatgen.io.vasp import Vasprun
from pymatgen.electronic_structure.plotter import BSPlotter

# Read from VASP calculation
vasprun = Vasprun("vasprun.xml")
bs = vasprun.get_band_structure()

# Analyze
band_gap = bs.get_band_gap()
print(f"Band gap: {band_gap['energy']:.3f} eV")
print(f"Direct: {band_gap['direct']}")
print(f"Is metal: {bs.is_metal()}")

# Plot
plotter = BSPlotter(bs)
plotter.save_plot("band_structure.png")

Density of states:

from pymatgen.electronic_structure.plotter import DosPlotter

dos = vasprun.complete_dos

# Get element-projected DOS
element_dos = dos.get_element_dos()
for element, element_dos_obj in element_dos.items():
    print(f"{element}: {element_dos_obj.get_gap():.3f} eV")

# Plot
plotter = DosPlotter()
plotter.add_dos("Total DOS", dos)
plotter.show()

Reference: See references/analysis_modules.md (Electronic Structure section) and references/io_formats.md (VASP section).

6. Surface and Interface Analysis

Generate slabs, analyze surfaces, and study interfaces.

Slab generation:

from pymatgen.core.surface import SlabGenerator

# Generate slabs for specific Miller index
slabgen = SlabGenerator(
    struct,
    miller_index=(1, 1, 1),
    min_slab_size=10.0,      # Å
    min_vacuum_size=10.0,    # Å
    center_slab=True
)

slabs = slabgen.get_slabs()

# Write slabs
for i, slab in enumerate(slabs):
    slab.to(filename=f"slab_{i}.cif")

Wulff shape construction:

from pymatgen.analysis.wulff import WulffShape

# Define surface energies
surface_energies = {
    (1, 0, 0): 1.0,
    (1, 1, 0): 1.1,
    (1, 1, 1): 0.9,
}

wulff = WulffShape(struct.lattice, surface_energies)
print(f"Surface area: {wulff.surface_area:.2f} Ų")
print(f"Volume: {wulff.volume:.2f} ų")

wulff.show()

Adsorption site finding:

from pymatgen.analysis.adsorption import AdsorbateSiteFinder
from pymatgen.core import Molecule

asf = AdsorbateSiteFinder(slab)

# Find sites
ads_sites = asf.find_adsorption_sites()
print(f"On-top sites: {len(ads_sites['ontop'])}")
print(f"Bridge sites: {len(ads_sites['bridge'])}")
print(f"Hollow sites: {len(ads_sites['hollow'])}")

# Add adsorbate
adsorbate = Molecule("O", [[0, 0, 0]])
ads_struct = asf.add_adsorbate(adsorbate, ads_sites["ontop"][0])

Reference: See references/analysis_modules.md (Surface and Interface section) and references/transformations_workflows.md (Workflows 3 and 9).

7. Materials Project Database Access

Programmatically access the Materials Project database.

Setup:

1. Get API key from https://next-gen.materialsproject.org/
2. Set environment variable: export MP_API_KEY="your_key_here"

Search and retrieve:

from mp_api.client import MPRester

with MPRester() as mpr:
    # Search by formula
    materials = mpr.materials.summary.search(formula="Fe2O3")

    # Search by chemical system
    materials = mpr.materials.summary.search(chemsys="Li-Fe-O")

    # Filter by properties
    materials = mpr.materials.summary.search(
        chemsys="Li-Fe-O",
        energy_above_hull=(0, 0.05),  # Stable/metastable
        band_gap=(1.0, 3.0)            # Semiconducting
    )

    # Get structure
    struct = mpr.get_structure_by_material_id("mp-149")

    # Get band structure
    bs = mpr.get_bandstructure_by_material_id("mp-149")

    # Get entries for phase diagram
    entries = mpr.get_entries_in_chemsys("Li-Fe-O")

Reference: See references/materials_project_api.md for comprehensive API documentation and examples.

8. Computational Workflow Setup

Set up calculations for various electronic structure codes.

VASP input generation:

from pymatgen.io.vasp.sets import MPRelaxSet, MPStaticSet, MPNonSCFSet

# Relaxation
relax = MPRelaxSet(struct)
relax.write_input("./relax_calc")

# Static calculation
static = MPStaticSet(struct)
static.write_input("./static_calc")

# Band structure (non-self-consistent)
nscf = MPNonSCFSet(struct, mode="line")
nscf.write_input("./bandstructure_calc")

# Custom parameters
custom = MPRelaxSet(struct, user_incar_settings={"ENCUT": 600})
custom.write_input("./custom_calc")

Other codes:

# Gaussian
from pymatgen.io.gaussian import GaussianInput

gin = GaussianInput(
    mol,
    functional="B3LYP",
    basis_set="6-31G(d)",
    route_parameters={"Opt": None}
)
gin.write_file("input.gjf")