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pymatgen

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

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SKILL.md
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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} Ã…")

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, # Ã… min_vacuum_size=10.0, # Ã… 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") # Quantum ESPRESSO from pymatgen.io.pwscf import PWInput pwin = PWInput(struct, control={"calculation": "scf"}) pwin.write_file("pw.in")

Reference: See references/io_formats.md (Electronic Structure Code I/O section) and references/transformations_workflows.md for workflow examples.

9. Advanced Analysis

Diffraction patterns:

from pymatgen.analysis.diffraction.xrd import XRDCalculator xrd = XRDCalculator() pattern = xrd.get_pattern(struct) # Get peaks for peak in pattern.hkls: print(f"2θ = {peak['2theta']:.2f}°, hkl = {peak['hkl']}") pattern.plot()

Elastic properties:

from pymatgen.analysis.elasticity import ElasticTensor # From elastic tensor matrix elastic_tensor = ElasticTensor.from_voigt(matrix) print(f"Bulk modulus: {elastic_tensor.k_voigt:.1f} GPa") print(f"Shear modulus: {elastic_tensor.g_voigt:.1f} GPa") print(f"Young's modulus: {elastic_tensor.y_mod:.1f} GPa")

Magnetic ordering:

from pymatgen.transformations.advanced_transformations import MagOrderingTransformation # Enumerate magnetic orderings trans = MagOrderingTransformation({"Fe": 5.0}) mag_structs = trans.apply_transformation(struct, return_ranked_list=True) # Get lowest energy magnetic structure lowest_energy_struct = mag_structs[0]['structure']

Reference: See references/analysis_modules.md for comprehensive analysis module documentation.

Bundled Resources

Scripts (scripts/)

Executable Python scripts for common tasks:

  • structure_converter.py: Convert between structure file formats

    • Supports batch conversion and automatic format detection
    • Usage: python scripts/structure_converter.py POSCAR structure.cif
  • structure_analyzer.py: Comprehensive structure analysis

    • Symmetry, coordination, lattice parameters, distance matrix
    • Usage: python scripts/structure_analyzer.py structure.cif --symmetry --neighbors
  • phase_diagram_generator.py: Generate phase diagrams from Materials Project

    • Stability analysis and thermodynamic properties
    • Usage: python scripts/phase_diagram_generator.py Li-Fe-O --analyze "LiFeO2"

All scripts include detailed help: python scripts/script_name.py --help

References (references/)

Comprehensive documentation loaded into context as needed:

  • core_classes.md: Element, Structure, Lattice, Molecule, Composition classes
  • io_formats.md: File format support and code integration (VASP, Gaussian, etc.)
  • analysis_modules.md: Phase diagrams, surfaces, electronic structure, symmetry
  • materials_project_api.md: Complete Materials Project API guide
  • transformations_workflows.md: Transformations framework and common workflows

Load references when detailed information is needed about specific modules or workflows.

Common Workflows

High-Throughput Structure Generation

from pymatgen.transformations.standard_transformations import SubstitutionTransformation from pymatgen.io.vasp.sets import MPRelaxSet # Generate doped structures base_struct = Structure.from_file("POSCAR") dopants = ["Mn", "Co", "Ni", "Cu"] for dopant in dopants: trans = SubstitutionTransformation({"Fe": dopant}) doped_struct = trans.apply_transformation(base_struct) # Generate VASP inputs vasp_input = MPRelaxSet(doped_struct) vasp_input.write_input(f"./calcs/Fe_{dopant}")

Band Structure Calculation Workflow

# 1. Relaxation relax = MPRelaxSet(struct) relax.write_input("./1_relax") # 2. Static (after relaxation) relaxed = Structure.from_file("1_relax/CONTCAR") static = MPStaticSet(relaxed) static.write_input("./2_static") # 3. Band structure (non-self-consistent) nscf = MPNonSCFSet(relaxed, mode="line") nscf.write_input("./3_bandstructure") # 4. Analysis from pymatgen.io.vasp import Vasprun vasprun = Vasprun("3_bandstructure/vasprun.xml") bs = vasprun.get_band_structure() bs.get_band_gap()

Surface Energy Calculation

# 1. Get bulk energy bulk_vasprun = Vasprun("bulk/vasprun.xml") bulk_E_per_atom = bulk_vasprun.final_energy / len(bulk) # 2. Generate and calculate slabs slabgen = SlabGenerator(bulk, (1,1,1), 10, 15) slab = slabgen.get_slabs()[0] MPRelaxSet(slab).write_input("./slab_calc") # 3. Calculate surface energy (after calculation) slab_vasprun = Vasprun("slab_calc/vasprun.xml") E_surf = (slab_vasprun.final_energy - len(slab) * bulk_E_per_atom) / (2 * slab.surface_area) E_surf *= 16.021766 # Convert eV/Ų to J/m²

More workflows: See references/transformations_workflows.md for 10 detailed workflow examples.

Best Practices

Structure Handling

  1. Use automatic format detection: Structure.from_file() handles most formats
  2. Prefer immutable structures: Use IStructure when structure shouldn't change
  3. Check symmetry: Use SpacegroupAnalyzer to reduce to primitive cell
  4. Validate structures: Check for overlapping atoms or unreasonable bond lengths

File I/O

  1. Use convenience methods: from_file() and to() are preferred
  2. Specify formats explicitly: When automatic detection fails
  3. Handle exceptions: Wrap file I/O in try-except blocks
  4. Use serialization: as_dict()/from_dict() for version-safe storage

Materials Project API

  1. Use context manager: Always use with MPRester() as mpr:
  2. Batch queries: Request multiple items at once
  3. Cache results: Save frequently used data locally
  4. Filter effectively: Use property filters to reduce data transfer

Computational Workflows

  1. Use input sets: Prefer MPRelaxSet, MPStaticSet over manual INCAR
  2. Check convergence: Always verify calculations converged
  3. Track transformations: Use TransformedStructure for provenance
  4. Organize calculations: Use clear directory structures

Performance

  1. Reduce symmetry: Use primitive cells when possible
  2. Limit neighbor searches: Specify reasonable cutoff radii
  3. Use appropriate methods: Different analysis tools have different speed/accuracy tradeoffs
  4. Parallelize when possible: Many operations can be parallelized

Units and Conventions

Pymatgen uses atomic units throughout:

  • Lengths: Angstroms (Ã…)
  • Energies: Electronvolts (eV)
  • Angles: Degrees (°)
  • Magnetic moments: Bohr magnetons (μB)
  • Time: Femtoseconds (fs)

Convert units using pymatgen.core.units when needed.

Integration with Other Tools

Pymatgen integrates seamlessly with:

  • ASE (Atomic Simulation Environment)
  • Phonopy (phonon calculations)
  • BoltzTraP (transport properties)
  • Atomate/Fireworks (workflow management)
  • AiiDA (provenance tracking)
  • Zeo++ (pore analysis)
  • OpenBabel (molecule conversion)

Troubleshooting

Import errors: Install missing dependencies

uv pip install pymatgen[analysis,vis]

API key not found: Set MP_API_KEY environment variable

export MP_API_KEY="your_key_here"

Structure read failures: Check file format and syntax

# Try explicit format specification struct = Structure.from_file("file.txt", fmt="cif")

Symmetry analysis fails: Structure may have numerical precision issues

# Increase tolerance from pymatgen.symmetry.analyzer import SpacegroupAnalyzer sga = SpacegroupAnalyzer(struct, symprec=0.1)

Additional Resources

Version Notes

This skill is designed for pymatgen 2024.x and later. For the Materials Project API, use the mp-api package (separate from legacy pymatgen.ext.matproj).

Requirements:

  • Python 3.10 or higher
  • pymatgen >= 2023.x
  • mp-api (for Materials Project access)
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