Skip to content
pymatgen logo

Pymatgen - Python Materials Genomics

pymatgen

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

ljchg12-hue/dotfiles0installs1stars

SKILL.md

Full skill instructions

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
pip install pymatgen

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

# Optional dependencies for extended functionality
pip install pymatgen[analysis]  # Additional analysis tools
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")

# 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 (Å)
  • 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

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)

More skills from ljchg12-hue

labarchive-integration logo
ljchg12-hue/dotfiles

labarchive-integration

Electronic lab notebook API integration. Access notebooks, manage entries/attachments, backup notebooks, integrate with Protocols.io/Jupyter/REDCap, for programmatic ELN workflows.

1 0
View
llm-evaluation logo
ljchg12-hue/dotfiles

llm-evaluation

Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.

1 0
View
requesting-code-review logo
ljchg12-hue/dotfiles

requesting-code-review

Use when completing tasks, implementing major features, or before merging to verify work meets requirements - dispatches superpowers:code-reviewer subagent to review implementation against plan or requirements before proceeding

1 0
View
uspto-database logo
ljchg12-hue/dotfiles

uspto-database

Access USPTO APIs for patent/trademark searches, examination history (PEDS), assignments, citations, office actions, TSDR, for IP analysis and prior art searches.

1 0
View
scientific-writing logo
ljchg12-hue/dotfiles

scientific-writing

Write scientific manuscripts. IMRAD structure, citations (APA/AMA/Vancouver), figures/tables, reporting guidelines (CONSORT/STROBE/PRISMA), abstracts, for research papers and journal submissions.

1 0
View
kegg-database logo
ljchg12-hue/dotfiles

kegg-database

Direct REST API access to KEGG (academic use only). Pathway analysis, gene-pathway mapping, metabolic pathways, drug interactions, ID conversion. For Python workflows with multiple databases, prefer bioservices. Use this for direct HTTP/REST work or KEGG-specific control.

1 0
View
database-migration logo
ljchg12-hue/dotfiles

database-migration

Execute database migrations across ORMs and platforms with zero-downtime strategies, data transformation, and rollback procedures. Use when migrating databases, changing schemas, performing data transformations, or implementing zero-downtime deployment strategies.

1 0
View
internal-comms logo
ljchg12-hue/dotfiles

internal-comms

A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident ...

1 0
View
meeting-transcript-analysis logo
ljchg12-hue/dotfiles

meeting-transcript-analysis

Analyze meeting transcripts to extract action items, decisions, key points, and generate summaries

1 0
View
neurokit2 logo
ljchg12-hue/dotfiles

neurokit2

Comprehensive biosignal processing toolkit for analyzing physiological data including ECG, EEG, EDA, RSP, PPG, EMG, and EOG signals. Use this skill when processing cardiovascular signals, brain activity, electrodermal responses, respiratory patterns, muscle activity, or eye movements. Applicable ...

1 0
View
shap logo
ljchg12-hue/dotfiles

shap

Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias ...

1 0
View
sql-optimization-patterns logo
ljchg12-hue/dotfiles

sql-optimization-patterns

Master SQL query optimization, indexing strategies, and EXPLAIN analysis to dramatically improve database performance and eliminate slow queries. Use when debugging slow queries, designing database schemas, or optimizing application performance.

1 0
View

Popular AI tools

Kaiber logo
Video

Kaiber

Generate, edit, and beat-sync AI video with leading models in one workspace.

Paid
View
Vimcal logo
Productivity

Vimcal

The world's fastest calendar for remote work

Free
View

Transform Your Design with AI Designer by ImgCreator.ai

Freemium
View
Akool AI logo
Content & writing

Akool AI

Revolutionizing Video Production with AI-Powered Creativity

Paid
View

Extend an image past the frame and let AI fill the new aspect ratio.

Freemium
View
StarByFace logo
Security

StarByFace

Discover your celebrity doppelgänger with StarByFace!

Free
View
C

ChainClarity explains 700+ crypto whitepapers in plain English, with layered summaries, comparisons, research tools, alerts, and a $4.99 Pro plan.

Freemium
View
Opus Clip logo
Coding & apps

Opus Clip

Opus.ai: Revolutionize Your Web Experience

Free
View