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    davila7

    pymatgen

    davila7/pymatgen
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    About

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

    SKILL.md

    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")
    
    # 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

    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

    • Documentation: https://pymatgen.org/
    • Materials Project: https://materialsproject.org/
    • GitHub: https://github.com/materialsproject/pymatgen
    • Forum: https://matsci.org/
    • Example notebooks: https://matgenb.materialsvirtuallab.org/

    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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