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. license MIT license metadata {"skill-author":"K-Dense Inc."} 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: .2 f} 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' ]: .3 f} 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: .4 f} 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' ]: .3 f} 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(): .3 f} 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: .2 f} Ų" ) print ( f"Volume: {wulff.volume: .2 f} 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: Get API key from https://next-gen.materialsproject.org/ 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" )