--- name: pymatgen-materials-19b2b9016e28 description: "Materials science computation with pymatgen. Use when: (1) crystal structure creation and manipulation, (2) phase diagram construction, (3) electronic structure analysis, (4) symmetry and space group operations, (5) VASP input/output parsing. NOT for: molecular chemistry (use rdkit-chemistry), protein structure (use biopython-bio), or general numerical computation (use scipy-analysis)." metadata: { "openclaw": { "emoji": "💎", "requires": { "bins": ["python3"] }, "install": [{ "id": "uv-pymatgen", "kind": "uv", "package": "pymatgen" }] } } --- # Pymatgen Materials Science Materials science analysis using pymatgen for crystal structures, phase diagrams, electronic structure, and computational materials workflows. ## When to Use - Crystal structure creation, manipulation, and visualization - Phase diagram construction and thermodynamic stability analysis - Electronic structure (band structure, DOS) parsing and plotting - Symmetry analysis and space group determination - Reading/writing VASP, CIF, POSCAR, and other structure formats ## When NOT to Use - Molecular chemistry or drug design (use rdkit-chemistry) - Protein or biomolecular structure (use biopython-bio) - General plotting without materials context (use matplotlib-viz) - Machine learning on materials data (use dedicated ML frameworks) ## Crystal Structure Creation ```python from pymatgen.core import Structure, Lattice, Molecule # Create from spacegroup and Wyckoff positions structure = Structure.from_spacegroup( "Fm-3m", Lattice.cubic(5.43), ["Si"], [[0, 0, 0]] ) # Create from file structure = Structure.from_file("POSCAR") structure = Structure.from_file("structure.cif") # Create manually with lattice parameters lattice = Lattice.from_parameters(a=3.84, b=3.84, c=3.84, alpha=90, beta=90, gamma=90) structure = Structure(lattice, ["Cu", "Cu", "Cu", "Cu"], [[0, 0, 0], [0.5, 0.5, 0], [0.5, 0, 0.5], [0, 0.5, 0.5]]) # Hexagonal lattice lattice = Lattice.hexagonal(a=2.46, c=6.71) ``` ## Structure Properties and Manipulation ```python # Basic properties print(structure.lattice) # lattice vectors print(structure.lattice.abc) # a, b, c lengths print(structure.lattice.angles) # alpha, beta, gamma print(structure.volume) # unit cell volume print(structure.density) # density in g/cm^3 print(structure.composition) # chemical formula print(len(structure)) # number of sites # Space group and symmetry from pymatgen.symmetry.analyzer import SpacegroupAnalyzer sga = SpacegroupAnalyzer(structure) print(sga.get_space_group_symbol()) # e.g., "Fm-3m" print(sga.get_space_group_number()) # e.g., 225 print(sga.get_point_group_symbol()) # e.g., "m-3m" conventional = sga.get_conventional_standard_structure() primitive = sga.get_primitive_standard_structure() # Supercell and perturbation supercell = structure.copy() supercell.make_supercell([2, 2, 2]) structure.perturb(0.01) # random perturbation # Write to file structure.to(filename="POSCAR") structure.to(filename="output.cif") structure.to(fmt="poscar") # return as string ``` ## Phase Diagrams ```python from pymatgen.analysis.phase_diagram import PhaseDiagram, PDPlotter, PDEntry from pymatgen.core import Composition # Build entries from computed energies entries = [ PDEntry(Composition("Li"), -1.9), PDEntry(Composition("Fe"), -8.3), PDEntry(Composition("O"), -4.95), PDEntry(Composition("LiFePO4"), -43.2), PDEntry(Composition("FePO4"), -38.5), PDEntry(Composition("Li3PO4"), -25.6), ] # Construct phase diagram pd = PhaseDiagram(entries) # Stability analysis for entry in entries: ehull = pd.get_e_above_hull(entry) print(f"{entry.composition.reduced_formula}: E_above_hull = {ehull:.3f} eV/atom") # Decomposition products decomp, ehull = pd.get_decomp_and_e_above_hull(entries[3]) for comp, amount in decomp.items(): print(f" {comp.reduced_formula}: {amount:.3f}") # Plot plotter = PDPlotter(pd) plotter.get_plot().savefig("phase_diagram.pdf") ``` ## Electronic Structure ```python from pymatgen.io.vasp import Vasprun, BSVasprun from pymatgen.electronic_structure.plotter import BSPlotter, DosPlotter # Parse VASP output vasprun = Vasprun("vasprun.xml", parse_dos=True, parse_eigen=True) print(f"Final energy: {vasprun.final_energy} eV") print(f"Converged: {vasprun.converged}") # Band structure bs_vasprun = BSVasprun("vasprun.xml") bs = bs_vasprun.get_band_structure(line_mode=True) print(f"Band gap: {bs.get_band_gap()['energy']:.3f} eV") print(f"Direct: {bs.get_band_gap()['direct']}") bs_plotter = BSPlotter(bs) bs_plotter.get_plot().savefig("band_structure.pdf") # Density of states dos = vasprun.complete_dos dos_plotter = DosPlotter() dos_plotter.add_dos("Total", dos) dos_plotter.add_dos_dict(dos.get_element_dos()) dos_plotter.get_plot().savefig("dos.pdf") ``` ## VASP I/O ```python from pymatgen.io.vasp import Poscar, Incar, Kpoints, Outcar # Read VASP files poscar = Poscar.from_file("POSCAR") structure = poscar.structure incar = Incar.from_file("INCAR") print(incar["ENCUT"]) kpoints = Kpoints.from_file("KPOINTS") outcar = Outcar("OUTCAR") print(f"Total magnetization: {outcar.total_mag}") print(f"Final energy: {outcar.final_energy}") # Create VASP input set from pymatgen.io.vasp.sets import MPRelaxSet relax_set = MPRelaxSet(structure) relax_set.write_input("vasp_input/") ``` ## Best Practices 1. Always check symmetry with `SpacegroupAnalyzer` after structure creation. 2. Use `get_primitive_standard_structure()` to reduce computational cost. 3. Validate structures with `structure.is_valid()` before running calculations. 4. Use Materials Project API (`MPRester`) to fetch known structures and energies. 5. When comparing energies, normalize per atom (`energy / len(structure)`). 6. Save structures in CIF format for archival and POSCAR for VASP input. 7. Use `structure.get_neighbors()` for local environment analysis. 8. Check convergence flags in `Vasprun` before trusting computed properties. --- Source attribution: beita6969 Original project: https://github.com/beita6969/ScienceClaw/blob/e925f732c7ca435f557e88075bc47a58f1e984f1/skills/pymatgen-materials/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Copyright (c) 2025 Peter Steinberger Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: beita6969 Original project: https://github.com/beita6969/ScienceClaw/blob/e925f732c7ca435f557e88075bc47a58f1e984f1/skills/pymatgen-materials/SKILL.md Attribution basis: Source repository record Fields of work: Data & Analytics, Development & Engineering, Education & Research Roles: Data Scientist, ML / AI Engineer, Researcher Specialties: API Tools: Pymatgen Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: 99ac87a43548f0d884de720f8480178adb81eb80a97295454d4b07b4e44f76da