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Core classes: explicit chemistry, coordinates, and periodicity

This reference targets the verified pymatgen==2026.5.4 wrapper with pymatgen-core==2026.7.16. Core objects now ship from pymatgen-core but keep the public pymatgen.core namespace.

Units and representation

Pymatgen does not make every quantity "atomic units." Common contracts include:

• lattice vectors and Cartesian coordinates: Å
• lattice angles: degrees
• structure volume: ų
• density: g/cm³
• composition weight: amu for the represented composition
• electronic and entry energies: usually eV; phase-diagram normalized values: eV/atom

Read the specific method contract before combining quantities. Record units in every artifact.

Structure is periodic and owns a Lattice; Molecule is non-periodic. Structure coordinates are fractional by default. Molecule coordinates are Cartesian. Never infer which object or coordinate mode the user intended.

Element and Species

from pymatgen.core import DummySpecies, Element, Species

iron = Element("Fe")
silicon = Element.from_Z(14)
oxygen = Element.from_name("oxygen")
fe2 = Species("Fe", oxidation_state=2)
vacancy_label = DummySpecies("X")

Important distinctions:

• Element.symbol is the chemical symbol.
• Element.Z is atomic number.
• Element.X is Pauling electronegativity, not the symbol.
• Elemental properties can be missing or uncertain; do not replace missing values with zero.
• Species adds oxidation state and optional properties. Oxidation state is formal chemical annotation, not an automatically validated charge model.
• A dummy species is a modeling label, not a physical atom.

Current API documentation also exposes predicates and data such as is_metal, is_noble_gas, atomic_mass, oxidation-state sets, and electronic configuration. Check for None/missing values and retain property provenance.

Composition

Use strict parsing at external boundaries:

from pymatgen.core import Composition

composition = Composition("LiFePO4", strict=True)
formula = composition.formula
reduced = composition.reduced_formula
chemical_system = composition.chemical_system
mass_amu = float(composition.weight)

Construction from a mapping is explicit:

composition = Composition({"Fe": 2, "O": 3}, strict=True)

Safety rules:

1. Bound formula length before parsing.
2. Reject duplicate JSON keys, non-finite values, and non-positive amounts in external mappings.
3. Keep full and reduced formulas distinct. Reduction loses the integer scale.
4. A composition is not a structure, phase, oxidation-state assignment, or proof that a compound exists.
5. oxi_state_guesses() is heuristic and can be combinatorial. Call it only after explicit user approval and bound elements, formula size, runtime, and returned guesses.
6. Do not mix Element and oxidized Species keys without intentionally defining how charge decoration should behave.

The bundled validator does not guess by default:

python scripts/composition_structure_validator.py composition "Fe2O3"
python scripts/composition_structure_validator.py composition "Fe2O3" \
  --guess-oxidation-states

Lattice

from pymatgen.core import Lattice

cubic = Lattice.cubic(5.64)
triclinic = Lattice.from_parameters(
    a=4.0,
    b=5.0,
    c=6.0,
    alpha=80,
    beta=90,
    gamma=100,
)
matrix_lattice = Lattice(
    [
        [4.0, 0.0, 0.0],
        [0.5, 5.0, 0.0],
        [0.2, 0.3, 6.0],
    ],
    pbc=(True, True, True),
)

The matrix rows are lattice vectors. Preserve:

• matrix and (a, b, c)
• (alpha, beta, gamma)
• determinant/volume and handedness
• periodic-boundary-condition tuple
• whether the cell was reduced, standardized, strained, or transformed

Niggli/LLL reduction and crystallographic standardization can change the cell basis and site coordinates without changing intended periodic geometry. They still produce new representations and require provenance.

Structure and IStructure

The verified constructor includes explicit safety-relevant switches:

from pymatgen.core import Lattice, Structure

structure = Structure(
    lattice=Lattice.cubic(5.64),
    species=["Na", "Cl"],
    coords=[[0, 0, 0], [0.5, 0.5, 0.5]],
    coords_are_cartesian=False,
    validate_proximity=True,
    to_unit_cell=False,
)

Structure is mutable. IStructure is immutable/hashable. Prefer:

original = Structure.from_file("input.cif", primitive=False, sort=False)
derived = original.copy()
derived.make_supercell([2, 2, 2])

Do not mutate original in a provenance-sensitive workflow.

Disorder and occupancy

Each periodic site's species is a composition-like mapping. An ordered site has one species with occupancy 1. A disordered site can contain multiple species and fractional occupancies.

for index, site in enumerate(structure):
    occupancy_sum = sum(float(value) for value in site.species.values())
    print(index, site.species, occupancy_sum)

Before downstream analysis:

• report structure.is_ordered
• reject non-positive or overfull occupancy unless an explicitly documented parser tolerance explains a tiny rounding deviation
• preserve vacancy conventions and oxidation-state decoration
• check whether the target method supports disorder

Ordering a disordered structure changes the model and may create many candidates. It is never a format cleanup.

Coordinate safety

site.frac_coords and site.coords are fractional and Cartesian, respectively. Fractional coordinates outside [0, 1) can be valid periodic images; wrapping them is a transformation, not an automatic fix.

Record whether to_unit_cell, sorting, merging, primitive reduction, or standardization occurred. Check minimum periodic distances under a site-count bound; an all-pairs matrix is quadratic.

Oxidation states

Oxidation states can be attached to species:

decorated = structure.copy()
decorated.add_oxidation_state_by_element({"Na": 1, "Cl": -1})

This mutates the copied structure. Preserve the undecorated parent, mapping, method, and any charge-balance assumptions. add_oxidation_state_by_guess() is heuristic; do not invoke it implicitly.

Common methods

Current public operations include:

• Structure.from_file(path, primitive=False, sort=False, merge_tol=0.0)
• Structure.from_str(text, fmt=...)
• structure.to(filename=..., fmt=...)
• get_distance(i, j) and bounded neighbor methods
• get_primitive_structure()
• copy(), make_supercell(), apply_strain(), and site editing
• interpolate() for compatible endpoints

Every operation has assumptions. Interpolation does not establish a physical path; primitive/standard cells can alter site order and properties.

Molecule and IMolecule

from pymatgen.core import Molecule

water = Molecule(
    ["O", "H", "H"],
    [[0.0, 0.0, 0.0], [0.758, 0.0, 0.504], [-0.758, 0.0, 0.504]],
    charge=0,
    spin_multiplicity=1,
)

Molecule coordinates are Cartesian Å. Record:

• charge and spin multiplicity
• atom order, labels, and site properties
• coordinate origin/orientation
• whether hydrogens, bond perception, centering, or geometry generation changed the object

File formats often omit charge, multiplicity, bonding, isotope, or atom-label semantics. Molecule.from_file() parsing success does not prove those fields were present or preserved.

Explicit JSON serialization

Core objects expose as_dict() and from_dict():

import json
from pymatgen.core import Structure

payload = structure.as_dict()
text = json.dumps(payload, allow_nan=False, sort_keys=True)

decoded = json.loads(text)
restored = Structure.from_dict(decoded)

For untrusted JSON:

1. enforce byte, nesting, collection, and string limits
2. reject duplicate keys and non-finite numbers
3. validate the expected Structure schema
4. call the specific class constructor

Do not use pickle. Do not feed attacker-controlled MSON metadata to a general decoder that dynamically imports classes. JSON is only a syntax; schema validation is the trust boundary.

Validation checklist

• object kind (composition/molecule/periodic structure) is explicit
• units and coordinate mode are explicit
• lattice/PBC and charge/spin are recorded where applicable
• all parser warnings are preserved
• occupancy/disorder and oxidation states are reported
• coordinates and lattice values are finite
• minimum distances are checked under a bound
• original is immutable or retained unchanged
• output schema and maximum size are explicit
• provenance links every derived object to its parent checksum

Sources (verified 2026-07-23)

• pymatgen core API
• pymatgen usage guide
• pymatgen-core 2026.7.16 package metadata
• pymatgen 2026.5.4 package metadata
• pymatgen-core source
• pymatgen changelog