Pymatgen

# Pymatgen Analysis Modules Reference

This reference documents pymatgen's extensive analysis capabilities for materials characterization, property prediction, and computational analysis.

## Phase Diagrams and Thermodynamics

### Phase Diagram Construction

```python
from pymatgen.analysis.phase_diagram import PhaseDiagram, PDPlotter
from pymatgen.entries.computed_entries import ComputedEntry

# Create entries (composition and total energy)
entries = [
    ComputedEntry("Fe", -8.4),
    ComputedEntry("O2", -4.9),
    ComputedEntry("FeO", -6.7),
    ComputedEntry("Fe2O3", -8.3),
    ComputedEntry("Fe3O4", -9.1),
]

# Build phase diagram
pd = PhaseDiagram(entries)

# Get stable entries
stable_entries = pd.stable_entries

# Get energy above hull (stability)
entry_to_test = ComputedEntry("Fe2O3", -8.0)
energy_above_hull = pd.get_e_above_hull(entry_to_test)

# Get decomposition products
decomp = pd.get_decomposition(entry_to_test.composition)
# Returns: {entry1: fraction1, entry2: fraction2, ...}

# Get equilibrium reaction energy
rxn_energy = pd.get_equilibrium_reaction_energy(entry_to_test)

# Plot phase diagram
plotter = PDPlotter(pd)
plotter.show()
plotter.write_image("phase_diagram.png")
```

### Chemical Potential Diagrams

```python
from pymatgen.analysis.phase_diagram import ChemicalPotentialDiagram

# Create chemical potential diagram
cpd = ChemicalPotentialDiagram(entries, limits={"O": (-10, 0)})

# Get domains (stability regions)
domains = cpd.domains
```

### Pourbaix Diagrams

Electrochemical phase diagrams with pH and potential axes.

```python
from pymatgen.analysis.pourbaix_diagram import PourbaixDiagram, PourbaixPlotter
from pymatgen.entries.computed_entries import ComputedEntry

# Create entries with corrections for aqueous species
entries = [...]  # Include solids and ions

# Build Pourbaix diagram
pb = PourbaixDiagram(entries)

# Get stable entry at specific pH and potential
stable_entry = pb.get_stable_entry(pH=7, V=0)

# Plot
plotter = PourbaixPlotter(pb)
plotter.show()
```

## Structure Analysis

### Structure Matching and Comparison

```python
from pymatgen.analysis.structure_matcher import StructureMatcher

matcher = StructureMatcher()

# Check if structures match
is_match = matcher.fit(struct1, struct2)

# Get mapping between structures
mapping = matcher.get_mapping(struct1, struct2)

# Group similar structures
grouped = matcher.group_structures([struct1, struct2, struct3, ...])
```

### Ewald Summation

Calculate electrostatic energy of ionic structures.

```python
from pymatgen.analysis.ewald import EwaldSummation

ewald = EwaldSummation(struct)
total_energy = ewald.total_energy  # In eV
forces = ewald.forces  # Forces on each site
```

### Symmetry Analysis

```python
from pymatgen.symmetry.analyzer import SpacegroupAnalyzer

sga = SpacegroupAnalyzer(struct)

# Get space group information
spacegroup_symbol = sga.get_space_group_symbol()  # e.g., "Fm-3m"
spacegroup_number = sga.get_space_group_number()   # e.g., 225
crystal_system = sga.get_crystal_system()           # e.g., "cubic"

# Get symmetrized structure
sym_struct = sga.get_symmetrized_structure()
equivalent_sites = sym_struct.equivalent_sites

# Get conventional/primitive cells
conventional = sga.get_conventional_standard_structure()
primitive = sga.get_primitive_standard_structure()

# Get symmetry operations
symmetry_ops = sga.get_symmetry_operations()
```

## Local Environment Analysis

### Coordination Environment

```python
from pymatgen.analysis.local_env import (
    VoronoiNN,           # Voronoi tessellation
    CrystalNN,           # Crystal-based
    MinimumDistanceNN,   # Distance cutoff
    BrunnerNN_real,      # Brunner method
)

# Voronoi nearest neighbors
voronoi = VoronoiNN()
neighbors = voronoi.get_nn_info(struct, n=0)  # Neighbors of site 0

# CrystalNN (recommended for most cases)
crystalnn = CrystalNN()
neighbors = crystalnn.get_nn_info(struct, n=0)

# Analyze all sites
for i, site in enumerate(struct):
    neighbors = voro