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# Phase diagrams and Pourbaix diagrams

class `ase.phasediagram.``PhaseDiagram`(references, filter='', verbose=True)

  Phase-diagram.

  references: list of (name, energy) tuples
    List of references. The energy must be the total energy and not energy per atom. The names can also be dicts like `{'Zn': 1, 'O': 2}` which would be equivalent to `'ZnO2'`.
  filter: str or list of str
    Use only those references that match the given filter. Example: `filter='ZnO'` will select those that contain zinc or oxygen.
  verbose: bool
    Write information.

Here is a simple example using some made up numbers for Cu-Au alloys:

    >>> from ase.phasediagram import PhaseDiagram
    >>> refs = [('Cu', 0.0),
    ...         ('Au', 0.0),
    ...         ('CuAu', -0.5),
    ...         ('Cu2Au', -0.7),
    ...         ('Cu2Au', -0.2)]
    >>> pd = PhaseDiagram(refs)
    Species: Au, Cu
    References: 5
    0    Cu             0.000
    1    Au             0.000
    2    CuAu          -0.500
    3    Cu2Au         -0.700
    4    CuAu2         -0.200
    Simplices: 3

The convex hull looks like this:

    >>> pd.plot(show=True)

`PhaseDiagram.``plot`(ax=None, dims=None, show=False)

  Make 2-d or 3-d plot of datapoints and convex hull.

  Default is 2-d for 2- and 3-component diagrams and 3-d for a 4-component diagram.

If you want to see what Cu3Au will decompose into, you can use the `decompose()` method:

    >>> energy, indices, coefs = pd.decompose('Cu3Au')
    reference    coefficient      energy
    ------------------------------------
    Cu                     1       0.000
    Cu2Au                  1      -0.700
    ------------------------------------
    Total energy:                 -0.700
    ------------------------------------
    >>> print(energy, indices, coefs)
    (-0.69999999999999996, array([0, 3], dtype=int32), array([ 1.,  1.]))

Alternatively, one could have used `pd.decompose(Cu=3, Au=1)`.

`PhaseDiagram.``decompose`(formula=None, **kwargs)

  Find the combination of the references with the lowest energy.

  formula: str
    Stoichiometry. Example: `'ZnO'`. Can also be given as keyword arguments: `decompose(Zn=1, O=1)`.

  Example:

      pd = PhaseDiagram(...)
      pd.decompose(Zn=1, O=3)

  Returns energy, indices of references and coefficients.

Here is an example (see `ktao.py`) with three components using `plot(dims=2)` and `plot(dims=3)`:

## Pourbaix diagrams

Let’s create a Pourbaix diagram for ZnO from experimental numbers.

    >>> from ase.phasediagram import Pourbaix, solvated
    >>> refs = solvated('Zn')
    >>> print(refs)
    [('HZnO2-(aq)', -4.801274772854441), ('ZnO2--(aq)', -4.0454382546928365), ('ZnOH+(aq)', -3.5207324675582736), ('ZnO(aq)', -2.9236086089762137), ('H2O(aq)', -2.458311658897383), ('Zn++(aq)', -1.5264168353005447), ('H+(aq)', 0.0)]

We use the `solvated()` function to get solvation energies for zinc containing molecules (plus water and a proton):

`ase.phasediagram.``solvated`(symbols)

  Extract solvation energies from database.

  symbols: str
    Extract only those molecules that contain the chemical elements given by the symbols string (plus water and H+).

  Data from:

  > Johnson JW, Oelkers EH, Helgeson HC (1992) Comput Geosci 18(7):899. doi:10.1016/0098-3004(92)90029-Q

  and:

  > Pourbaix M (1966) Atlas of electrochemical equilibria in aqueous solutions. No. v. 1 in Atlas of Electrochemical Equilibria in Aqueous Solutions. Pergamon Press, New York.

  Returns list of (name, energy) tuples.

We add two solids and one more dissolved molecule to the references and create a `Pourbaix` object:

    >>> refs += [('Zn', 0.0), ('ZnO', -3.323), ('ZnO2(aq)', -2.921)]
    >>> pb = Pourbaix(refs, Zn=1, O=1)

To see what ZnO will `decompose()` to at a potential of 1 eV and a pH of 9.0, we do this:

    >>> coefs, energy = pb.decompose(1.0, 9.0)
    0    HZnO2-(aq)    -5.158
    1    ZnO2--(aq)    -4.403
    2    ZnOH+(aq)     -3.878
    3    ZnO(aq)       -3.281
    4    H2O(aq)       -2.458
    5    Zn++(aq)      -1.884
    6    H+(aq)        -0.536
    7    Zn             0.000
    8    ZnO           -3.323
    9    ZnO2(aq)      -3.278
    10   e-            -1.000
    reference    coefficient      energy
    ------------------------------------
    H2O(aq)               -1      -2.458
    H+(aq)                 2      -0.536
    ZnO2(aq)               1      -3.278
    e-                     2      -1.000
    ------------------------------------
    Total energy:                 -3.891
    ------------------------------------
    >>> print(coefs, energy)
    (array([  0.00000000e+00,   0.00000000e+00,   6.66133815e-16,
             0.00000000e+00,  -1.00000000e+00,   0.00000000e+00,
             2.00000000e+00,   0.00000000e+00,   0.00000000e+00,
             1.00000000e+00,   2.00000000e+00]), -3.8913313372636829)

The full `diagram()` is calculated like this:

    >>> import numpy as np
    >>> U = np.linspace(-2, 2, 200)
    >>> pH = np.linspace(-2, 16, 300)
    >>> d, names, text = pb.diagram(U, pH, plot=True)

class `ase.phasediagram.``Pourbaix`(references, formula=None, T=300.0, **kwargs)

  Pourbaix object.

  references: list of (name, energy) tuples
    Examples of names: ZnO2, H+(aq), H2O(aq), Zn++(aq), …
  formula: str
    Stoichiometry. Example: `'ZnO'`. Can also be given as keyword arguments: `Pourbaix(refs, Zn=1, O=1)`.
  T: float
    Temperature in Kelvin.
  `decompose`(U, pH, verbose=True, concentration=1e-06)

    Decompose material.

    U: float
      Potential in V.
    pH: float
      pH value.
    verbose: bool
      Default is True.
    concentration: float
      Concentration of solvated references.

    Returns optimal coefficients and energy.

  `diagram`(U, pH, plot=True, show=False, ax=None)

    Calculate Pourbaix diagram.

    U: list of float
      Potentials in V.
    pH: list of float
      pH values.
    plot: bool
      Create plot.
    show: bool
      Open graphical window and show plot.
    ax: matplotlib axes object
      When creating plot, plot onto the given axes object. If none given, plot onto the current one.

Documentation v: 3.19.0

Versions
  3.20.0b1 (development)
  3.19.0 (latest stable)