OLED / Oliynyk

OLED = Oliynyk Elemental Data: 22 physics/chemistry properties for 76 elements, for composition featurization (ML).

from cifkit.sources.oliynyk import Oliynyk, Property

oled = Oliynyk()                    # not a separate package
oled.db["Si"][Property.AW]          # Property is a str Enum (column key)
oled.to_csv("oled.csv")
df = oled.to_dataframe()            # shape (76, 23)

Method	Returns
list_supported_elements()	list[str] (76 symbols)
is_formula_supported(formula)	bool
get_supported_formulas(formulas)	(supported, unsupported)
get_property_data(Property)	dict[symbol, float]
get_property_data_for_formula(formula, Property)	dict[symbol, float]
to_dataframe()	pandas.DataFrame
to_csv(path)	str path written

Exact Property members

AW, ATOMIC_NUMBER, PERIOD, GROUP, MEND_NUM, VAL_TOTAL, UNPARIED_E, GILMAN, Z_EFF, ION_ENERGY, COORD_NUM, RATIO_CLOSEST, POLYHEDRON_DISTORT, CIF_RADIUS, PAULING_RADIUS_CN12, PAULING_EN, MARTYNOV_BATSANOV_EN, MELTING_POINT_K, DENSITY, SPECIFIC_HEAT, COHESIVE_ENERGY, BULK_MODULUS.

Use UNPARIED_E (as shipped). Column for VAL_TOTAL is valencee_total.

What each property means (definitions + ML context from the dataset paper’s Table 1): see the full table on the OLED tutorial and the short list in the API quick reference. Parent 98-feature Excel: Mendeley Data bt6gv5z6yv.

Formula → ML feature vector

from cifkit.parsers.formula import Formula
from cifkit.sources.oliynyk import Oliynyk, Property

oled = Oliynyk()
parsed = Formula("NdSi2").parsed_formula
total = sum(c for _, c in parsed)
features = {
    prop.value: sum(oled.db[el][prop] * c for el, c in parsed) / total
    for prop in Property
}

Tutorial (full table + CSV): OLED
Calibrated tables: API quick reference
LLM recipes: llms.txt
Dataset paper: https://doi.org/10.1016/j.dib.2024.110178

Oliynyk

class cifkit.sources.oliynyk.Oliynyk

Bases: object

OLED (Oliynyk elemental data) — 22 properties × 76 elements.

OLED is the short name for this table. Load it only via this class:

from cifkit.sources.oliynyk import Oliynyk, Property
oled = Oliynyk()
oled.db["Si"][Property.AW]
oled.to_csv("oled.csv")

db

Nested map symbol -> {property_column: value}. Property columns match Property enum .value strings (e.g. "atomic_weight").

Type:

dict[str, dict[str, float]]

elements

Supported element symbols (length 76), same order as loaded from Excel.

Type:

list[str]

Notes

Dataset paper (Data in Brief): https://doi.org/10.1016/j.dib.2024.110178 Docs: https://bobleesj.github.io/cifkit/tutorials/oled.html

get_oliynyk_CAF_data() → dict[str, dict[str, float]]

Load the Oliynyk elemental property data from an Excel file. The data is stored in a dictionary format with element symbols as keys.

Examples

>>> oliynyk = Oliynyk()
>>> data = oliynyk.get_oliynyk_CAF_data()
{
    "Li": {"atomic_weight": 6.941, ...},
    "Be": {"atomic_weight": 9.0122, ...},
    ...
}
>>> data["Li"]["atomic_weight"]
6.941

is_formula_supported(formula: str) → bool

Check if a formula is supported by the Oliynyk database.

Examples

>>> oliynyk = Oliynyk()
>>> oliynyk.is_formula_supported("LiFePO4")
True
>>> oliynyk.is_formula_supported("FeH")
False

get_supported_formulas(formulas: list[str]) → tuple[list[str], list[str]]

Filter formulas to only include those with supported elements.

Examples

>>> oliynyk = Oliynyk()
>>> formulas = ["FeH", "NdSi2"]
>>> supported, unsupported = oliynyk.get_supported_formulas(formulas)
>>> supported
["NdSi2"]
>>> unsupported
["FeH"]

list_supported_elements() → list[str]

List all elements in the Oliynyk database.

Examples

>>> oliynyk = Oliynyk()
>>> elements = oliynyk.list_supported_elements()
>>> elements
["Li", "Be", "B", "C", "Na", "Mg", "Al", "Si", "P", "S", ...]

get_property_data_for_formula(formula: str, property: Property) → dict[str, float]

Get property data for individual elements in a given formula.

Examples

>>> oliynyk = Oliynyk()
>>> oliynyk.get_property_data_for_formula("LiFeP", Property.AW)
{"Li": 6.941, "Fe": 55.845, "O": 15.999}

get_property_data(property: Property) → dict[str, float]

Get the given property data for all elements in the database.

Examples

>>> oliynyk = Oliynyk()
>>> property_data = oliynyk.get_property_data(Property.AW)
>>> property_data
{"Li": 6.941, "Be": 9.0122, "B": 10.81, ...}

to_dataframe() → DataFrame

Return the full OLED (Oliynyk elemental data) table as a pandas.DataFrame.

Rows are elements (one per supported symbol); columns are symbol plus the 22 property keys. Sorted by atomic number.

Examples

>>> oliynyk = Oliynyk()
>>> df = oliynyk.to_dataframe()
>>> df.shape
(76, 23)
>>> df.loc[df["symbol"] == "Si", "atomic_weight"].iloc[0]
28.0855

to_csv(path: str) → str

Write the OLED table to a CSV file and return the path.

Parameters:

path (str) – Destination file path (created or overwritten).

Returns:

The same path, for convenient chaining.

Return type:

str

Examples

>>> oliynyk = Oliynyk()
>>> oliynyk.to_csv("oled.csv")
'oled.csv'

Property

class cifkit.sources.oliynyk.Property(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)

Bases: str, Enum

OLED property keys. Members are str enums: use as dict keys.

Exact member names (do not rename when generating code):

AW, ATOMIC_NUMBER, PERIOD, GROUP, MEND_NUM, VAL_TOTAL, UNPARIED_E,
GILMAN, Z_EFF, ION_ENERGY, COORD_NUM, RATIO_CLOSEST, POLYHEDRON_DISTORT,
CIF_RADIUS, PAULING_RADIUS_CN12, PAULING_EN, MARTYNOV_BATSANOV_EN,
MELTING_POINT_K, DENSITY, SPECIFIC_HEAT, COHESIVE_ENERGY, BULK_MODULUS

Note the shipped spelling UNPARIED_E and column valencee_total.

AW = 'atomic_weight'

ATOMIC_NUMBER = 'atomic_number'

PERIOD = 'period'

GROUP = 'group'

MEND_NUM = 'Mendeleev_number'

VAL_TOTAL = 'valencee_total'

UNPARIED_E = 'unpaired_electrons'

GILMAN = 'Gilman'

Z_EFF = 'Z_eff'

ION_ENERGY = 'ionization_energy'

COORD_NUM = 'coordination_number'

RATIO_CLOSEST = 'ratio_closest'

POLYHEDRON_DISTORT = 'polyhedron_distortion'

CIF_RADIUS = 'CIF_radius'

PAULING_RADIUS_CN12 = 'Pauling_radius_CN12'

PAULING_EN = 'Pauling_EN'

MARTYNOV_BATSANOV_EN = 'Martynov_Batsanov_EN'

MELTING_POINT_K = 'melting_point_K'

DENSITY = 'density'

SPECIFIC_HEAT = 'specific_heat'

COHESIVE_ENERGY = 'cohesive_energy'

BULK_MODULUS = 'bulk_modulus'

classmethod display()

Display the available elemental properties in a user-friendly format.

Examples

>>> Property.display()
Available elemental properties:
  1. AW - atomic_weight
  2. ATOMIC_NUMBER - atomic_number
  ...

classmethod select()

Prompt the user to select an elemental property from the available options. Returns the selected property.

Examples

>>> selected_property = Property.select()
Available elemental properties:
  1. AW - atomic_weight
  2. ATOMIC_NUMBER - atomic_number
  ...

Enter the number of the property to use: 1