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Structured Representation of Materials

We present an example of our approach towards defining and storing structured data for materials. The aspects presented herein complement the general introduction.

Example Representation

In the expandable section below, the user can find an example JSON representation of a face-centered cubic Silicon:

Expand to view

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{
    "name" : "Silicon FCC",
    "basis" : {
        "units" : "crystal",
        "elements" : [
            {
                "id" : 1,
                "value" : "Si"
            },
            {
                "id" : 2,
                "value" : "Si"
            }
        ],
        "coordinates" : [
            {
                "id" : 1,
                "value" : [
                    0,
                    0,
                    0
                ]
            },
            {
                "id" : 2,
                "value" : [
                    0.25,
                    0.25,
                    0.25
                ]
            }
        ]
    },
    "lattice" : {
        "a" : 3.867,
        "c" : 3.867,
        "b" : 3.867,
        "units" : {
            "length" : "angstrom",
            "angle" : "degree"
        },
        "alpha" : 60,
        "type" : "FCC",
        "beta" : 60,
        "gamma" : 60,
        "vectors" : {
            "a" : [
                3.34892,
                0,
                1.9335
            ],
            "b" : [
                1.116307,
                3.157392,
                1.9335
            ],
            "c" : [
                0,
                0,
                3.867
            ],
            "alat" : 1,
            "units" : "angstrom"
        }
    },
    "formula" : "Si",
    "unitCellFormula" : "Si2",
    "tags" : [
        "silicon"
    ],
    "derivedProperties" : [
        {
            "units" : "angstrom^3",
            "name" : "volume",
            "value" : 40.88909038874689
        }
    ],
    "exabyteId" : "e3nJ9g7tLaARSA25g",
    "createdAt" : "2016-10-27T07:35:53.740Z",
    "updatedAt" : "2017-08-12T09:22:19.468Z",
    "hash" : "fa78cb87eb5c25d1661a8ba5c0654d24",
    "scaledHash" : "a4b8b020e89ff7c1c1c7b7bcf19de84e"
}

Explanation of Keywords

Keyword Short Description Details
basis Crystal basis with explicit identification per atom The information about the atomic type and coordinates
lattice Crystal lattice in both Bravais and vector notations Crystal lattice parameters - lattice constants and angles. Components of the corresponding lattice vectors are also included.
derivedProperties descriptive properties derived from lattice/basis (only one example shown above) Additional properties of the crystal structure under investigation as explained in the section ensuing the present table.
hash Hash string calculated by the Bank Mapping Function Structure-based hash string for the primitive standard representation of this material, calculated when checking this material against existing entries within the Materials Bank
scaledHash As above, but for the lattice axis scaled to 1.0 (i.e. to identify same structures under different uniform pressure) This hash string is calculated by scaling all the dimensions of the primitive unit cell representation of the material by the a lattice constant

Derived Properties

As seen above, we use the crystal lattice and basis JSON objects as the main identifying properties. Based upon them, we calculate the derivedProperties, that may include such information as:

  • the unit cell volume,
  • density,
  • chemical formula,
  • and a large number of other possibilities.

For every material imported/uploaded to our platform, we pre-calculate a set of such descriptors, and store them inside this "derivedProperties" section. This information can be further used during data analysis or the construction of statistical predictive models.