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Band Gap - Space Group, Derived - Deep Learning

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Use this model created via deep learning for fast and accurate predictions of band gap using stoichiometry, space group, and attributes derived from those values.

Load example values into the form.

Try it Yourself

Enter the corresponding values to try the approximation for yourself.

Specify the full stoichiometry
 

** Use of this web page reqiures correct Citing and attribution in any or all work and/or papers produced from results generated by this service.

API

You can access the single-attribute band gap predictor here:

URL format: /api/v{Version}/BandGap/Single

POST

{
	"stoichiometry": "Ca2Cu2Ge4O12",
	"spaceGroup": 15
}

JSON - response

{
    "bandGap": 1.0886605111631546614381073308,
    "spaceGroup": 15,
    "stoichiometry": "Ca2Cu2Ge4O12"
}

XML - response

<BandGapSpaceGroupHighSymmetryDerivedModel xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema">
    <BandGap>1.0886605111631546614381073308</BandGap>
    <SpaceGroup>12</SpaceGroup>
    <Stoichiometry>Ca2Cu2Ge4O12</Stoichiometry>
</BandGapSpaceGroupHighSymmetryDerivedModel>

 

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