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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.
Enter the corresponding values to try the approximation for yourself.
** 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.
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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