hadokenmaterials.io (BETA)The High Throughput Machine Learning Materials Design Platform |
Use this model created via deep learning for fast and accurate predictions of a material's gap type using stoichiometry and space group.
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}/MachineLearning/GapType/SpaceGroup
POST
{ "spaceGroup": 129, "stoichiometry": "Ag10O8P2Te2" }
JSON - response
{ "halfMetal": 0.0000000001208971313097922044; "insulatorDirect": 0.0276288844767050804013304393; "insulatorDirectSpinPolarised": 0.000000000000000000333201382; "insulatorIndirect": 0.972054870642805564504263858; "insulatorIndirectSpinPolarised": 0.0000000000001151086947130958; "metal": 0.0003162447594771147566990205; "spaceGroup": 129, "stoichiometry": "Ag10O8P2Te2" }
XML - response
<GapTypeSpaceGroupModel xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <HalfMetal>0.0000000001208971313097922044</HalfMetal> <InsulatorDirect>0.0276288844767050804013304393</InsulatorDirect> <InsulatorDirectSpinPolarised>0.000000000000000000333S201382</InsulatorDirectSpinPolarised> <InsulatorIndirect>0.972054870642805564504263858</InsulatorIndirect> <InsulatorIndirectSpinPolarised>0.0000000000001151086947130958</InsulatorIndirectSpinPolarised> <Metal>0.0003162447594771147566990205</Metal> <SpaceGroup>129</SpaceGroup>> <Stoichiometry>Cr4Cu1In1Se8</Stoichiometry> </GapTypeSpaceGroupModel>
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