This is the full list of identified candidate superconductors in the paper "Discovery of Novel Superconducting Materials with Deep Learning" in the IEEE Quantum Week 2023 Proceedings.
mp-id | Formula | Space Group | Stable | Energy Above Hull (eV/atom) | Experimentally Observed | Predicted Tc (K) | Predicted Tc Std. Dev. (K) | Closest Known Superconductor | Closest Superconductor Distance | Log Probability of Superconductivity | |
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mp-id | Formula | Space Group | Stable | Energy Above Hull (eV/atom) | Experimentally Observed | Predicted Tc (K) | Predicted Tc Std. Dev. (K) | Closest Known Superconductor | Closest Superconductor Distance | Log Probability of Superconductivity | |
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This table provides a (very rough) bulk estimate of cost per kg and relative abundance of each Element with respect to composition in Earth's crust. This data is used in the next table to organize superconductors by cost.
Z | Symbol | Name | Abundance in Crust (mg/kg) | USD/kg | Year | Source |
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mp-id | Formula | Composition-Weighted Cost$^*$ (USD/kg) | Limiting Abundance$^{**}$ (mg/kg) | Stable | Predicted Tc (K) | Oxide | Log Probability of Superconductivity | |
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*Composition-Weighted Cost: Estimated cost of the material weighted by elemental composition only. Cost of production and any reagents is not taken into account.
**Limiting Abundance: Estimated milligrams of material (limited by least abundant element) per kg of Earth's crust, assuming uniform distribution of elements in the crust.