Miguel A.L. Marques

Computing metallic conductivity from first principles is expensive, so large chemical spaces have gone largely unscreened. This workflow ranks about 2.8 million ordered compounds using two machine-learning proxies, a BoltzTraP2 conductivity under the constant relaxation-time approximation and the Eliashberg electron-phonon coupling λ, combined by symbolic regression into σSR=0.4σBT/λ, then runs full electron-phonon transport on the candidates. Be2IrPt, H3NaNi, LuIr and LiBePt2 reach room-temperature conductivities of roughly 34 to 38×10⁶ S/m, comparable to aluminum's 36.59×10⁶ S/m but still below Ag, Au and Cu.

Computing metallic conductivity from first principles is expensive, so large chemical spaces have gone largely unscreened. This workflow ranks about 2.8 million ordered compounds using two machine-learning proxies, a BoltzTraP2 conductivity under the constant relaxation-time approximation and the Eliashberg electron-phonon coupling λ, combined by symbolic regression into σSR=0.4σBT/λ, then runs full electron-phonon transport on the candidates. Be2IrPt, H3NaNi, LuIr and LiBePt2 reach room-temperature conductivities of roughly 34 to 38×10⁶ S/m, comparable to aluminum's 36.59×10⁶ S/m but still below Ag, Au and Cu.