# ALIGNN

Active learning for materials and molecular property prediction treats high-uncertainty samples as the information a model is missing. Across formation energy, bandgap and solubility tasks, uncertainty came from loss-landscape sampling and from ensembles retrained with different seeds, then was calibrated with linear calibration factors and a neural network. Calibrated uncertainty generally did not reduce the data a model needed to improve on out-of-distribution data, showing no advantage over random sampling or uncalibrated estimates, and error bars overlapped.

Active learning for materials and molecular property prediction treats high-uncertainty samples as the information a model is missing. Across formation energy, bandgap and solubility tasks, uncertainty came from loss-landscape sampling and from ensembles retrained with different seeds, then was calibrated with linear calibration factors and a neural network. Calibrated uncertainty generally did not reduce the data a model needed to improve on out-of-distribution data, showing no advantage over random sampling or uncalibrated estimates, and error bars overlapped.

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.